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Lucas PM, Di Marco M, Cazalis V, Luedtke J, Neam K, Brown MH, Langhammer PF, Mancini G, Santini L. Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024:e14316. [PMID: 38946355 DOI: 10.1111/cobi.14316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 07/02/2024]
Abstract
Assessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land-use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species' range size and spatial configuration of the range, biological traits, climate change, and land-use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models' uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up-to-date IUCN RL.
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Affiliation(s)
- Pablo Miguel Lucas
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
- Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Sevilla, Spain
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Jennifer Luedtke
- IUCN SSC Amphibian Specialist Group, Toronto, Ontario, Canada
- Re:wild, Austin, Texas, USA
| | - Kelsey Neam
- IUCN SSC Amphibian Specialist Group, Toronto, Ontario, Canada
- Re:wild, Austin, Texas, USA
| | | | | | - Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
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2
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Wang B, Jägermeyr J, O'Leary GJ, Wallach D, Ruane AC, Feng P, Li L, Liu DL, Waters C, Yu Q, Asseng S, Rosenzweig C. Pathways to identify and reduce uncertainties in agricultural climate impact assessments. NATURE FOOD 2024; 5:550-556. [PMID: 39009735 DOI: 10.1038/s43016-024-01014-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/14/2024] [Indexed: 07/17/2024]
Abstract
Both climate and impact models are essential for understanding and quantifying the impact of climate change on agricultural productivity. Multi-model ensembles have highlighted considerable uncertainties in these assessments, yet a systematic approach to quantify these uncertainties is lacking. We propose a standardized approach to attribute uncertainties in multi-model ensemble studies, based on insights from the Agricultural Model Intercomparison and Improvement Project. We find that crop model processes are the primary source of uncertainty in agricultural projections (over 50%), excluding unquantified hidden uncertainty that is not explicitly measured within the analyses. We propose multidimensional pathways to reduce uncertainty in climate change impact assessments.
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Affiliation(s)
- Bin Wang
- New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, New South Wales, Australia.
- Gulbali Institute for Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, New South Wales, Australia.
| | - Jonas Jägermeyr
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, Climate School, New York, NY, USA
- Potsdam Institute for Climate Impacts Research, Member of the Leibniz Association, Potsdam, Germany
| | - Garry J O'Leary
- Agriculture Victoria, Department of Energy, Environment and Climate Action, Horsham, Victoria, Australia
- Faculty of Science, The University of Melbourne, Parkville, Victoria, Australia
| | - Daniel Wallach
- Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Puyu Feng
- College of Land Science and Technology, China Agricultural University, Beijing, China
| | - Linchao Li
- New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, New South Wales, Australia
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, China
| | - De Li Liu
- New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, New South Wales, Australia
- Gulbali Institute for Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, New South Wales, Australia
- Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | - Cathy Waters
- GreenCollar, The Rocks, Sydney, New South Wales, Australia
| | - Qiang Yu
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, China
| | - Senthold Asseng
- Technical University of Munich, School of Life Sciences, Digital Agriculture, HEF World Agricultural Systems Center, Freising, Germany.
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3
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Santos RS, Alencar JBR, Gallo R. Modeling the current and projected distribution of Brazilian peppertree Schinus terebinthifolia Raddi (Anacardiaceae) in the Americas. BRAZ J BIOL 2024; 84:e279769. [PMID: 38922189 DOI: 10.1590/1519-6984.279769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 05/01/2024] [Indexed: 06/27/2024] Open
Abstract
Global biodiversity is under substantial threat due to biological invasions, a problem exacerbated by climate change. Such invasions have detrimental effects on the environment, economy, and human health, resulting in significant financial burdens. Recently, understanding these challenges has become a highlighted priority within the scientific community. This study focuses on the evaluation of Schinus terebinthifolia, native to South America, and its invasive spread into North and Central America, which has resulted in wide distribution and considerable impact. The primary objectives of this study include analyzing the potential distribution of the species under current and future climate scenarios, identifying the areas where its climatic niche is changing. Data collection encompassed a vast dataset of over 30,000 occurrence records of this species, from the following databases: (1) The Global Biodiversity Information Facility provided 22,163 records (GBIF), (2) The virtual Herbarium Reflora contributed 1,438 records, and NeoTropTree made available 6,591 records. Following a rigorous filtering process, 992 occurrences were considered for modeling. In this process, we utilized climate data and climate projections, employing various algorithms, with an emphasis on the consensus model methodology. The research results reveal a clear trend of reduced habitat suitability for S. terebinthifolia, especially under scenarios of high global warming. This accentuates the urgency of implementing emission control measures and mitigation strategies. Additionally, the study underscores the crucial importance of continuous monitoring, as well as actions for controlling and restoring affected ecosystems. The significant role played by S. terebinthifolia in both its native and invaded areas highlights the need for comprehensive management approaches. In the face of climate change and biodiversity threats, this study provides insightful observations on the dynamics of biological invasions. Success in addressing these issues relies on close cooperation between the scientific community, policymakers, land managers, and local communities. This collaboration is essential for guiding and conducting conservation and biodiversity management efforts in an ever-evolving world.
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Affiliation(s)
- R S Santos
- Universidade Federal Rural de Pernambuco - UFRPE, Programa de Pós-graduação em Ciências Florestais, Recife, PE, Brasil
| | - J B R Alencar
- Universidade Federal do Amazonas - UFAM, Departamento de Biologia, Manaus, AM, Brasil
- Instituto Nacional de Pesquisas da Amazônia - INPA, Coordenação de Pesquisas em Biodiversidade, Laboratório de Citotaxonomia e Insetos Aquáticos, Manaus, AM, Brasil
| | - R Gallo
- Universidade Federal Rural de Pernambuco - UFRPE, Departamento de Engenharia Florestal, Recife, PE, Brasil
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Abdelaal M, AL-Huqail AA, Alghanem SMS, Alhaithloul HAS, Al-Robai SA, Abeed AHA, Dakhil MA, El-Barougy RF, Yahia AA. Population status, habitat preferences and predictive current and future distributions of three endangered Silene species under changing climate. FRONTIERS IN PLANT SCIENCE 2024; 15:1336911. [PMID: 38966141 PMCID: PMC11222647 DOI: 10.3389/fpls.2024.1336911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 06/05/2024] [Indexed: 07/06/2024]
Abstract
One of the most crucial steps in the practical conservation of endangered endemic mountain plants is to address their population size status and habitat requirements concurrently with understanding their response to future global warming. Three endangered Silene species-Silene leucophylla Boiss., S. schimperiana Boiss., and S. oreosinaica Chowdhuri-in Egypt were the focus of the current study. These species were examined for population status change, habitat quality variables (topography, soil features, and threats), and predictive current and future distributions. To find population size changes, recent field surveys and historical records were compared. Using Random Forest (RF) and Canonical Correspondence Analysis (CCA), habitat preferences were assessed. To forecast present-day distribution and climate change response, an ensemble model was used. The results reported a continuous decline in the population size of the three species. Both RF and CCA addressed that elevation, soil texture (silt, sand, and clay fractions), soil moisture, habitat-type, chlorides, electric conductivity, and slope were among the important variables associated with habitat quality. The central northern sector of the Saint Catherine area is the hotspot location for the predictive current distribution of three species with suitable areas of 291.40, 293.10, and 58.29 km2 for S. leucophylla, S. schimperiana, and S. oreosinaica, respectively. Precipitation-related variables and elevation were the key predictors for the current distribution of three Silene species. In response to climate change scenarios, the three Silene species exhibited a gradual contraction in the predictive suitable areas with upward shifts by 2050 and 2070. The protection of these species and reintroduction to the predicted current and future climatically suitable areas are urgent priorities. Ex-situ conservation and raised surveillance, as well as fenced enclosures may catapult as promising and effective approaches to conserving such threatened species.
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Affiliation(s)
- Mohamed Abdelaal
- Department of Botany, Faculty of Science, Mansoura University, Mansoura, Egypt
| | - Arwa Abdulkreem AL-Huqail
- Department of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
| | | | | | - Sami Asir Al-Robai
- Department of Biology, Faculty of Science, Al-Baha University, Al-Baha, Saudi Arabia
| | - Amany H. A. Abeed
- Department of Botany and Microbiology, Faculty of Science, Assiut University, Assiut, Egypt
| | - Mohammed A. Dakhil
- Botany and Microbiology Department, Faculty of Science, Helwan University, Cairo, Egypt
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an, China
| | - Reham F. El-Barougy
- Botany and Microbiology Department, Faculty of Science, Damietta University, Damietta, Egypt
| | - Aya A. Yahia
- Department of Botany, Faculty of Science, Mansoura University, Mansoura, Egypt
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5
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Liang J, Wang W, Cai Q, Li X, Zhu Z, Zhai Y, Li X, Gao X, Yi Y. Prioritizing conservation efforts based on future habitat availability and accessibility under climate change. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14204. [PMID: 37855159 DOI: 10.1111/cobi.14204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 09/17/2023] [Accepted: 10/09/2023] [Indexed: 10/20/2023]
Abstract
The potential for species to shift their ranges to avoid extinction is contingent on the future availability and accessibility of habitats with analogous climates. To develop conservation strategies, many previous researchers used a single method that considered individual factors; a few combined 2 factors. Primarily, these studies focused on identifying climate refugia or climatically connected and spatially fixed areas, ignoring the range shifting process of animals. We quantified future habitat availability (based on species occurrence, climate data, land cover, and elevation) and accessibility (based on climate velocity) under climate change (4 scenarios) of migratory birds across the Yangtze River basin (YRB). Then, we assessed species' range-shift potential and identified conservation priority areas for migratory birds in the 2050s with a network analysis. Our results suggested that medium (i.e., 5-10 km/year) and high (i.e., ≥ 10 km/year) climate velocity would threaten 18.65% and 8.37% of stable habitat, respectively. Even with low (i.e., 0-5 km/year) climate velocity, 50.15% of climate-velocity-identified destinations were less available than their source habitats. Based on our integration of habitat availability and accessibility, we identified a few areas of critical importance for conservation, mainly in Sichuan and the middle to lower reaches of the YRB. Overall, we identified the differences between habitat availability and accessibility in capturing biological responses to climate change. More importantly, we accounted for the dynamic process of species' range shifts, which must be considered to identify conservation priority areas. Our method informs forecasting of climate-driven distribution shifts and conservation priorities.
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Affiliation(s)
- Jie Liang
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Wanting Wang
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Qing Cai
- Hunan Research Academy of Environmental Sciences, Changsha, P.R. China
| | - Xin Li
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Ziqian Zhu
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Yeqing Zhai
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Xiaodong Li
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Xiang Gao
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
| | - Yuru Yi
- College of Environmental Science and Engineering, Hunan University, Changsha, P.R. China
- Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha, P.R. China
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6
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Wessely J, Essl F, Fiedler K, Gattringer A, Hülber B, Ignateva O, Moser D, Rammer W, Dullinger S, Seidl R. A climate-induced tree species bottleneck for forest management in Europe. Nat Ecol Evol 2024; 8:1109-1117. [PMID: 38684739 DOI: 10.1038/s41559-024-02406-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 03/24/2024] [Indexed: 05/02/2024]
Abstract
Large pulses of tree mortality have ushered in a major reorganization of Europe's forest ecosystems. To initiate a robust next generation of trees, the species that are planted today need to be climatically suitable throughout the entire twenty-first century. Here we developed species distribution models for 69 European tree species based on occurrence data from 238,080 plot locations to investigate the option space for current forest management in Europe. We show that the average pool of tree species continuously suitable throughout the century is smaller than that under current and end-of-century climate conditions, creating a tree species bottleneck for current management. If the need for continuous climate suitability throughout the lifespan of a tree planted today is considered, climate change shrinks the tree species pool available to management by between 33% and 49% of its current values (40% and 54% of potential end-of-century values), under moderate (Representative Concentration Pathway 2.6) and severe (Representative Concentration Pathway 8.5) climate change, respectively. This bottleneck could have strong negative impacts on timber production, carbon storage and biodiversity conservation, as only 3.18, 3.53 and 2.56 species of high potential for providing these functions remain suitable throughout the century on average per square kilometre in Europe. Our results indicate that the option space for silviculture is narrowing substantially because of climate change and that an important adaptation strategy in forestry-creating mixed forests-might be curtailed by widespread losses of climatically suitable tree species.
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Affiliation(s)
- Johannes Wessely
- Division of Biodiversity Dynamics and Conservation, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria.
| | - Franz Essl
- Division of BioInvasions, Global Change and Macroecology, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
- Centre for Invasion Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Konrad Fiedler
- Division of Tropical Ecology and Animal Biodiversity, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Andreas Gattringer
- Division of Biodiversity Dynamics and Conservation, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Bernhard Hülber
- Division of Biodiversity Dynamics and Conservation, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Olesia Ignateva
- Research Division Cartography, Department of Geodesy and Geoinformation, Vienna University of Technology, Vienna, Austria
| | - Dietmar Moser
- Division of Biodiversity Dynamics and Conservation, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Werner Rammer
- Ecosystem Dynamics and Forest Management Group, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Stefan Dullinger
- Division of Biodiversity Dynamics and Conservation, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Rupert Seidl
- Ecosystem Dynamics and Forest Management Group, School of Life Sciences, Technical University of Munich, Freising, Germany
- Berchtesgaden National Park, Berchtesgaden, Germany
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7
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Fastovich D, Radeloff VC, Zuckerberg B, Williams JW. Legacies of millennial-scale climate oscillations in contemporary biodiversity in eastern North America. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230012. [PMID: 38583476 PMCID: PMC10999273 DOI: 10.1098/rstb.2023.0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 01/22/2024] [Indexed: 04/09/2024] Open
Abstract
The Atlantic meridional overturning circulation (AMOC) has caused significant climate changes over the past 90 000 years. Prior work has hypothesized that these millennial-scale climate variations effected past and contemporary biodiversity, but the effects are understudied. Moreover, few biogeographic models have accounted for uncertainties in palaeoclimatic simulations of millennial-scale variability. We examine whether refuges from millennial-scale climate oscillations have left detectable legacies in the patterns of contemporary species richness in eastern North America. We analyse 13 palaeoclimate estimates from climate simulations and proxy-based reconstructions as predictors for the contemporary richness of amphibians, passerine birds, mammals, reptiles and trees. Results suggest that past climate changes owing to AMOC variations have left weak but detectable imprints on the contemporary richness of mammals and trees. High temperature stability, precipitation increase, and an apparent climate fulcrum in the southeastern United States across millennial-scale climate oscillations aligns with high biodiversity in the region. These findings support the hypothesis that the southeastern United States may have acted as a biodiversity refuge. However, for some taxa, the strength and direction of palaeoclimate-richness relationships varies among different palaeoclimate estimates, pointing to the importance of palaeoclimatic ensembles and the need for caution when basing biogeographic interpretations on individual palaeoclimate simulations. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.
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Affiliation(s)
- David Fastovich
- Department of Geography, University of Wisconsin–Madison, 550 North Park Street, Madison, WI 53706, USA
- Department of Earth and Environmental Sciences, Syracuse University, 141 Crouse Drive, Syracuse, NY 13210, USA
| | - Volker C. Radeloff
- SILVIS Laboratory, Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, 1630 Linden Drive, Madison, WI 53706, USA
| | - Benjamin Zuckerberg
- Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, 1630 Linden Drive, Madison, WI 53706, USA
| | - John W. Williams
- Department of Geography, University of Wisconsin–Madison, 550 North Park Street, Madison, WI 53706, USA
- Center for Climatic Research, University of Wisconsin–Madison, 550 North Park Street, Madison, WI 53706, USA
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8
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Allen BJ, Hill DJ, Burke AM, Clark M, Marchant R, Stringer LC, Williams DR, Lyon C. Projected future climatic forcing on the global distribution of vegetation types. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230011. [PMID: 38583474 PMCID: PMC10999268 DOI: 10.1098/rstb.2023.0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 03/07/2024] [Indexed: 04/09/2024] Open
Abstract
Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.
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Affiliation(s)
- Bethany J. Allen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- Computational Evolution Group, Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Daniel J. Hill
- School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
| | - Ariane M. Burke
- Département d'Anthropologie, Université de Montréal, Montréal, Quebec, H3C 3J7, Canada
| | - Michael Clark
- Smith School of Enterprise and the Environment, University of Oxford, Oxford, OX1 3QY, UK
- Oxford Martin School, University of Oxford, Oxford, OX1 3BD, UK
- Department of Biology, University of Oxford, Oxford, OX1 3RB, UK
| | - Robert Marchant
- Department of Environment and Geography, University of York, York, YO10 5NG, UK
| | - Lindsay C. Stringer
- Department of Environment and Geography, University of York, York, YO10 5NG, UK
- Leverhulme Centre for Anthropocene Biodiversity, University of York, York, YO10 5DD, UK
- York Environmental Sustainability Institute, University of York, York, YO10 5DD, UK
| | - David R. Williams
- School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
| | - Christopher Lyon
- Department of Environment and Geography, University of York, York, YO10 5NG, UK
- Leverhulme Centre for Anthropocene Biodiversity, University of York, York, YO10 5DD, UK
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9
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Weiskopf SR, Isbell F, Arce-Plata MI, Di Marco M, Harfoot M, Johnson J, Lerman SB, Miller BW, Morelli TL, Mori AS, Weng E, Ferrier S. Biodiversity loss reduces global terrestrial carbon storage. Nat Commun 2024; 15:4354. [PMID: 38778013 PMCID: PMC11111688 DOI: 10.1038/s41467-024-47872-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 04/11/2024] [Indexed: 05/25/2024] Open
Abstract
Natural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem's carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between 7.44-103.14 PgC (global sustainability scenario) and 10.87-145.95 PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals.
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Affiliation(s)
- Sarah R Weiskopf
- U.S. Geological Survey National Climate Adaptation Science Center, Reston, VA, USA.
- Department of Environmental Conservation, University of Massachusetts, Amherst, MA, USA.
| | - Forest Isbell
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN, USA
| | | | - Moreno Di Marco
- Department of Biology and Biotechnologies, Sapienza University of Rome, Rome, Italy
| | - Mike Harfoot
- Vizzuality, 123 Calle de Fuencarral, 28010, Madrid, Spain
| | - Justin Johnson
- Department of Applied Economics, University of Minnesota, 1994 Buford Ave, Saint Paul, MN, 55105, USA
| | | | - Brian W Miller
- U.S. Geological Survey North Central Climate Adaptation Science Center, Boulder, CO, USA
| | - Toni Lyn Morelli
- Department of Environmental Conservation, University of Massachusetts, Amherst, MA, USA
- U.S. Geological Survey Northeast Climate Adaptation Science Center, Amherst, MA, USA
| | - Akira S Mori
- Research Center for Advanced Science and Technology, the University of Tokyo, 4-6-1 Komaba, Meguro, Tokyo, 153-8904, Japan
| | - Ensheng Weng
- Columbia University/NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY, 10025, USA
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10
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Zhang HT, Yang TT, Wang WT. A novel hybrid model for species distribution prediction using neural networks and Grey Wolf Optimizer algorithm. Sci Rep 2024; 14:11505. [PMID: 38769379 PMCID: PMC11106298 DOI: 10.1038/s41598-024-62285-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/15/2024] [Indexed: 05/22/2024] Open
Abstract
Neural networks are frequently employed to model species distribution through backpropagation methods, known as backpropagation neural networks (BPNN). However, the complex structure of BPNN introduces parameter settings challenges, such as the determination of connection weights, which can affect the accuracy of model simulation. In this paper, we integrated the Grey Wolf Optimizer (GWO) algorithm, renowned for its excellent global search capacity and rapid convergence, to enhance the performance of BPNN. Then we obtained a novel hybrid algorithm, the Grey Wolf Optimizer algorithm optimized backpropagation neural networks algorithm (GNNA), designed for predicting species' potential distribution. We also compared the GNNA with four prevalent species distribution models (SDMs), namely the generalized boosting model (GBM), generalized linear model (GLM), maximum entropy (MaxEnt), and random forest (RF). These models were evaluated using three evaluation metrics: the area under the receiver operating characteristic curve, Cohen's kappa, and the true skill statistic, across 23 varied species. Additionally, we examined the predictive accuracy concerning spatial distribution. The results showed that the predictive performance of GNNA was significantly improved compared to BPNN, was significantly better than that of GLM and GBM, and was even comparable to that of MaxEnt and RF in predicting species distributions with small sample sizes. Furthermore, the GNNA demonstrates exceptional powers in forecasting the potential non-native distribution of invasive plant species.
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Affiliation(s)
- Hao-Tian Zhang
- School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, 730030, People's Republic of China
| | - Ting-Ting Yang
- School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, 730030, People's Republic of China
| | - Wen-Ting Wang
- School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, 730030, People's Republic of China.
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11
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Souther SK, Sandor ME, Sample M, Gabrielson S, Aslan CE. Bee and butterfly records indicate diversity losses in western and southern North America, but extensive knowledge gaps remain. PLoS One 2024; 19:e0289742. [PMID: 38748698 PMCID: PMC11095745 DOI: 10.1371/journal.pone.0289742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 03/07/2024] [Indexed: 05/19/2024] Open
Abstract
Pollinator losses threaten ecosystems and food security, diminishing gene flow and reproductive output for ecological communities and impacting ecosystem services broadly. For four focal families of bees and butterflies, we constructed over 1400 ensemble species distribution models over two time periods for North America. Models indicated disproportionally increased richness in eastern North America over time, with decreases in richness over time in the western US and southern Mexico. To further pinpoint geographic areas of vulnerability, we mapped records of potential pollinator species of conservation concern and found high concentrations of detections in the Great Lakes region, US East Coast, and southern Canada. Finally, we estimated asymptotic diversity indices for genera known to include species that visit flowers and may carry pollen for ecoregions across two time periods. Patterns of generic diversity through time mirrored those of species-level analyses, again indicating a decline in pollinators in the western U.S. Increases in generic diversity were observed in cooler and wetter ecoregions. Overall, changes in pollinator diversity appear to reflect changes in climate, though other factors such as land use change may also explain regional shifts. While statistical methods were employed to account for unequal sampling effort across regions and time, improved monitoring efforts with rigorous sampling designs would provide a deeper understanding of pollinator communities and their responses to ongoing environmental change.
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Affiliation(s)
- Sara K. Souther
- Center for Adaptable Western Landscapes, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Manette E. Sandor
- Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY, United States of America
- Center for Conservation and Biodiversity, American Museum of Natural History, New York, NY, United States of America
| | - Martha Sample
- Center for Adaptable Western Landscapes, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Sara Gabrielson
- Department of Biology, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Clare E. Aslan
- Center for Adaptable Western Landscapes, Northern Arizona University, Flagstaff, AZ, United States of America
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12
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Blais BR, Koprowski JL. Modeling a hot, dry future: Substantial range reductions in suitable environment projected under climate change for a semiarid riparian predator guild. PLoS One 2024; 19:e0302981. [PMID: 38709740 PMCID: PMC11073737 DOI: 10.1371/journal.pone.0302981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 04/15/2024] [Indexed: 05/08/2024] Open
Abstract
An understanding of species-environmental relationships is invaluable for effective conservation and management under anthropogenic climate change, especially for biodiversity hotspots such as riparian habitats. Species distribution models (SDMs) assess present species-environmental relationships which can project potential suitable environments through space and time. An understanding of environmental factors associated with distributions can guide conservation management strategies under a changing climate. We generated 260 ensemble SDMs for five species of Thamnophis gartersnakes (n = 347)-an important riparian predator guild-in a semiarid and biogeographically diverse region under impact from climate change (Arizona, United States). We modeled present species-environmental relationships and projected changes to suitable environment under 12 future climate scenarios per species, including the most and least optimistic greenhouse gas emission pathways, through 2100. We found that Thamnophis likely advanced northward since the turn of the 20th century and overwinter temperature and seasonal precipitation best explained present distributions. Future ranges of suitable environment for Thamnophis are projected to decrease by ca. -37.1% on average. We found that species already threatened with extinction or those with warm trailing-edge populations likely face the greatest loss of suitable environment, including near or complete loss of suitable environment. Future climate scenarios suggest an upward advance of suitable environment around montane areas for some low to mid-elevation species, which may create pressures to ascend. The most suitable environmental areas projected here can be used to identify potential safe zones to prioritize conservation refuges, including applicable critical habitat designations. By bounding the climate pathway extremes to, we reduce SDM uncertainties and provide valuable information to help conservation practitioners mitigate climate-induced threats to species. Implementing informed conservation actions is paramount for sustaining biodiversity in important aridland riparian systems as the climate warms and dries.
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Affiliation(s)
- Brian R. Blais
- School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, United States of America
| | - John L. Koprowski
- School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, United States of America
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13
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Alencar JBR, Sampaio A, da Fonseca CRV. Ecological niche modeling of two Microtheca Stål, 1860 species (Coleoptera: Chrysomelidae: Chrysomelinae) in the Americas: insights from Brassicaceae occurrence. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2024; 68:891-898. [PMID: 38374294 DOI: 10.1007/s00484-024-02634-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/02/2024] [Accepted: 01/28/2024] [Indexed: 02/21/2024]
Abstract
Biological invasions pose significant threats to biodiversity, with invasive species spread often facilitated by human activities. Consequently, this research utilized ecological niche modeling (ENM) to overcome this limitation and map the potential suitability of Microtheca ochroloma Stål, 1860 and Microtheca semilaevis Stål, 1860, which have been evaluated as potential insect pests in the Americas, zones for four genera of Brassicaceae, which include globally cultivated species such as Sinapis L., Raphanus L., Eruca Mill., and Brassica L. We utilized multiple methods to forecast the ecological habitat of Microtheca Stål, 1860 species based on distribution data and various environmental indicators. Our models, exhibiting high-performance metrics (TSS ranging from 0.84 to 0.96), revealed extensive environmental suitability for these species across the Americas, including previously unreported regions. The predicted zones overlapped significantly with areas where Brassicaceae crops were grown. Contrary to some previous assertions, our findings suggest that while these Microtheca species are recognized pests on these crops, their consistent widespread damage may be overstated. Nevertheless, their invasive potential could have broad ecological impacts, including biodiversity loss. Our research emphasizes the need for focused sampling in potential distribution zones and underlines the value of integrating ENM in predicting and managing invasive species spread.
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Affiliation(s)
- Janderson Batista Rodrigues Alencar
- Programa de Pós-Graduação Em Ciências Biológicas (Entomologia), Instituto Nacional de Pesquisas da Amazônia, Av. André Araújo, 2936, Petrópolis, Manaus, AM, 69067-375, Brazil.
| | - Aline Sampaio
- Programa de Pós-Graduação Em Ciências Biológicas (Entomologia), Instituto Nacional de Pesquisas da Amazônia, Av. André Araújo, 2936, Petrópolis, Manaus, AM, 69067-375, Brazil
| | - Claudio Ruy Vasconcelos da Fonseca
- Programa de Pós-Graduação Em Ciências Biológicas (Entomologia), Instituto Nacional de Pesquisas da Amazônia, Av. André Araújo, 2936, Petrópolis, Manaus, AM, 69067-375, Brazil
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14
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Zhang Z, Zhou J, García Molinos J, Mammola S, Bede-Fazekas Á, Feng X, Kitazawa D, Assis J, Qiu T, Lin Q. Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area. MARINE LIFE SCIENCE & TECHNOLOGY 2024; 6:349-362. [PMID: 38827135 PMCID: PMC11136901 DOI: 10.1007/s42995-024-00226-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 02/20/2024] [Indexed: 06/04/2024]
Abstract
Correlative species distribution models (SDMs) are important tools to estimate species' geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species' physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models' sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available. Supplementary Information The online version contains supplementary material available at 10.1007/s42995-024-00226-0.
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Affiliation(s)
- Zhixin Zhang
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301 China
- Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301 China
- Marine Biodiversity and Ecological Evolution Research Center, South China Sea Institute of Oceanology, Guangzhou, 510301 China
- Global Ocean and Climate Research Center, South China Sea Institute of Oceanology, Guangzhou, 510301 China
| | - Jinxin Zhou
- Institute of Industrial Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8574 Japan
| | | | - Stefano Mammola
- Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
- Molecular Ecology Group (MEG), Water Research Institute (IRSA), National Research Council of Italy (CNR), 28922 Verbania Pallanza, Italy
- National Biodiversity Future Center (NBFC), Palermo, Italy
| | - Ákos Bede-Fazekas
- Institute of Ecology and Botany, HUN-REN Centre for Ecological Research, Vácrátót, Hungary
- Department of Environmental and Landscape Geography, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Xiao Feng
- Department of Biology, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Daisuke Kitazawa
- Institute of Industrial Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8574 Japan
| | - Jorge Assis
- Centre of Marine Sciences, University of Algarve, Campus de Gambelas, Faro, Portugal
| | - Tianlong Qiu
- CAS Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071 China
| | - Qiang Lin
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301 China
- Marine Biodiversity and Ecological Evolution Research Center, South China Sea Institute of Oceanology, Guangzhou, 510301 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
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15
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Pereira HM, Martins IS, Rosa IMD, Kim H, Leadley P, Popp A, van Vuuren DP, Hurtt G, Quoss L, Arneth A, Baisero D, Bakkenes M, Chaplin-Kramer R, Chini L, Di Marco M, Ferrier S, Fujimori S, Guerra CA, Harfoot M, Harwood TD, Hasegawa T, Haverd V, Havlík P, Hellweg S, Hilbers JP, Hill SLL, Hirata A, Hoskins AJ, Humpenöder F, Janse JH, Jetz W, Johnson JA, Krause A, Leclère D, Matsui T, Meijer JR, Merow C, Obersteiner M, Ohashi H, De Palma A, Poulter B, Purvis A, Quesada B, Rondinini C, Schipper AM, Settele J, Sharp R, Stehfest E, Strassburg BBN, Takahashi K, Talluto MV, Thuiller W, Titeux N, Visconti P, Ware C, Wolf F, Alkemade R. Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050. Science 2024; 384:458-465. [PMID: 38662818 DOI: 10.1126/science.adn3441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/28/2024] [Indexed: 05/04/2024]
Abstract
Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.
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Affiliation(s)
- Henrique M Pereira
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, Germany
- BIOPOLIS, CIBIO/InBIO, Universidade do Porto, Vairão 4485-661, Portugal
| | - Inês S Martins
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, Germany
- Leverhulme Centre for Anthropocene Biodiversity, Department of Biology, University of York, York, YO10 5DD, UK
| | - Isabel M D Rosa
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, Germany
- Kenvue Portugal, JNTL Consumer Health Ltd, Porto Salvo 2740-262, Portugal
| | - HyeJin Kim
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, Germany
- UK Centre for Ecology and Hydrology, Lancaster LA1 4AP, UK
| | - Paul Leadley
- Ecologie Systématique Evolution, Université Paris-Saclay, CNRS, AgroParisTech, Gif-sur-Yvette 91190, France
| | - Alexander Popp
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam 14473, Germany
- Faculty of Organic Agricultural Sciences, University of Kassel, Witzenhausen D-37213, Germany
| | - Detlef P van Vuuren
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht 3584 CB, Netherlands
| | - George Hurtt
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Luise Quoss
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, Germany
| | - Almut Arneth
- Karlsruhe Institute of Technology, Department of Meteorology and Climate/Atmospheric Environmental Research, Garmisch-Partenkirchen 82467, Germany
| | - Daniele Baisero
- Department of Biology and Biotechnologies, Sapienza Università di Roma, Rome I-00185, Italy
- KBA Secretariat, BirdLife International, Cambridge CB2 3QZ, UK
| | - Michel Bakkenes
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
| | - Rebecca Chaplin-Kramer
- Global Science, World Wildlife Fund, San Francisco, CA 94105, USA
- Institute on the Environment, University of Minnesota, Saint Paul, MN 55108, USA
| | - Louise Chini
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Moreno Di Marco
- Department of Biology and Biotechnologies, Sapienza Università di Roma, Rome I-00185, Italy
| | | | - Shinichiro Fujimori
- Department of Environmental Engineering, Katsura Campus, Kyoto University, Kyoto-city 615-8540, Japan
- National Institute for Environmental Studies, Ibaraki 305-8506, Japan
| | - Carlos A Guerra
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Universidade de Coimbra, Coimbra 3004-530, Portugal
| | - Michael Harfoot
- United Nations Environment Programme, World Conservation Monitoring Centre, Cambridge CB3 0DL, UK
| | - Thomas D Harwood
- CSIRO Environment, Canberra, ACT 2601, Australia
- Environmental Change Institute, Oxford OX1 3QY, UK
| | - Tomoko Hasegawa
- National Institute for Environmental Studies, Ibaraki 305-8506, Japan
- Ritsumeikan University, Shiga 525-8577, Japan
| | | | - Petr Havlík
- International Institute for Applied Systems Analysis, Laxenburg 2361, Austria
| | - Stefanie Hellweg
- Institute of Environmental Engineering, ETH Zurich, Zurich 8093, Switzerland
| | - Jelle P Hilbers
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
- Radboud University, Radboud Institute for Biological and Environmental Sciences, Nijmegen 6500 GL, Netherlands
| | - Samantha L L Hill
- United Nations Environment Programme, World Conservation Monitoring Centre, Cambridge CB3 0DL, UK
- Department of Life Sciences, Natural History Museum, London SW7 5BD, UK
| | - Akiko Hirata
- Forestry and Forest Products Research Institute, Forest Research and Management Organization, Ibaraki 305-8687, Japan
- Faculty of Life and Environmental Sciences, University of Tsukuba, Ibaraki 305-8572, Japan
| | - Andrew J Hoskins
- CSIRO Environment, Canberra, ACT 2601, Australia
- James Cook University, Townsville, 4811 Queensland, Australia
| | - Florian Humpenöder
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam 14473, Germany
| | - Jan H Janse
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
- Netherlands Institute of Ecology NIOO-KNAW, Wageningen 6700AB, Netherlands
| | - Walter Jetz
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06511, USA
- Center for Biodiversity and Global Change, Yale University, New Haven, CT 06511, USA
| | - Justin A Johnson
- Department of Applied Economics, University of Minnesota, Saint Paul, MN 55108, USA
| | - Andreas Krause
- Karlsruhe Institute of Technology, Department of Meteorology and Climate/Atmospheric Environmental Research, Garmisch-Partenkirchen 82467, Germany
- Technical University of Munich, TUM School of Life Sciences, Freising 85354, Germany
| | - David Leclère
- International Institute for Applied Systems Analysis, Laxenburg 2361, Austria
| | - Tetsuya Matsui
- Forestry and Forest Products Research Institute, Forest Research and Management Organization, Ibaraki 305-8687, Japan
- Faculty of Life and Environmental Sciences, University of Tsukuba, Ibaraki 305-8572, Japan
| | - Johan R Meijer
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
| | - Cory Merow
- Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT 06269, USA
| | - Michael Obersteiner
- Environmental Change Institute, Oxford OX1 3QY, UK
- International Institute for Applied Systems Analysis, Laxenburg 2361, Austria
| | - Haruka Ohashi
- Forestry and Forest Products Research Institute, Forest Research and Management Organization, Ibaraki 305-8687, Japan
| | - Adriana De Palma
- Department of Life Sciences, Natural History Museum, London SW7 5BD, UK
| | - Benjamin Poulter
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
| | - Andy Purvis
- Department of Life Sciences, Natural History Museum, London SW7 5BD, UK
- Department of Life Sciences, Imperial College London, Ascot SL5 7PY, UK
| | - Benjamin Quesada
- Karlsruhe Institute of Technology, Department of Meteorology and Climate/Atmospheric Environmental Research, Garmisch-Partenkirchen 82467, Germany
- "Interactions Climate-Ecosystems (ICE)" Research Group, Earth System Science Program, Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Bogotá DC 63B-48, Colombia
| | - Carlo Rondinini
- Department of Biology and Biotechnologies, Sapienza Università di Roma, Rome I-00185, Italy
| | - Aafke M Schipper
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
- Radboud University, Radboud Institute for Biological and Environmental Sciences, Nijmegen 6500 GL, Netherlands
| | - Josef Settele
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Helmholtz Centre for Environmental Research - UFZ, Department of Conservation Biology and Social-Ecological Systems, Halle 06210, Germany
- Institute of Biological Sciences, University of the Philippines, Laguna 4031, Philippines
| | - Richard Sharp
- Global Science, World Wildlife Fund, San Francisco, CA 94105, USA
| | - Elke Stehfest
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
| | - Bernardo B N Strassburg
- re.green, Rio de Janeiro 22470-060, Brazil
- Rio Conservation and Sustainability Science Centre, Department of Geography and the Environment, Pontifícia Universidade Católica, Rio de Janeiro 22451-900, Brazil
| | - Kiyoshi Takahashi
- National Institute for Environmental Studies, Ibaraki 305-8506, Japan
| | - Matthew V Talluto
- Department of Ecology, University of Innsbruck, Innsbruck 6020, Austria
| | - Wilfried Thuiller
- Université Grenoble Alpes, CNRS, Université Savoie Mont Blanc, LECA, Laboratoire d'Écologie Alpine, Grenoble F-38000, France
| | - Nicolas Titeux
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Helmholtz Centre for Environmental Research - UFZ, Department of Conservation Biology and Social-Ecological Systems, Halle 06210, Germany
- Luxembourg Institute of Science and Technology, Environmental Research and Innovation Department, Observatory for Climate, Environment and Biodiversity, Belvaux 4422, Luxembourg
| | - Piero Visconti
- International Institute for Applied Systems Analysis, Laxenburg 2361, Austria
- Luxembourg Institute of Science and Technology, Environmental Research and Innovation Department, Observatory for Climate, Environment and Biodiversity, Belvaux 4422, Luxembourg
- Centre for Biodiversity and Environment Research, University College London, London C1E6BT, UK
| | | | - Florian Wolf
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, Germany
| | - Rob Alkemade
- PBL Netherlands Environmental Assessment Agency, Hague 2500 GH, Netherlands
- Earth System and Global Change Group, Wageningen University, Wageningen 6708PB Netherlands
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16
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Banda LB, Dejene SW, Mzumara TI, McCarthy C, Pangapanga‐Phiri I. An ensemble model predicts an upward range shift of the endemic and endangered Yellow-throated Apalis ( Apalis flavigularis) under future climate change in Malawi. Ecol Evol 2024; 14:e11283. [PMID: 38623518 PMCID: PMC11017464 DOI: 10.1002/ece3.11283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 03/09/2024] [Accepted: 04/03/2024] [Indexed: 04/17/2024] Open
Abstract
Climate change poses a significant threat to endemic and endangered montane bird species with limited elevation and temperature ranges. Understanding their responses to changes in climate is essential for informing conservation actions. This study focused on the montane dwelling Yellow-throated Apalis (Apalis flavigularis) in Malawi, aiming to identify key factors affecting its distribution and predicting its potential distribution under different climate change scenarios. Using an ensemble species distribution modeling approach, we found that the mean temperature of the driest quarter (Bio9), mean temperature of the wettest quarter (Bio8), and precipitation seasonality (Bio15) were the most important variables that influenced the distribution of this species. Across future climate scenarios, the species' geographic range declined where range losses varied from 57.74% (2050 RCP 6.0) to 82.88% (2070 RCP 6.0). We estimate its current range size to be 549 km2 which is lower than some previous estimates of its spatial distribution. Moreover, our projections indicate that under future climate scenarios, the species will shift to higher elevations with a large proportion of suitable areas located outside forests, posing challenges for adaptation. Our results suggest that the species may be under greater threat than previously thought; hence, urgent conservation actions are required. We recommend reinforcing the protection of areas predicted to remain suitable under future climate scenarios and the development of a species conservation action plan.
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Affiliation(s)
- Lumbani Benedicto Banda
- Department of Environment and Natural Resources ManagementLilongwe University of Agriculture and Natural Resources (LUANAR)LilongweMalawi
- Africa Centre of Excellence for Climate Smart Agriculture and Biodiversity ConservationHaramaya UniversityDire DawaEthiopia
| | - Sintayehu W. Dejene
- Africa Centre of Excellence for Climate Smart Agriculture and Biodiversity ConservationHaramaya UniversityDire DawaEthiopia
- College of Agriculture and Environmental SciencesHaramaya UniversityDire DawaEthiopia
| | - Tiwonge I. Mzumara
- Department of Biological SciencesMalawi University of Science and Technology (MUST)LimbeMalawi
| | - Christopher McCarthy
- Zanvyl Krieger School of Arts and SciencesJohns Hopkins UniversityBaltimoreMassachusettsUSA
| | - Innocent Pangapanga‐Phiri
- Department of Environment and Natural Resources ManagementLilongwe University of Agriculture and Natural Resources (LUANAR)LilongweMalawi
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17
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Simmonds EG, Adjei KP, Cretois B, Dickel L, González-Gil R, Laverick JH, Mandeville CP, Mandeville EG, Ovaskainen O, Sicacha-Parada J, Skarstein ES, O'Hara B. Recommendations for quantitative uncertainty consideration in ecology and evolution. Trends Ecol Evol 2024; 39:328-337. [PMID: 38030538 DOI: 10.1016/j.tree.2023.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 09/13/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023]
Abstract
Ecological and evolutionary studies are currently failing to achieve complete and consistent reporting of model-related uncertainty. We identify three key barriers - a focus on parameter-related uncertainty, obscure uncertainty metrics, and limited recognition of uncertainty propagation - which have led to gaps in uncertainty consideration. However, these gaps can be closed. We propose that uncertainty reporting in ecology and evolution can be improved through wider application of existing statistical solutions and by adopting good practice from other scientific fields. Our recommendations include greater consideration of input data and model structure uncertainties, field-specific uncertainty standards for methods and reporting, and increased uncertainty propagation through the use of hierarchical models.
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Affiliation(s)
- Emily G Simmonds
- The Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim 7491, Norway; Institute for Biology, Norwegian University of Science and Technology, Trondheim 7491, Norway; Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK.
| | - Kwaku P Adjei
- The Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim 7491, Norway; Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim 7034, Norway
| | - Benjamin Cretois
- Norwegian Institute for Nature Research, Torgarden, Trondheim, Trøndelag 7485, Norway
| | - Lisa Dickel
- The Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim 7491, Norway; Institute for Biology, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Ricardo González-Gil
- Observatorio Marino de Asturias (OMA), Departamento de Biología de Organismos y Sistemas, University of Oviedo, 33071 Oviedo, Spain; GOAL, Colonia Castaño Sur, Casa 1901, Calle Paseo Virgilio Zelaya Rubí, Tegucigalpa, Honduras, CA, USA
| | - Jack H Laverick
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, UK
| | - Caitlin P Mandeville
- The Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim 7491, Norway; Department of Natural History, Norwegian University of Science and Technology, Trondheim, Trøndelag 7491, Norway
| | | | - Otso Ovaskainen
- The Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim 7491, Norway; Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki 00014, Finland; Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä 40014, Finland
| | - Jorge Sicacha-Parada
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim 7034, Norway
| | - Emma S Skarstein
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim 7034, Norway
| | - Bob O'Hara
- The Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim 7491, Norway; Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim 7034, Norway
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18
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Kass JM, Fukaya K, Thuiller W, Mori AS. Biodiversity modeling advances will improve predictions of nature's contributions to people. Trends Ecol Evol 2024; 39:338-348. [PMID: 37968219 DOI: 10.1016/j.tree.2023.10.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 10/17/2023] [Accepted: 10/17/2023] [Indexed: 11/17/2023]
Abstract
Accurate predictions of ecosystem functions and nature's contributions to people (NCP) are needed to prioritize environmental protection and restoration in the Anthropocene. However, our ability to predict NCP is undermined by approaches that rely on biophysical variables and ignore those describing biodiversity, which have strong links to NCP. To foster predictive mapping of NCP, we should harness the latest methods in biodiversity modeling. This field advances rapidly, and new techniques with promising applications for predicting NCP are still underutilized. Here, we argue that employing recent advances in biodiversity modeling can enhance the accuracy and scope of NCP maps and predictions. This enhancement will contribute significantly to the achievement of global objectives to preserve NCP, for both the present and an unpredictable future.
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Affiliation(s)
- Jamie M Kass
- Macroecology Laboratory, Graduate School of Life Sciences, Tohoku University, Sendai, Miyagi, Japan; Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa, Japan.
| | - Keiichi Fukaya
- Biodiversity Division, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan
| | - Wilfried Thuiller
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, F-38000 Grenoble, France
| | - Akira S Mori
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
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19
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Palei HS, Jangid AK, Hanumant DD, Palei NC, Mishra AK. On the elephant trails: habitat suitability and connectivity for Asian elephants in eastern Indian landscape. PeerJ 2024; 12:e16746. [PMID: 38562998 PMCID: PMC10984178 DOI: 10.7717/peerj.16746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 12/11/2023] [Indexed: 04/04/2024] Open
Abstract
Identifying suitable habitats and conserving corridors are crucial to the long-term conservation of large and conflict-prone animals. Being a flagship species, survival of Asian elephants is threatened by human-induced mortality and habitat modification. We aimed to assess the habitat suitability and connectivity of the Asian elephant Elephas maximus Linnaeus, 1758 habitat in the state of Odisha in eastern India. We followed the ensemble of spatial prediction models using species presence data and five environmental variables. We used least-cost path and circuit theory approaches to identify the spatial connectivity between core habitats for Asian elephants. The results revealed that normalized difference vegetation index (NDVI; variable importance 42%) and terrain ruggedness (19%) are the most influential variables for predicting habitat suitability of species within the study area. Our habitat suitability map estimated 14.6% of Odisha's geographical area (c. 22,442 km2) as highly suitable and 13.3% (c. 20,464 km2) as moderate highly suitable. We identified 58 potential linkages to maintain the habitat connectivity across study area. Furthermore, we identified pinch points, bottlenecks, and high centrality links between core habitats. Our study offers management implications for long-term landscape conservation for Asian elephants in Odisha and highlights priority zones that can help maintain spatial links between elephant habitats.
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Affiliation(s)
| | - Ashish Kumar Jangid
- Bisalpur, Pali, Rajasthan, India
- Current affiliation: Wildlife Institute of India, Dehradun, Uttarakhand, India
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20
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Siddique MT, García Molinos J. Risk from future climate change to Pakistan's protected area network: A composite analysis for hotspot identification. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:169948. [PMID: 38211866 DOI: 10.1016/j.scitotenv.2024.169948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 11/27/2023] [Accepted: 01/03/2024] [Indexed: 01/13/2024]
Abstract
As climate change becomes a primary driver of global ecosystem deterioration and biodiversity loss, protected areas (PAs) are posed to play a crucial conservation role. At a global scale, 17 % of land is currently covered by PAs; a figure expected to reach 30 % by 2030 under the UN post-2020 global biodiversity framework. However, focusing only on the percent coverage of PAs without assessing their efficacy may not accomplish the intended conservation goals. Here, we present the first assessment of the risk from climate change to existing PAs and non-protected lands across Pakistan by combining data on the local exposure and vulnerability of 409 species of birds, mammals, reptiles and amphibians to multidimensional changes in climate by mid (2040-2060) and late (2061-2080) century under two climate emission scenarios (RCP4.5 and RCP8.5). We find that between 7 % (2050 RCP4.5) and 19 % (2080 RCP8.5) of the current network of PAs, mostly located in the eastern and southeastern parts of the country, are projected to be under future extreme risk (i.e., highly exposed areas containing highly vulnerable communities). Importantly, hotspots of risk within these PAs are projected to significantly expand over time and with increasing severity of the scenario. In contrast, PAs in the northern part of the country are projected to remain under moderate to low risk. Results are subject to variability across the country reflecting interesting differences in climate change exposure and species vulnerability between protected and non-protected lands. Importantly, significantly lower level of risks from future climate change are projected for PAs than non-protected lands across emission scenarios and periods suggesting potential candidate areas for the future expansion of the country's PA network. Our analysis provides novel insights that can help inform conservation decisions and management at a time when the country is investing in ambitious efforts to expand its network of protected areas.
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Affiliation(s)
- Muhammad Taimur Siddique
- Graduate School of Environmental Science, Hokkaido University, N10W5, Kita-ku, Sapporo, Hokkaido, Japan 060-0810
| | - Jorge García Molinos
- Arctic Research Center, Hokkaido University, N21W11, Kita-ku, Sapporo, Hokkaido, Japan 001-0021.
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21
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Brambilla M, Bazzi G, Ilahiane L. The effectiveness of species distribution models in predicting local abundance depends on model grain size. Ecology 2024; 105:e4224. [PMID: 38038251 DOI: 10.1002/ecy.4224] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 10/19/2023] [Accepted: 11/10/2023] [Indexed: 12/02/2023]
Abstract
The use of species distribution models (SDMs) to predict local abundance has been often proposed and contested. We tested whether SDMs at different spatiotemporal resolutions may predict the local density of 14 bird species of open/semi-open habitats. SDMs were built at 1 ha and 1 km, and with long-term versus a mix of current and long-term climatic variables. The estimated environmental suitability was used to predict local abundance obtained by means of 275 linear transects. We tested SDM ability to predict abundance for all sampled sites versus occurrence sites, using N-mixture models to account for imperfect detection. Then, we related the R2 of N-mixture models to SDM traits. Fine-grain SDMs appeared generally more robust than large-grain ones. Considering the all-transects models, for all species environmental suitability displayed a positive and highly significant effect at all the four combinations of spatial and temporal grains. When focusing only on occurrence transects, at the 1 km grain only one species showed a significant and positive effect. At the 1 ha grain, 62% of species models showed (over both climatic sets) a significant or nearly significant positive effect of environmental suitability on abundance. Grain was the only factor significantly affecting the model's explanatory power: 1 km grain led to lower amounts of variation explained by models. Our work re-opens the debate about predicting abundance using SDM-derived suitability, emphasizing the importance of grains and of spatiotemporal resolution more in general. The incorporation of local variables into SDMs at fine grains is key to predict local abundance. SDMs worked out at really fine grains, approaching the average size of territory or home range of target species, are needed to predict local abundance effectively. This may result from the fact that each single cell may represent a potential territory/home range, and hence a higher suitability over a given area means that more potential territories occur there.
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Affiliation(s)
- Mattia Brambilla
- Department of Environmental Science and Policy, Milan University, Milan, Italy
| | - Gaia Bazzi
- Area Avifauna Migratrice, Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), Ozzano dell'Emilia, Italy
| | - Luca Ilahiane
- Department of Environmental Science and Policy, Milan University, Milan, Italy
- Department of Sustainable Development and Ecological Transition, Eastern Piedmont University, Vercelli, Italy
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22
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Golivets M, Knapp S, Essl F, Lenzner B, Latombe G, Leung B, Kühn I. Future changes in key plant traits across Central Europe vary with biogeographical status, woodiness, and habitat type. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167954. [PMID: 37866591 DOI: 10.1016/j.scitotenv.2023.167954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/17/2023] [Accepted: 10/18/2023] [Indexed: 10/24/2023]
Abstract
Many plant traits covary with environmental gradients, reflecting shifts in adaptive strategies and thus informing about potential consequences of future environmental change for vegetation and ecosystem functioning. Yet, the evidence of trait-environment relationships (TERs) remains too heterogeneous for reliable predictions, partially due to insufficient consideration of trait syndromes specific to certain growth forms and habitats. Moreover, it is still unclear whether non-native and native plants' traits align similarly along environmental gradients, limiting our ability to assess the impacts of future plant invasions. Using a Bayesian multilevel modelling framework, we assess TERs for native and non-native woody and herbaceous plants across six broad habitat types in Central Europe at a resolution of c. 130 km2 and use them to project trait change under future environmental change scenarios until 2081-2100. We model TERs between three key plant traits (maximum height, Hmax; specific leaf area, SLA; seed mass, SM) and individual environmental factors (7 climate variables and % urban land cover) and estimate trait change summed across all environmental effects. We also quantify the change in the average trait difference between native and non-native plants. Our models depict multiple TERs, with important differences attributed to biogeographical status and woodiness within and across habitat types. The overall magnitude of trait change is projected to be greater for non-native than native taxa and to increase under more extreme scenarios. Native woody plant assemblages may generally experience a future increase across all three traits, whereas woody non-natives may decline in Hmax and increase in SLA and SM. Herbaceous Hmax is estimated to increase and SLA to decrease in most habitats. The obtained trait projections highlight conditions of competitive advantage of non-native plants over natives and vice versa and can serve as starting points for projecting future changes in ecosystem functions and services.
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Affiliation(s)
- Marina Golivets
- Department of Community Ecology, Helmholtz Centre for Environmental Research - UFZ, Halle, Germany.
| | - Sonja Knapp
- Department of Community Ecology, Helmholtz Centre for Environmental Research - UFZ, Halle, Germany; Ecosystem Science/Plant Ecology, Department of Ecology, Technische Universität Berlin, Berlin, Germany; German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Leipzig, Germany
| | - Franz Essl
- Division of Bioinvasions, Global Change & Macroecology, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Bernd Lenzner
- Division of Bioinvasions, Global Change & Macroecology, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Guillaume Latombe
- Institute of Ecology and Evolution, The University of Edinburgh, King's Buildings, Edinburgh, United Kingdom
| | - Brian Leung
- Department of Biology, McGill University, Montreal, Quebec, Canada; Bieler School of Environment, McGill University, Montreal, Quebec, Canada
| | - Ingolf Kühn
- Department of Community Ecology, Helmholtz Centre for Environmental Research - UFZ, Halle, Germany; German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Leipzig, Germany; Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Halle, Germany
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23
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Perret DL, Evans MEK, Sax DF. A species' response to spatial climatic variation does not predict its response to climate change. Proc Natl Acad Sci U S A 2024; 121:e2304404120. [PMID: 38109562 PMCID: PMC10769845 DOI: 10.1073/pnas.2304404120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 10/23/2023] [Indexed: 12/20/2023] Open
Abstract
The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here, we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.
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Affiliation(s)
- Daniel L. Perret
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI02912
| | | | - Dov F. Sax
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI02912
- Institute at Brown for Environment and Society, Brown University, Providence, RI02912
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24
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Puchałka R, Paź-Dyderska S, Dylewski Ł, Czortek P, Vítková M, Sádlo J, Klisz M, Koniakin S, Čarni A, Rašomavičius V, De Sanctis M, Dyderski MK. Forest herb species with similar European geographic ranges may respond differently to climate change. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167303. [PMID: 37742951 DOI: 10.1016/j.scitotenv.2023.167303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/04/2023] [Accepted: 09/21/2023] [Indexed: 09/26/2023]
Abstract
Many phenological studies have shown that spring geophytes are very sensitive to climate change, responding by shifting flowering and fruiting dates. However, there is a gap in knowledge about climatic drivers of their distributions and range shifts under climate change. Here we aimed to estimate climate niche shifts for four widely distributed and common geophytes of the nemoral zone of Europe (Anemone nemorosa, Anemone ranunculoides, Convallaria majalis and Maianthemum bifolium) and to assess the threat level under various climate change scenarios. Using MaxEnt species distribution models and future climate change scenarios we found that the precipitation of the warmest quarter was the most important factor shaping their ranges. All species studied will experience more loss in the 2061-2080 period than in 2041-2060, and under more pessimistic scenarios. M. bifolium will experience the highest loss, followed by A. nemorosa, A. ranunculoides, and the smallest for C. majalis. A. ranunculoides will gain the most, while M. bifolium will have the smallest potential range expansion. Studied species may respond differently to climate change despite similar current distributions and climatic variables affecting their potential distribution. Even slight differences in climatic niches could reduce the overlap of future ranges compared to present. We expect that due to high dependence on the warmest quarter precipitation, summer droughts in the future may be particularly severe for species that prefer moist soils. The lack of adaptation to long-distance migration and limited availability of appropriate soils may limit their migration and lead to a decline in biodiversity and changes in European forests.
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Affiliation(s)
- Radosław Puchałka
- Department of Ecology and Biogeography, Nicolaus Copernicus University in Toruń, Poland; Centre for Climate Change Research, Nicolaus Copernicus University in Toruń, Poland.
| | | | - Łukasz Dylewski
- Department of Zoology, Poznań University of Life Sciences, Poland
| | - Patryk Czortek
- Białowieża Geobotanical Station, Faculty of Biology, University of Warsaw, Białowieża, Poland
| | - Michaela Vítková
- Department of Invasion Ecology, Czech Academy of Sciences, Institute of Botany, Průhonice, Czech Republic
| | - Jiří Sádlo
- Department of Invasion Ecology, Czech Academy of Sciences, Institute of Botany, Průhonice, Czech Republic
| | - Marcin Klisz
- Department of Silviculture and Genetics, Forest Research Institute, Poland
| | - Serhii Koniakin
- Department of Phytoecology, Institute for Evolutionary Ecology, National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Andraž Čarni
- Research Center of the Slovenian Academy of Sciences and Arts, Institute of Biology, Ljubljana, Slovenia; University of Nova Gorica, School for Viticulture and Enology, Nova Gorica, Slovenia
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25
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Eckert I, Brown A, Caron D, Riva F, Pollock LJ. 30×30 biodiversity gains rely on national coordination. Nat Commun 2023; 14:7113. [PMID: 37932316 PMCID: PMC10628259 DOI: 10.1038/s41467-023-42737-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/17/2023] [Indexed: 11/08/2023] Open
Abstract
Global commitments to protect 30% of land by 2030 present an opportunity to combat the biodiversity crisis, but reducing extinction risk will depend on where countries expand protection. Here, we explore a range of 30×30 conservation scenarios that vary what dimension of biodiversity is prioritized (taxonomic groups, species-at-risk, biodiversity facets) and how protection is coordinated (transnational, national, or regional approaches) to test which decisions influence our ability to capture biodiversity in spatial planning. Using Canada as a model nation, we evaluate how well each scenario captures biodiversity using scalable indicators while accounting for climate change, data bias, and uncertainty. We find that only 15% of all terrestrial vertebrates, plants, and butterflies (representing only 6.6% of species-at-risk) are adequately represented in existing protected land. However, a nationally coordinated approach to 30×30 could protect 65% of all species representing 40% of all species-at-risk. How protection is coordinated has the largest impact, with regional approaches protecting up to 38% fewer species and 65% fewer species-at-risk, while the choice of biodiversity incurs much smaller trade-offs. These results demonstrate the potential of 30×30 while highlighting the critical importance of biodiversity-informed national strategies.
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Affiliation(s)
- Isaac Eckert
- Dept. of Biology, McGill University, H3A 1B1, Montreal, QC, Canada.
- Quebec Center for Biodiversity Science, Montreal, QC, Canada.
| | - Andrea Brown
- Dept. of Biology, McGill University, H3A 1B1, Montreal, QC, Canada
- Quebec Center for Biodiversity Science, Montreal, QC, Canada
| | - Dominique Caron
- Dept. of Biology, McGill University, H3A 1B1, Montreal, QC, Canada
- Quebec Center for Biodiversity Science, Montreal, QC, Canada
| | - Federico Riva
- Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Laura J Pollock
- Dept. of Biology, McGill University, H3A 1B1, Montreal, QC, Canada.
- Quebec Center for Biodiversity Science, Montreal, QC, Canada.
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26
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Zhang H, Guo W, Wang W. The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models. Ecol Evol 2023; 13:e10747. [PMID: 38020673 PMCID: PMC10659948 DOI: 10.1002/ece3.10747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 10/29/2023] [Accepted: 11/06/2023] [Indexed: 12/01/2023] Open
Abstract
How to effectively obtain species-related low-dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high-dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.
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Affiliation(s)
- Hao‐Tian Zhang
- School of Mathematics and Computer ScienceNorthwest Minzu UniversityLanzhouChina
| | - Wen‐Yong Guo
- Research Center for Global Change and Complex Ecosystems, School of Ecological and Environmental SciencesEast China Normal UniversityShanghaiChina
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental SciencesEast China Normal UniversityShanghaiChina
| | - Wen‐Ting Wang
- School of Mathematics and Computer ScienceNorthwest Minzu UniversityLanzhouChina
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27
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Maitner B, Gallagher R, Svenning JC, Tietje M, Wenk EH, Eiserhardt WL. A global assessment of the Raunkiaeran shortfall in plants: geographic biases in our knowledge of plant traits. THE NEW PHYTOLOGIST 2023; 240:1345-1354. [PMID: 37369249 DOI: 10.1111/nph.18999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 05/03/2023] [Indexed: 06/29/2023]
Abstract
This article is part of the Special Collection ‘Global plant diversity and distribution’. See https://www.newphytologist.org/global-plant-diversity for more details.
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Affiliation(s)
- Brian Maitner
- Department of Geography, University at Buffalo, 125a Wilkeson Quadrangle, Buffalo, NY, 14261, USA
| | - Rachael Gallagher
- Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia
| | - Jens-Christian Svenning
- Department of Biology, Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) & Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Aarhus University, Ny Munkegade 114, DK-8000, Aarhus C, Denmark
| | - Melanie Tietje
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Ny Munkegade 114, DK-8000, Aarhus C, Denmark
| | - Elizabeth H Wenk
- Evolution & Ecology Research Centre, School of Biological, Earth, and Environmental Sciences, UNSW Sydney, Sydney, NSW, 2033, Australia
| | - Wolf L Eiserhardt
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Ny Munkegade 114, DK-8000, Aarhus C, Denmark
- Royal Botanic Gardens, Kew, Richmond, TW9 3AE, Surrey, UK
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28
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Schoeman DS, Gupta AS, Harrison CS, Everett JD, Brito-Morales I, Hannah L, Bopp L, Roehrdanz PR, Richardson AJ. Demystifying global climate models for use in the life sciences. Trends Ecol Evol 2023; 38:843-858. [PMID: 37179171 DOI: 10.1016/j.tree.2023.04.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 05/15/2023]
Abstract
For each assessment cycle of the Intergovernmental Panel on Climate Change (IPCC), researchers in the life sciences are called upon to provide evidence to policymakers planning for a changing future. This research increasingly relies on highly technical and complex outputs from climate models. The strengths and weaknesses of these data may not be fully appreciated beyond the climate modelling community; therefore, uninformed use of raw or preprocessed climate data could lead to overconfident or spurious conclusions. We provide an accessible introduction to climate model outputs that is intended to empower the life science community to robustly address questions about human and natural systems in a changing world.
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Affiliation(s)
- David S Schoeman
- Ocean Futures Research Cluster, School of Science, Technology and Engineering, University of the Sunshine Coast, Maroochydore, Queensland, Australia; Centre for African Conservation Ecology, Department of Zoology, Nelson Mandela University, Gqeberha, South Africa.
| | - Alex Sen Gupta
- Climate Change Research Centre, University of New South Wales, Sydney, Australia; Australian Research Council, Centre of Excellence for Climate Extremes, The University of New South Wales, Sydney, New South Wales, Australia; Centre for Marine Science and Innovation, University of New South Wales, Sydney, Australia
| | - Cheryl S Harrison
- Department of Ocean and Coastal Science, Center for Computation and Technology, Louisiana State University, Baton Rouge, LA, USA
| | - Jason D Everett
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Environment, St Lucia, Queensland, Australia; School of Environment, The University of Queensland, St Lucia, Queensland, Australia; Centre for Marine Science and Innovation, University of New South Wales, Sydney, Australia
| | - Isaac Brito-Morales
- Betty and Gordon Moore Center for Science, Conservation International, Arlington, VA, USA; Marine Science Institute, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Lee Hannah
- Betty and Gordon Moore Center for Science, Conservation International, Arlington, VA, USA
| | - Laurent Bopp
- LMD/IPSL, Ecole Normale Supérieure/Université PSL, CNRS, Ecole Polytechnique, Sorbonne Université, Paris, France
| | - Patrick R Roehrdanz
- Betty and Gordon Moore Center for Science, Conservation International, Arlington, VA, USA
| | - Anthony J Richardson
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Environment, St Lucia, Queensland, Australia; School of Environment, The University of Queensland, St Lucia, Queensland, Australia
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Karger DN, Saladin B, Wüest RO, Graham CH, Zurell D, Mo L, Zimmermann NE. Interannual climate variability improves niche estimates for ectothermic but not endothermic species. Sci Rep 2023; 13:12538. [PMID: 37532828 PMCID: PMC10397316 DOI: 10.1038/s41598-023-39637-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 07/28/2023] [Indexed: 08/04/2023] Open
Abstract
Climate is an important limiting factor of species' niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over their lifespan and within their geographical range which is unlikely captured by long-term means. Further, depending on their physiology, distinct groups of species cope with climate variability differently. Ectothermic species, which are directly dependent on the thermal environment are expected to show a different response to temporal or spatial variability in temperature than endothermic groups that can decouple their internal temperature from that of their surroundings. Here, we explore the degree to which spatial variability and long-term temporal variability in temperature and precipitation change niche estimates for ectothermic (730 amphibian, 1276 reptile), and endothermic (1961 mammal) species globally. We use three different species distribution modelling (SDM) algorithms to quantify the effect of spatial and temporal climate variability, based on global range maps of all species and climate data from 1979 to 2013. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). The mean performance of SDMs using only climatic means as predictors was TSS = 0.71 and AUC = 0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS = 0.74, mean AUC = 0.92), as does the inclusion of temporal variability (mean TSS = 0.80, mean AUC = 0.94). Including both spatial and temporal variability in SDMs shows the highest scores in AUC and TSS. Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in ectotherm groups such as amphibians and reptiles, while for endothermic mammals no such improvement was observed. These results indicate that including long term climate interannual climate variability into niche estimations matters most for ectothermic species that cannot decouple their physiology from the surrounding environment as endothermic species can.
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Affiliation(s)
- Dirk Nikolaus Karger
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland.
| | - Bianca Saladin
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - Rafael O Wüest
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - Catherine H Graham
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - Damaris Zurell
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
- University of Potsdam, Maulbeerallee 3, 14469, Potsdam, Germany
| | - Lidong Mo
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
- ETH Zurich, Universitätstrasse 16, 8092, Zürich, Switzerland
| | - Niklaus E Zimmermann
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
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Nikkel E, Clements DR, Anderson D, Williams JL. Regional habitat suitability for aquatic and terrestrial invasive plant species may expand or contract with climate change. Biol Invasions 2023; 25:3805-3822. [PMID: 37854296 PMCID: PMC10579163 DOI: 10.1007/s10530-023-03139-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 07/14/2023] [Indexed: 10/20/2023]
Abstract
The threat of invasive species to biodiversity and ecosystem structure is exacerbated by the increasingly concerning outlook of predicted climate change and other human influences. Developing preventative management strategies for invasive plant species before they establish is crucial for effective management. To examine how climate change may impact habitat suitability, we modeled the current and future habitat suitability of two terrestrial species, Geranium lucidum and Pilosella officinarum, and two aquatic species, Butomus umbellatus and Pontederia crassipes, that are relatively new invasive plant species regionally, and are currently spreading in the Pacific Northwest (PNW, North America), an area of unique natural areas, vibrant economic activity, and increasing human population. Using North American presence records, downscaled climate variables, and human influence data, we developed an ensemble model of six algorithms to predict the potential habitat suitability under current conditions and projected climate scenarios RCP 4.5, 7.0, and 8.5 for 2050 and 2080. One terrestrial species (P. officinarum) showed declining habitat suitability in future climate scenarios (contracted distribution), while the other terrestrial species (G. lucidum) showed increased suitability over much of the region (expanded distribution overall). The two aquatic species were predicted to have only moderately increased suitability, suggesting aquatic plant species may be less impacted by climate change. Our research provides a template for regional-scale modelling of invasive species of concern, thus assisting local land managers and practitioners to inform current and future management strategies and to prioritize limited available resources for species with expanding ranges. Supplementary Information The online version contains supplementary material available at 10.1007/s10530-023-03139-8.
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Affiliation(s)
- Emma Nikkel
- Department of Geography, University of British Columbia, Vancouver, BC Canada
| | - David R. Clements
- Department of Biology, Trinity Western University, Langley, BC Canada
| | - Delia Anderson
- Department of Biology, Trinity Western University, Langley, BC Canada
| | - Jennifer L. Williams
- Department of Geography and Biodiversity Research Centre, University of British Columbia, Vancouver, BC Canada
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García Criado M, Myers-Smith IH, Bjorkman AD, Normand S, Blach-Overgaard A, Thomas HJD, Eskelinen A, Happonen K, Alatalo JM, Anadon-Rosell A, Aubin I, Te Beest M, Betway-May KR, Blok D, Buras A, Cerabolini BEL, Christie K, Cornelissen JHC, Forbes BC, Frei ER, Grogan P, Hermanutz L, Hollister RD, Hudson J, Iturrate-Garcia M, Kaarlejärvi E, Kleyer M, Lamarque LJ, Lembrechts JJ, Lévesque E, Luoto M, Macek P, May JL, Prevéy JS, Schaepman-Strub G, Sheremetiev SN, Siegwart Collier L, Soudzilovskaia NA, Trant A, Venn SE, Virkkala AM. Plant traits poorly predict winner and loser shrub species in a warming tundra biome. Nat Commun 2023; 14:3837. [PMID: 37380662 DOI: 10.1038/s41467-023-39573-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 06/15/2023] [Indexed: 06/30/2023] Open
Abstract
Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces.
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Affiliation(s)
| | | | - Anne D Bjorkman
- Department of Biology and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Signe Normand
- Department of Biology, Aarhus University, Aarhus, Denmark
| | | | - Haydn J D Thomas
- School of GeoSciences, University of Edinburgh, Edinburgh, Scotland, UK
| | - Anu Eskelinen
- Department of Physiological Diversity, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Konsta Happonen
- Department of Biology and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Juha M Alatalo
- Environmental Science Center, Qatar University, Doha, Qatar
| | - Alba Anadon-Rosell
- CREAF, Cerdanyola del Vallès, Barcelona, Catalonia, Spain
- Institute of Botany and Landscape Ecology, University of Greifswald, Greifswald, Germany
| | - Isabelle Aubin
- Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, Sault Ste Marie, ON, Canada
| | - Mariska Te Beest
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands
- Centre for African Conservation Ecology, Nelson Mandela University, Port Elizabeth, South Africa
| | | | - Daan Blok
- Dutch Research Council (NWO), The Hague, The Netherlands
| | - Allan Buras
- Land Surface-Atmosphere Interactions, School of Life Sciences Weihenstephan, Freising, Germany
| | - Bruno E L Cerabolini
- Department of Biotechnologies and Life Sciences, University of Insubria, Varese, Italy
| | - Katherine Christie
- Threatened, Endangered, and Diversity Program, Alaska Department of Fish and Game, Anchorage, USA
| | - J Hans C Cornelissen
- Section Systems Ecology, Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit, Amsterdam, The Netherlands
| | - Bruce C Forbes
- Arctic Centre, University of Lapland, Rovaniemi, Finland
| | - Esther R Frei
- WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
- Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
- Department of Geography, University of British Columbia, Vancouver, BC, Canada
- Climate Change and Extremes in Alpine Regions Research Centre CERC, Davos, Switzerland
| | - Paul Grogan
- Department of Biology, Queen's University, Kingston, Ontario, ON, Canada
| | - Luise Hermanutz
- Department of Biology, Memorial University, St. John's, NL, Canada
| | | | - James Hudson
- Government of British Columbia, Vancouver, BC, Canada
| | - Maitane Iturrate-Garcia
- Department of Chemical and Biological Metrology, Federal Institute of Metrology METAS, Bern-Wabern, Switzerland
| | - Elina Kaarlejärvi
- Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland
| | - Michael Kleyer
- Institute of Biology and Environmental Sciences, University of Oldenburg, Oldenburg, Germany
| | - Laurent J Lamarque
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
| | - Jonas J Lembrechts
- Research Group Plants and Ecosystems (PLECO), University of Antwerp, Wilrijk, Belgium
| | - Esther Lévesque
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
| | - Miska Luoto
- Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
| | - Petr Macek
- Institute of Hydrobiology, Biology Centre of the Czech Academy of Sciences, Ceske Budejovice, Czech Republic
| | - Jeremy L May
- Department of Biological Sciences, Florida International University, Miami, FL, USA
- Department of Biology and Environmental Science, Marietta College, Marietta, OH, USA
| | - Janet S Prevéy
- WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
- U.S. Geological Survey, Fort Collins, CO, USA
| | - Gabriela Schaepman-Strub
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | | | - Laura Siegwart Collier
- Department of Biology, Memorial University, St. John's, NL, Canada
- Terra Nova National Park, Parks Canada Agency, Glovertown, NL, Canada
| | | | - Andrew Trant
- School of Environment, Resources and Sustainability, University of Waterloo, Waterloo, ON, Canada
| | - Susanna E Venn
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, VIC, Australia
| | - Anna-Maria Virkkala
- Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
- Woodwell Climate Research Center, Falmouth, MA, USA
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32
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de Aguiar CVS, Alencar JBR, da Silva Santana G, Teles BR. Predicting the Potential Global Distribution of Scirtothrips dorsalis (Hood) (Thysanoptera: Thripidae) with Emphasis on the Americas Using an Ecological Niche Model. NEOTROPICAL ENTOMOLOGY 2023; 52:512-520. [PMID: 36884146 DOI: 10.1007/s13744-023-01038-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 02/23/2023] [Indexed: 05/13/2023]
Abstract
Scirtothrips dorsalis Hood (Thysanoptera: Thripidae) is an invasive pest that is popularly known as chilli thrips. This insect pest has a wide range of hosts distributed across 72 plant families, causing damage to numerous crops of great economic importance. In the Americas, it is present in the USA, Mexico, Suriname, Venezuela, Colombia, and some Caribbean Islands. Knowing the regions which have environmentally suitable conditions for the survival of this pest is important for phytosanitary monitoring and inspection. Thus, our objective was to forecast the distribution potential of S. dorsalis with a focus on the Americas. Models were produced to design this distribution, in which the environmental variables used were made available in Wordclim version 2.1. The algorithms used for the modeling were the generalized additive model (GAM), generalized linear model (GLM), maximum entropy (MAXENT), random forest (RF), and Bioclim, in addition to the ensemble, which consisted of the grouping of the algorithms used. The metrics used to evaluate the models were area over the curve (AUC), true ability statistics (TSS), and Sorensen score. All models had satisfactory results (> 0.8) for all metrics used. In North America, the model showed favorable regions on the west coast of the USA and east coast near New York. In South America, the potential distribution of the pest is significant, encompassing regions in all countries. It is concluded that S. dorsalis has suitable areas for the occurrence in the three American subcontinents and, in particular, a large part of South America.
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Affiliation(s)
- Caio Victor Soares de Aguiar
- Programa de Pós-Graduação em Agricultura no Trópico Úmido, Instituto Nacional de Pesquisas da Amazônia, Manaus, Amazonas, Brazil.
| | | | - Geovani da Silva Santana
- Programa de Pós-Graduação em Ciências Biológicas (Entomologia), Instituto Nacional de Pesquisas da Amazônia, Manaus, Amazonas, Brazil
| | - Beatriz Ronchi Teles
- Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazonia, Manaus, Amazonas, Brazil
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Cenni L, Simoncini A, Massetti L, Rizzoli A, Hauffe HC, Massolo A. Current and future distribution of a parasite with complex life cycle under global change scenarios: Echinococcus multilocularis in Europe. GLOBAL CHANGE BIOLOGY 2023; 29:2436-2449. [PMID: 36815401 DOI: 10.1111/gcb.16616] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/06/2023] [Indexed: 05/28/2023]
Abstract
Global change is expected to have complex effects on the distribution and transmission patterns of zoonotic parasites. Modelling habitat suitability for parasites with complex life cycles is essential to further our understanding of how disease systems respond to environmental changes, and to make spatial predictions of their future distributions. However, the limited availability of high quality occurrence data with high spatial resolution often constrains these investigations. Using 449 reliable occurrence records for Echinococcus multilocularis from across Europe published over the last 35 years, we modelled habitat suitability for this parasite, the aetiological agent of alveolar echinococcosis, in order to describe its environmental niche, predict its current and future distribution under three global change scenarios, and quantify the probability of occurrence for each European country. Using a machine learning approach, we developed large-scale (25 × 25 km) species distribution models based on seven sets of predictors, each set representing a distinct biological hypothesis supported by current knowledge of the autecology of the parasite. The best-supported hypothesis included climatic, orographic and land-use/land-cover variables such as the temperature of the coldest quarter, forest cover, urban cover and the precipitation seasonality. Future projections suggested the appearance of highly suitable areas for E. multilocularis towards northern latitudes and in the whole Alpine region under all scenarios, while decreases in habitat suitability were predicted for central Europe. Our spatially explicit predictions of habitat suitability shed light on the complex responses of parasites to ongoing global changes.
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Affiliation(s)
- Lucia Cenni
- Ethology Unit, Department of Biology, University of Pisa, Pisa, Italy
- Applied Ecology Research Unit, Research and Innovation Centre, Fondazione Edmund Mach, Trento, Italy
- Conservation Genomics Research Unit, Research and Innovation Centre, Fondazione Edmund Mach, Trento, Italy
| | - Andrea Simoncini
- Ethology Unit, Department of Biology, University of Pisa, Pisa, Italy
| | - Luciano Massetti
- Institute of Bioeconomy of the National Research Council, Firenze, Italy
| | - Annapaola Rizzoli
- Applied Ecology Research Unit, Research and Innovation Centre, Fondazione Edmund Mach, Trento, Italy
| | - Heidi C Hauffe
- Conservation Genomics Research Unit, Research and Innovation Centre, Fondazione Edmund Mach, Trento, Italy
| | - Alessandro Massolo
- Ethology Unit, Department of Biology, University of Pisa, Pisa, Italy
- Faculty of Veterinary Medicine, University of Calgary, Alberta, Calgary, Canada
- UMR CNRS 6249 Chrono-environnement, Université Bourgogne Franche-Comté, Besançon, France
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da Silva JP, Sousa R, Gonçalves DV, Miranda R, Reis J, Teixeira A, Varandas S, Lopes-Lima M, Filipe AF. Streams in the Mediterranean Region are not for mussels: Predicting extinctions and range contractions under future climate change. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 883:163689. [PMID: 37100131 DOI: 10.1016/j.scitotenv.2023.163689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/18/2023] [Accepted: 04/19/2023] [Indexed: 05/03/2023]
Abstract
Climate change is becoming the leading driver of biodiversity loss. The Mediterranean region, particularly southwestern Europe, is already confronting the consequences of ongoing global warming. Unprecedented biodiversity declines have been recorded, particularly within freshwater ecosystems. Freshwater mussels contribute to essential ecosystem services but are among the most threatened faunal groups on Earth. Their poor conservation status is related to the dependence on fish hosts to complete the life cycle, which also makes them particularly vulnerable to climate change. Species Distribution Models (SDMs) are commonly used to predict species distributions, but often disregard the potential effect of biotic interactions. This study investigated the potential impact of future climate on the distribution of freshwater mussel species while considering their obligatory interaction with fish hosts. Specifically, ensemble models were used to forecast the current and future distribution of six mussel species in the Iberian Peninsula, including environmental conditions and the distribution of fish hosts as predictors. We found that climate change is expected to severely impact the future distribution of Iberian mussels. Species with narrow ranges, namely Margaritifera margaritifera and Unio tumidiformis, were predicted to have their suitable habitats nearly lost and could potentially be facing regional and global extinctions, respectively. Anodonta anatina, Potomida littoralis, and particularly Unio delphinus and Unio mancus, are expected to suffer distributional losses but may gain new suitable habitats. A shift in their distribution to new suitable areas is only possible if fish hosts are able to disperse while carrying larvae. We also found that including the distribution of fish hosts in the mussels' models avoided the underprediction of habitat loss under climate change. This study warns of the imminent loss of mussel species and populations and the urgent need of management actions to reverse current trends and mitigate irreversible damage to species and ecosystems in Mediterranean regions.
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Affiliation(s)
- Janine P da Silva
- CBMA - Centre of Molecular and Environmental Biology, Department of Biology, University of Minho, Campus Gualtar, 4710-057 Braga, Portugal.
| | - Ronaldo Sousa
- CBMA - Centre of Molecular and Environmental Biology, Department of Biology, University of Minho, Campus Gualtar, 4710-057 Braga, Portugal
| | - Duarte Vasconcelos Gonçalves
- CIIMAR - Centro Interdisciplinar de Investigação Marinha e Ambiental, University of Porto, 4450-208 Matosinhos, Portugal
| | - Rafael Miranda
- Instituto de Biodiversidad y Medioambiente (BIOMA), Universidad de Navarra, Irunlarrea 1, 31008, Navarra, Spain
| | - Joaquim Reis
- MARE - Marine and Environmental Sciences Centre//ARNET-Aquatic Research Network, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
| | - Amílcar Teixeira
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Simone Varandas
- CITAB-UTAD - Centre for Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes and Alto Douro, Forestry Department, Vila Real, Portugal; CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources, University of Porto, Campus Agrário de Vairão, 4485-661 Vairão, Portugal
| | - Manuel Lopes-Lima
- CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources, University of Porto, Campus Agrário de Vairão, 4485-661 Vairão, Portugal
| | - Ana Filipa Filipe
- Forest Research Centre and Associated Laboratory TERRA, School of Agriculture, University of Lisbon, Lisbon, Portugal; TERRA Associate Laboratory, School of Agriculture, University of Lisbon, Lisbon, Portugal
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Cardillo M, Skeels A, Dinnage R. Priorities for conserving the world's terrestrial mammals based on over-the-horizon extinction risk. Curr Biol 2023; 33:1381-1388.e6. [PMID: 37040697 DOI: 10.1016/j.cub.2023.02.063] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/15/2022] [Accepted: 02/21/2023] [Indexed: 04/13/2023]
Abstract
Three major axes of global change put the world's mammal biodiversity at risk: climate change, human population growth, and land-use change.1,2,3,4,5,6,7,8,9,10,11,12 In some parts of the world the full effects of these threats on species will only be felt in decades to come, yet conservation emphasizes species currently threatened with extinction, by threats that have already occurred. There have been calls for conservation to become more proactive by anticipating and protecting species that may not yet be threatened, but have a high chance of becoming threatened in the future.3,6,8,10,12,13,14 We refer to this as "over-the-horizon" extinction risk, and we identify such species among the world's nonmarine mammals by considering not only the severity of increase in threats faced by each species, but also the way each species' biology confers sensitivity or robustness to threats. We define four future risk factors based on species' biology and projected exposure to severe change in climate, human population, and land use. We regard species with two or more of these risk factors as especially vulnerable to future extinction risk.10,15,16,17,18,19 Our models predict that by 2100 up to 1,057 (20%) of nonmarine mammal species will have combinations of two or more future risk factors. These species will be particularly concentrated in two future risk hotspots in sub-Saharan Africa and southern/eastern Australia. Proactively targeting species with over-the-horizon extinction risk could help to future-proof global conservation planning and prevent a new wave of mammal species from becoming threatened with extinction by the end of this century.
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Affiliation(s)
- Marcel Cardillo
- Research School of Biology, Australian National University, 46 Sullivans Creek Rd, Acton, ACT 0200, Australia.
| | - Alexander Skeels
- Research School of Biology, Australian National University, 46 Sullivans Creek Rd, Acton, ACT 0200, Australia; Landscape Ecology, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, CH-8092 Zürich, Switzerland
| | - Russell Dinnage
- Research School of Biology, Australian National University, 46 Sullivans Creek Rd, Acton, ACT 0200, Australia; Institute of Environment, Department of Biological Sciences, Florida International University, Miami, FL 33199, USA
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Wang M, Hu Z, Wang Y, Zhao W. Spatial Distribution Characteristics of Suitable Planting Areas for Pyrus Species under Climate Change in China. PLANTS (BASEL, SWITZERLAND) 2023; 12:1559. [PMID: 37050185 PMCID: PMC10097120 DOI: 10.3390/plants12071559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 03/29/2023] [Accepted: 04/03/2023] [Indexed: 06/19/2023]
Abstract
Planting suitability determines the distribution and yield of crops in a given region which can be greatly affected by climate change. In recent years, many studies have shown that carbon dioxide fertilization effects increase the productivity of temperate deciduous fruit trees under a changing climate, but the potential risks to fruit tree planting caused by a reduction in suitable planting areas are rarely reported. In this study, Maxent was first used to investigate the spatial distribution of five Pyrus species in China, and the consistency between the actual production area and the modeled climatically suitable area under the current climatic conditions were determined. In addition, based on Coupled Model Intercomparison Project Phase 6, three climate models were used to simulate the change in suitable area and the migration trend for different species under different emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). The results showed that the suitable area for pear was highly consistent with the actual main production area under current climate conditions. The potential planting areas of P. ussuriensis showed a downward trend under all emission paths from 2020 to 2100; other species showed a trend of increasing first and then decreasing or slowing down and this growth effect was the most obvious in 2020-2040. Except for P. pashia, other species showed a migration trend toward a high latitude, and the trend was more prominent under the high emission path. Our results emphasize the response difference between species to climate change, and the method of consistency analysis between suitable planting area and actual production regions cannot only evaluate the potential planting risk but also provide a reasonable idea for the accuracy test of the modeled results. This work has certain guiding and reference significance for the protection of pear germplasm resources and the prediction of yield.
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Affiliation(s)
- Mi Wang
- College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
| | - Zhuowei Hu
- College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
| | - Yongcai Wang
- College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
| | - Wenji Zhao
- College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
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Zhao X, Guo Y, Kang L, Yin C, Bi A, Xu D, Zhang Z, Zhang J, Yang X, Xu J, Xu S, Song X, Zhang M, Li Y, Kear P, Wang J, Liu Z, Fu X, Lu F. Population genomics unravels the Holocene history of bread wheat and its relatives. NATURE PLANTS 2023; 9:403-419. [PMID: 36928772 DOI: 10.1038/s41477-023-01367-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 02/08/2023] [Indexed: 05/06/2023]
Abstract
Deep knowledge of crop biodiversity is essential to improving global food security. Despite bread wheat serving as a keystone crop worldwide, the population history of bread wheat and its relatives, both cultivated and wild, remains elusive. By analysing whole-genome sequences of 795 wheat accessions, we found that bread wheat originated from the southwest coast of the Caspian Sea and underwent a slow speciation process, lasting ~3,300 yr owing to persistent gene flow from its relatives. Soon after, bread wheat spread across Eurasia and reached Europe, South Asia and East Asia ~7,000 to ~5,000 yr ago, shaping a diversified but occasionally convergent adaptive landscape in novel environments. By contrast, the cultivated relatives of bread wheat experienced a population decline by ~82% over the past ~2,000 yr due to the food choice shift of humans. Further biogeographical modelling predicted a continued population shrinking of many bread wheat relatives in the coming decades because of their vulnerability to the changing climate. These findings will guide future efforts in protecting and utilizing wheat biodiversity to enhance global wheat production.
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Affiliation(s)
- Xuebo Zhao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yafei Guo
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lipeng Kang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Changbin Yin
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Aoyue Bi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Daxing Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhiliang Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jijin Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaohan Yang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jun Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Song Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xinyue Song
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Conservation and Utilization of Bio-Resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, China
| | - Ming Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yiwen Li
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Philip Kear
- International Potato Center-China Center for Asia and the Pacific, Beijing, China
| | - Jing Wang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Zhiyong Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiangdong Fu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fei Lu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.
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Pacioni C, Sentís M, Kerimov A, Bushuev A, Lens L, Strubbe D. Seasonal variation in thermoregulatory capacity of three closely related Afrotropical Estrildid finches introduced to Europe. J Therm Biol 2023; 113:103534. [PMID: 37055139 DOI: 10.1016/j.jtherbio.2023.103534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/07/2023]
Abstract
A species' potential geographical range is largely determined by how the species responds physiologically to its changing environment. It is therefore crucial to study the physiological mechanisms that species use to maintain their homeothermy in order to address biodiversity conservation challenges, such as the success of invasions of introduced species. The common waxbill Estrilda astrild, the orange-cheeked waxbill E. melpoda, and the black-rumped waxbill E. troglodytes are small Afrotropical passerines that have established invasive populations in regions where the climate is colder than in their native ranges. As a result, they are highly suitable species for studying potential mechanisms for coping with a colder and more variable climate. Here, we investigated the magnitude and direction of seasonal variation in their thermoregulatory traits, such as basal (BMR), summit (Msum) metabolic rates and thermal conductance. We found that, from summer to autumn, their ability to resist colder temperatures increased. This was not related to larger body masses or higher BMR and Msum, but instead, species downregulated BMR and Msum toward the colder season, suggesting energy conservation mechanisms to increase winter survival. BMR and Msum were most strongly correlated with temperature variation in the week preceding the measurements. Common waxbill and black-rumped waxbill, whose native ranges encompass the highest degree of seasonality, showed the most flexibility in metabolic rates (i.e., stronger downregulation toward colder seasons). This ability to adjust thermoregulatory traits, combined with increased cold tolerance, may facilitate their establishment in areas characterized by colder winters and less predictable climates.
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Lopes A, Demarchi LO, Piedade MTF, Schöngart J, Wittmann F, Munhoz CBR, Ferreira CS, Franco AC. Predicting the range expansion of invasive alien grasses under climate change in the Neotropics. Perspect Ecol Conserv 2023. [DOI: 10.1016/j.pecon.2023.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023] Open
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40
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Rossi JP, Rasplus JY. Climate change and the potential distribution of the glassy-winged sharpshooter (Homalodisca vitripennis), an insect vector of Xylella fastidiosa. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 860:160375. [PMID: 36423847 DOI: 10.1016/j.scitotenv.2022.160375] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 11/17/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
Biological invasions represent a major threat for biodiversity and agriculture. Despite efforts to restrict the spread of alien species, preventing their introduction remains the best strategy for an efficient control. In that context preparedness of phytosanitary authorities is very important and estimating the geographical range of alien species becomes a key information. The present study investigates the potential geographical range of the glassy-winged sharpshooter (Homalodisca vitripennis), a very efficient insect vector of Xylella fastidiosa, one of the most dangerous plant-pathogenic bacteria worldwide. We use species distribution modeling (SDM) to analyse the climate factors driving the insect distribution and we evaluate its potential distribution in its native range (USA) and in Europe according to current climate and different scenarios of climate change: 6 General Circulation Models (GCM), 4 shared socioeconomic pathways of gas emission and 4 time periods (2030, 2050, 2070, 2090). The first result is that the climate conditions of the European continent are suitable to the glassy-winged sharpshooter, in particular around the Mediterranean basin where X. fastidiosa is present. Projections according to future climate conditions indicate displacement of climatically suitable areas towards the north in both North America and Europe. Globally, suitable areas will decrease in North America and increase in Europe in the coming decades. SDM outputs vary according to the GCM considered and this variability indicated areas of uncertainty in the species potential range. Both potential distribution and its uncertainty associated to future climate projections are important information for improved preparedness of phytosanitary authorities.
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Affiliation(s)
- Jean-Pierre Rossi
- CBGP (Centre de Biologie pour la Gestion des Populations), INRAE, CIRAD, IRD, Institut Agro, Montpellier, France.
| | - Jean-Yves Rasplus
- CBGP (Centre de Biologie pour la Gestion des Populations), INRAE, CIRAD, IRD, Institut Agro, Montpellier, France.
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Gonçalves GSR, Cerqueira PV, Silva DP, Gomes LB, Leão CF, de Andrade AFA, Santos MPD. Multi-temporal ecological niche modeling for bird conservation in the face of climate change scenarios in Caatinga, Brazil. PeerJ 2023; 11:e14882. [PMID: 36874965 PMCID: PMC9979838 DOI: 10.7717/peerj.14882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 01/20/2023] [Indexed: 03/02/2023] Open
Abstract
Background Global shifts in climatic patterns have been recorded over the last decades. Such modifications mainly correspond to increased temperatures and rainfall regime changes, which are becoming more variable and extreme. Methods We aimed to evaluate the impact of future changes in climatic patterns on the distribution of 19 endemic or threatened bird taxa of the Caatinga. We assessed whether current protected areas (PAs) are adequate and whether they will maintain their effectiveness in the future. Also, we identified climatically stable areas that might work as refugia for an array of species. Results We observed that 84% and 87% of the bird species of Caatinga analyzed in this study will face high area losses in their predicted range distribution areas in future scenarios (RCP4.5 and RCP8.5, respectively). We also observed that the current PAs in Caatinga are ineffective in protecting these species in both present and future scenarios, even when considering all protection area categories. However, several suitable areas can still be allocated for conservation, where there are vegetation remnants and a high amount of species. Therefore, our study paves a path for conservation actions to mitigate current and future extinctions due to climate change by choosing more suitable protection areas.
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Affiliation(s)
| | - Pablo Vieira Cerqueira
- Laboratório de Biogeografia da Conservação e Macroecologia, Universidade Federal do Pará, Belém, Brazil
| | - Daniel Paiva Silva
- Departamento de Biologia, Instituto Federal Goiano, Urutaí, Goiás, Brazil
| | - Letícia Braga Gomes
- Laboratório de Biogeografia da Conservação e Macroecologia, Universidade Federal do Pará, Belém, Brazil
| | - Camila Ferreira Leão
- Laboratório de Biogeografia da Conservação e Macroecologia, Universidade Federal do Pará, Belém, Brazil
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Wang Y, Zhang L, Zhou Y, Ma W, Li M, Guo P, Feng L, Fu C. Using landscape genomics to assess local adaptation and genomic vulnerability of a perennial herb Tetrastigma hemsleyanum (Vitaceae) in subtropical China. Front Genet 2023; 14:1150704. [PMID: 37144128 PMCID: PMC10151583 DOI: 10.3389/fgene.2023.1150704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 04/04/2023] [Indexed: 05/06/2023] Open
Abstract
Understanding adaptive genetic variation of plant populations and their vulnerabilities to climate change are critical to preserve biodiversity and subsequent management interventions. To this end, landscape genomics may represent a cost-efficient approach for investigating molecular signatures underlying local adaptation. Tetrastigma hemsleyanum is, in its native habitat, a widespread perennial herb of warm-temperate evergreen forest in subtropical China. Its ecological and medicinal values constitute a significant revenue for local human populations and ecosystem. Using 30,252 single nucleotide polymorphisms (SNPs) derived from reduced-representation genome sequencing in 156 samples from 24 sites, we conducted a landscape genomics study of the T. hemsleyanum to elucidate its genomic variation across multiple climate gradients and genomic vulnerability to future climate change. Multivariate methods identified that climatic variation explained more genomic variation than that of geographical distance, which implied that local adaptation to heterogeneous environment might represent an important source of genomic variation. Among these climate variables, winter precipitation was the strongest predictor of the contemporary genetic structure. F ST outlier tests and environment association analysis totally identified 275 candidate adaptive SNPs along the genetic and environmental gradients. SNP annotations of these putatively adaptive loci uncovered gene functions associated with modulating flowering time and regulating plant response to abiotic stresses, which have implications for breeding and other special agricultural aims on the basis of these selection signatures. Critically, modelling revealed that the high genomic vulnerability of our focal species via a mismatch between current and future genotype-environment relationships located in central-northern region of the T. hemsleyanum's range, where populations require proactive management efforts such as assistant adaptation to cope with ongoing climate change. Taken together, our results provide robust evidence of local climate adaption for T. hemsleyanum and further deepen our understanding of adaptation basis of herbs in subtropical China.
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Affiliation(s)
- Yihan Wang
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Lin Zhang
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
- College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou, China
| | - Yuchao Zhou
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Wenxin Ma
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Manyu Li
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Peng Guo
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
- *Correspondence: Peng Guo, ; Li Feng,
| | - Li Feng
- School of Pharmacy, Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Peng Guo, ; Li Feng,
| | - Chengxin Fu
- Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, College of Life Sciences, Zhejiang University, Hangzhou, China
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Ureta C, Ramírez‐Barrón M, Sánchez‐García EA, Cuervo‐Robayo AP, Munguía‐Carrara M, Mendoza‐Ponce A, Gay C, Sánchez‐Cordero V. Species, taxonomic, and functional group diversities of terrestrial mammals at risk under climate change and land-use/cover change scenarios in Mexico. GLOBAL CHANGE BIOLOGY 2022; 28:6992-7008. [PMID: 36053734 PMCID: PMC9826092 DOI: 10.1111/gcb.16411] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 08/23/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
There is a need to revise the framework used to project species risks under climate change (CC) and land-use/cover change (LUCC) scenarios. We built a CC risk index using the latest Intergovernmental Panel on Climate Change framework, where risk is a function of vulnerability (sensitivity and adaptive capacity), exposure, and hazard. We incorporated future LUCC scenarios as part of the exposure component. We combined a trait-based approach based on biological characteristics of species with a correlative approach based on ecological niche modeling, assigning risk scores to species, taxonomic (orders), and functional (trophic, body size, and locomotion) groups of terrestrial mammals occurring in Mexico. We identified 15 species projected to lose their climatic suitability. Of the 11 taxonomic orders, Eulipotyphla, Didelphimorphia, Artiodactyla, and Lagomorpha had the highest risk scores. Of the 19 trophic groups, piscivores, insectivores under canopy, frugivores-granivores, herbivores browser, and myrmecophagous had the highest risk scores. Of the five body-sized groups, large-sized species (>15 kg) had highest risk scores. Of the seven locomotion groups, arboreal and semi-aquatics had highest risk scores. CC and LUCC scenarios reduced suitable areas of species potential distributions by 37.5% (with CC), and 51% (with CC and LUCC) under a limited full-dispersal assumption. Reductions in suitable areas of species potential distributions increased to 50.2% (with CC), and 52.4% (with CC and LUCC) under a non-dispersal assumption. Species-rich areas (>75% species) projected 36% (with CC) and 57% (with CC and LUCC) reductions in suitability for 2070. Shifts in climatic suitability projections of species-rich areas increased in number of species in northeast and southeast Mexico and decreased in northwest and southern Mexico, suggesting important species turnover. High-risk projections under future CC and LUCC scenarios for species, taxonomic, and functional group diversities, and species-rich areas of terrestrial mammals highlight trends in different impacts on biodiversity and ecosystem function.
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Affiliation(s)
- Carolina Ureta
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de MéxicoCiudad de MéxicoMexico
- Investigadora por México‐CONACyTConsejo Nacional de Ciencia y TecnologíaCiudad de MéxicoMexico
| | - Mercedes Ramírez‐Barrón
- Departamento de ZoologíaInstituto de Biología, Universidad Nacional Autónoma de MéxicoCiudad de MéxicoMexico
| | - Edgar Andrés Sánchez‐García
- Departamento de ZoologíaInstituto de Biología, Universidad Nacional Autónoma de MéxicoCiudad de MéxicoMexico
| | - Angela P. Cuervo‐Robayo
- Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Insurgentes Sur‐PeriféricoCiudad de MéxicoMexico
| | - Mariana Munguía‐Carrara
- Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Insurgentes Sur‐PeriféricoCiudad de MéxicoMexico
| | - Alma Mendoza‐Ponce
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de MéxicoCiudad de MéxicoMexico
- International Institute for Applied Systems AnalysisLaxenburgAustria
| | - Carlos Gay
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de MéxicoCiudad de MéxicoMexico
| | - Víctor Sánchez‐Cordero
- Departamento de ZoologíaInstituto de Biología, Universidad Nacional Autónoma de MéxicoCiudad de MéxicoMexico
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Prioritizing Areas for Primate Conservation in Argentina. DIVERSITY 2022. [DOI: 10.3390/d14110982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Argentina lies within the southernmost distributional range of five neotropical primates, the brown howler monkey Alouatta guariba, the black-and-gold howler monkey Alouatta caraya, the black-horned capuchin Sapajus nigritus, the Azara’s capuchin Sapajus cay, and the Azara’s owl monkey Aotus azarae; the first three of which are globally threatened. These species occupy different ecoregions: the Alto Paraná Atlantic forest, the Araucaria moist forest, the humid Chaco, the Southern Cone Mesopotamian savanna, the Paraná Ffooded savanna, and the Southern Andean Yungas. The recently approved National Primate Conservation Plan of Argentina calls for identifying priority areas to focus conservation actions for these species. We used species distribution models to estimate species ranges and then used the Zonation software to perform a spatial conservation prioritization analysis based on primate habitat quality and connectivity to identify potential areas of importance at national and ecoregional levels. Only 7.2% (19,500 km2) of the area inhabited by primates in Argentina is under protection. Outside the current protected areas, the top-ranked 1% and 5% priority areas identified in our analysis covered 1894 and 7574 km2, respectively. The top 1% areas were in the Atlantic forest of Misiones province, where S. nigritus, A. guariba, and A. caraya are distributed, and in the humid portion of eastern Chaco and Formosa provinces, where A. azarae and A. caraya are present. The top 5% areas included portions of the Yungas, where S. cay is the only primate present. Priority areas in Chaco and Formosa provinces are particularly relevant because of the paucity of protected areas and the high deforestation rate. The endangered A. guariba population will benefit from the better protection of the priority areas of Misiones. The potential priority areas proposed herein, considered within a context of a broad participatory process involving relevant stakeholders and local people, will help guide new and innovative conservation policies and practices while supporting management objectives.
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Brodie S, Smith JA, Muhling BA, Barnett LAK, Carroll G, Fiedler P, Bograd SJ, Hazen EL, Jacox MG, Andrews KS, Barnes CL, Crozier LG, Fiechter J, Fredston A, Haltuch MA, Harvey CJ, Holmes E, Karp MA, Liu OR, Malick MJ, Pozo Buil M, Richerson K, Rooper CN, Samhouri J, Seary R, Selden RL, Thompson AR, Tommasi D, Ward EJ, Kaplan IC. Recommendations for quantifying and reducing uncertainty in climate projections of species distributions. GLOBAL CHANGE BIOLOGY 2022; 28:6586-6601. [PMID: 35978484 PMCID: PMC9805044 DOI: 10.1111/gcb.16371] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/25/2022] [Accepted: 07/27/2022] [Indexed: 05/26/2023]
Abstract
Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.
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Affiliation(s)
- Stephanie Brodie
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationMontereyCaliforniaUSA
| | - James A. Smith
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSan DiegoCaliforniaUSA
| | - Barbara A. Muhling
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSan DiegoCaliforniaUSA
| | - Lewis A. K. Barnett
- Alaska Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | | | - Paul Fiedler
- Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSan DiegoCaliforniaUSA
| | - Steven J. Bograd
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationMontereyCaliforniaUSA
| | - Elliott L. Hazen
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationMontereyCaliforniaUSA
| | - Michael G. Jacox
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationMontereyCaliforniaUSA
- Physical Sciences Laboratory, Earth System Research LaboratoriesNational Oceanic and Atmospheric AdministrationBoulderColoradoUSA
| | - Kelly S. Andrews
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Cheryl L. Barnes
- Cooperative Institute for Climate, Ocean, and Ecosystem StudiesUniversity of WashingtonSeattleWashingtonUSA
| | - Lisa G. Crozier
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Jerome Fiechter
- Ocean Sciences DepartmentUniversity of California Santa CruzSanta CruzCaliforniaUSA
| | - Alexa Fredston
- Ocean Sciences DepartmentUniversity of California Santa CruzSanta CruzCaliforniaUSA
- Department of Ecology, Evolution, and Natural ResourcesRutgers UniversityNew BrunswickNew JerseyUSA
| | - Melissa A. Haltuch
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Chris J. Harvey
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Elizabeth Holmes
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Melissa A. Karp
- ECS Tech, in support of, NOAA Fisheries Office of Science and TechnologySilver SpringMarylandUSA
| | - Owen R. Liu
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Michael J. Malick
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Mercedes Pozo Buil
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationMontereyCaliforniaUSA
| | - Kate Richerson
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | | | - Jameal Samhouri
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Rachel Seary
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationMontereyCaliforniaUSA
| | - Rebecca L. Selden
- Department of Biological SciencesWellesley CollegeWellesleyMassachusettsUSA
| | - Andrew R. Thompson
- Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSan DiegoCaliforniaUSA
| | - Desiree Tommasi
- Institute of Marine SciencesUniversity of California Santa CruzMontereyCaliforniaUSA
- Southwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSan DiegoCaliforniaUSA
| | - Eric J. Ward
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
| | - Isaac C. Kaplan
- Northwest Fisheries Science Center, National Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationSeattleWashingtonUSA
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Lovrenčić L, Temunović M, Bonassin L, Grandjean F, Austin CM, Maguire I. Climate change threatens unique genetic diversity within the Balkan biodiversity hotspot – The case of the endangered stone crayfish. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2022.e02301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
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47
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Prager CM, Classen AT, Sundqvist MK, Barrios‐Garcia M, Cameron EK, Chen L, Chisholm C, Crowther TW, Deslippe JR, Grigulis K, He J, Henning JA, Hovenden M, Høye TTT, Jing X, Lavorel S, McLaren JR, Metcalfe DB, Newman GS, Nielsen ML, Rixen C, Read QD, Rewcastle KE, Rodriguez‐Cabal M, Wardle DA, Wipf S, Sanders NJ. Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network. Ecol Evol 2022; 12:e9396. [PMID: 36262264 PMCID: PMC9575997 DOI: 10.1002/ece3.9396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/25/2022] [Accepted: 05/31/2022] [Indexed: 11/10/2022] Open
Abstract
A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta‐analyses across many independent experiments. However, results from single‐site studies tend to have limited generality. Although meta‐analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long‐term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high‐ and low‐elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above‐ and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.
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Affiliation(s)
- Case M. Prager
- Ecology and Evolutionary Biology DepartmentUniversity of MichiganAnn ArborMichiganUSA,The Rocky Mountain Biological LaboratoryCrested ButteColoradoUSA
| | - Aimee T. Classen
- Ecology and Evolutionary Biology DepartmentUniversity of MichiganAnn ArborMichiganUSA,The Rocky Mountain Biological LaboratoryCrested ButteColoradoUSA,Natural History Museum of DenmarkUniversity of CopenhagenCopenhagenDenmark
| | - Maja K. Sundqvist
- Natural History Museum of DenmarkUniversity of CopenhagenCopenhagenDenmark,Department of Forest Ecology and ManagementSwedish University of Agricultural SciencesUmeåSweden
| | - Maria Noelia Barrios‐Garcia
- CONICET, CENAC‐APNSan Carlos de BarilocheRio NegroArgentina,Rubenstein School of Environment and Natural ResourcesUniversity of VermontBurlingtonVermontUSA
| | - Erin K. Cameron
- Department of Environmental ScienceSaint Mary's UniversityHalifaxNova ScotiaCanada
| | - Litong Chen
- Qinghai Provincial Key Laboratory of Restoration Ecology of Cold Area and Key Laboratory of Adaptation and Evolution of Plant BiotaNorthwest Institute of Plateau Biology, Chinese Academy of SciencesXiningChina
| | - Chelsea Chisholm
- Department of Environment Systems Science, Institute of Integrative BiologyETH ZürichZürichSwitzerland
| | - Thomas W. Crowther
- Department of Environment Systems Science, Institute of Integrative BiologyETH ZürichZürichSwitzerland
| | - Julie R. Deslippe
- Centre for Biodiversity and Restoration Ecology, School of Biological SciencesVictoria University of WellingtonWellingtonNew Zealand
| | - Karl Grigulis
- Laboratoire d'Ecologie AlpineUniversité Grenoble Alpes – CNRS – Université Savoie Mont‐BlancGrenobleFrance
| | - Jin‐Sheng He
- Department of Ecology, College of Urban and Environmental SciencesPeking UniversityBeijingChina
| | - Jeremiah A. Henning
- The Rocky Mountain Biological LaboratoryCrested ButteColoradoUSA,Department of BiologyUniversity of South AlabamaMobileAlabamaUSA
| | - Mark Hovenden
- Biological Sciences, School of Natural SciencesUniversity of TasmaniaHobartTasmaniaAustralia
| | - Toke T. Thomas Høye
- Department of Ecoscience and Arctic Research CentreAarhus UniversityAarhus CDenmark
| | - Xin Jing
- Natural History Museum of DenmarkUniversity of CopenhagenCopenhagenDenmark,State Key Laboratory of Grassland Agro‐Ecosystems, and College of Pastoral Agriculture Science and TechnologyLanzhou UniversityLanzhouGansuChina
| | - Sandra Lavorel
- Laboratoire d'Ecologie AlpineUniversité Grenoble Alpes – CNRS – Université Savoie Mont‐BlancGrenobleFrance
| | - Jennie R. McLaren
- Department of Biological SciencesUniversity of Texas at El PasoEl PasoTexasUSA
| | - Daniel B. Metcalfe
- Department of Ecology and Environmental ScienceUmeå UniversityUmeåSweden
| | | | - Marie Louise Nielsen
- Department of Ecoscience and Arctic Research CentreAarhus UniversityAarhus CDenmark
| | - Christian Rixen
- Mountain Ecosystems GroupWSL Institute for Snow and Avalanche Research SLFDavos DorfSwitzerland
| | - Quentin D. Read
- The Rocky Mountain Biological LaboratoryCrested ButteColoradoUSA,National Socio‐Environmental Synthesis CenterAnnapolisMarylandUSA
| | - Kenna E. Rewcastle
- Rubenstein School of Environment and Natural ResourcesUniversity of VermontBurlingtonVermontUSA
| | - Mariano Rodriguez‐Cabal
- Rubenstein School of Environment and Natural ResourcesUniversity of VermontBurlingtonVermontUSA,Grupo de Ecología de Invasiones, INIBIOMA, CONICETUniversidad Nacional del ComahueSan Carlos de BarilocheArgentina
| | - David A. Wardle
- Asian School of the EnvironmentNanyang Technological UniversitySingaporeSingapore
| | - Sonja Wipf
- Department of BiologyUniversity of OklahomaNormanOklahomaUSA,Department of Research and MonitoringChastè Planta‐WildenbergZernezSwitzerland
| | - Nathan J. Sanders
- Ecology and Evolutionary Biology DepartmentUniversity of MichiganAnn ArborMichiganUSA,The Rocky Mountain Biological LaboratoryCrested ButteColoradoUSA,Natural History Museum of DenmarkUniversity of CopenhagenCopenhagenDenmark
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Santos JM, Capinha C, Rocha J, Sousa CA. The current and future distribution of the yellow fever mosquito (Aedes aegypti) on Madeira Island. PLoS Negl Trop Dis 2022; 16:e0010715. [PMID: 36094951 PMCID: PMC9499243 DOI: 10.1371/journal.pntd.0010715] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 09/22/2022] [Accepted: 08/02/2022] [Indexed: 12/02/2022] Open
Abstract
The Aedes aegypti mosquito is the main vector for several diseases of global importance, such as dengue and yellow fever. This species was first identified on Madeira Island in 2005, and between 2012 and 2013 was responsible for an outbreak of dengue that affected several thousand people. However, the potential distribution of the species on the island remains poorly investigated. Here we assess the suitability of current and future climatic conditions to the species on the island and complement this assessment with estimates of the suitability of land use and human settlement conditions. We used four modelling algorithms (boosted regression trees, generalized additive models, generalized linear models and random forest) and data on the distribution of the species worldwide and across the island. For both climatic and non-climatic factors, suitability estimates predicted the current distribution of the species with good accuracy (mean area under the Receiver Operating Characteristic curve = 0.88 ±0.06, mean true skill statistic = 0.72 ±0.1). Minimum temperature of coldest month was the most influential climatic predictor, while human population density, residential housing density and public spaces were the most influential predictors describing land use and human settlement conditions. Suitable areas under current climates are predicted to occur mainly in the warmer and densely inhabited coastal areas of the southern part of the island, where the species is already established. By mid-century (2041–2060), the extent of climatically suitable areas is expected to increase, mainly towards higher altitudes and in the eastern part of the island. Our work shows that ongoing efforts to monitor and prevent the spread of Ae. aegypti on Madeira Island will have to increasingly consider the effects of climate change. The Aedes aegypti mosquito is an invasive species on Madeira Island and recently responsible for a dengue outbreak that affected more than 2000 people. To help control the activity of this mosquito, the local health authorities have an entomological surveillance program in place throughout the island. However, the full extent of the areas that can be colonized by this species remains unknown. We estimate the current and future potential distribution of Ae. aegypti on Madeira Island accounting for climatic, land use and human settlement conditions. Our results suggest that suitable conditions are predominantly distributed along the southern coast of the island. However, as climate change progresses, climatically suitable areas are expected to increase, particularly at mid-altitudes and in eastern part of the island. Minimum temperature of the coldest month was the most influential predictor variable in climatic suitability models, while human population density, housing density and public spaces were the most influential in models of land use and human settlement suitability. Our work provides valuable insight on the potential distribution of Ae. aegypti on Madeira Island, which can be used to inform ongoing and future monitoring and prevention initiatives.
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Affiliation(s)
- José Maurício Santos
- Centre for Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Lisbon, Portugal
- Associated Laboratory TERRA, Lisbon, Portugal
- * E-mail: (JMS); (CC)
| | - César Capinha
- Centre for Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Lisbon, Portugal
- Associated Laboratory TERRA, Lisbon, Portugal
- * E-mail: (JMS); (CC)
| | - Jorge Rocha
- Centre for Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Lisbon, Portugal
| | - Carla Alexandra Sousa
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
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49
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Wu X, Wang M, Li X, Yan Y, Dai M, Xie W, Zhou X, Zhang D, Wen Y. Response of distribution patterns of two closely related species in Taxus genus to climate change since last inter-glacial. Ecol Evol 2022; 12:e9302. [PMID: 36177121 PMCID: PMC9475124 DOI: 10.1002/ece3.9302] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 07/05/2022] [Accepted: 08/26/2022] [Indexed: 02/02/2023] Open
Abstract
Climate change affects the species spatio-temporal distribution deeply. However, how climate affects the spatio-temporal distribution pattern of related species on the large scale remains largely unclear. Here, we selected two closely related species in Taxus genus Taxus chinensis and Taxus mairei to explore their distribution pattern. Four environmental variables were employed to simulate the distribution patterns using the optimized Maxent model. The results showed that the highly suitable area of T. chinensis and T. mairei in current period was 1.616 × 105 km2 and 3.093 × 105 km2, respectively. The distribution area of T. chinensis was smaller than that of T. mairei in different periods. Comparison of different periods shown that the distribution area of the two species was almost in stasis from LIG to the future periods. Temperature and precipitation were the main climate factors that determined the potential distribution of the two species. The centroids of T. chinensis and T. mairei were in Sichuan and Hunan provinces in current period, respectively. In the future, the centroid migration direction of the two species would shift towards northeast. Our results revealed that the average elevation distribution of T. chinensis was higher than that of T. mairei. This study sheds new insights into the habitat preference and limiting environment factors of the two related species and provides a valuable reference for the conservation of these two threatened species.
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Affiliation(s)
- Xingtong Wu
- Central South University of Forestry and Technology Hunan China
| | - Minqiu Wang
- Central South University of Forestry and Technology Hunan China
| | - Xinyu Li
- Central South University of Forestry and Technology Hunan China
| | - Yadan Yan
- Central South University of Forestry and Technology Hunan China
| | - Minjun Dai
- Central South University of Forestry and Technology Hunan China.,University of Georgia Athens Georgia USA
| | - Wanyu Xie
- Central South University of Forestry and Technology Hunan China
| | - Xiaofen Zhou
- Central South University of Forestry and Technology Hunan China
| | | | - Yafeng Wen
- Central South University of Forestry and Technology Hunan China
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50
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Abdulwahab UA, Hammill E, Hawkins CP. Choice of climate data affects the performance and interpretation of species distribution models. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2022.110042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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