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Ferreira LC, Jenner C, Jenner M, Udyawer V, Radford B, Davenport A, Moller L, Andrews-Goff V, Double M, Thums M. Predicting suitable habitats for foraging and migration in Eastern Indian Ocean pygmy blue whales from satellite tracking data. MOVEMENT ECOLOGY 2024; 12:42. [PMID: 38845039 PMCID: PMC11157879 DOI: 10.1186/s40462-024-00481-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 05/21/2024] [Indexed: 06/09/2024]
Abstract
BACKGROUND Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species. METHODS We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia. RESULTS Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence. CONCLUSIONS Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.
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Affiliation(s)
- Luciana C Ferreira
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia.
| | - Curt Jenner
- Centre for Whale Research (WA) Inc., Fremantle, WA, Australia
| | | | - Vinay Udyawer
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
| | - Ben Radford
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
| | - Andrew Davenport
- Centre for Whale Research (WA) Inc., Fremantle, WA, Australia
- Centre for Marine Science and Technology, Curtin University, Bentley, WA, Australia
| | - Luciana Moller
- Cetacean Ecology, Behaviour and Evolution Lab, College of Science and Engineering, Flinders University, Bedford Park, SA, Australia
| | - Virginia Andrews-Goff
- Australian Antarctic Division, Department of Climate Change, Energy, the Environment and Water, Kingston, TAS, Australia
| | - Mike Double
- Australian Antarctic Division, Department of Climate Change, Energy, the Environment and Water, Kingston, TAS, Australia
| | - Michele Thums
- Australian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
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Sousa LM, Correia LL, Alexandre RJR, Pena SA, Vieira TB. Conservation units alone are insufficient to protect Brazilian Amazonian chelonians. Sci Rep 2024; 14:10827. [PMID: 38734762 PMCID: PMC11088686 DOI: 10.1038/s41598-024-61722-y] [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: 12/09/2023] [Accepted: 05/08/2024] [Indexed: 05/13/2024] Open
Abstract
The creation of protected areas (PAs) is not always based on science; consequently, some aquatic species may not receive the same level of protection as terrestrial ones. The objective of this study was to identify priority areas for the conservation of chelonians in the Brazilian Amazon basin and assess the contribution of PAs, distinguishing between Full Protection Areas, Sustainable Use Areas, and Indigenous Lands for group protection. The entire species modeling procedure was carried out using Species Distribution Models. Location records were obtained from platforms such as SpeciesLink, GBIF, the Hydroatlas database, and WorldClim for bioclimatic variables adjusted with algorithms like Maximum Entropy, Random Forest, Support Vector Machine, and Gaussian-Bayesian. Indigenous lands cover more than 50% of the distribution areas of chelonian species in the Brazilian Amazon. Protected areas with higher conservation importance (Full Protection Areas and Sustainable Use Areas) hold less than 15% of the combined species distribution. Researchers face significant challenges when making decisions with models, especially in conservation efforts involving diverse taxa that differ significantly from one another within a group of individuals.
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Affiliation(s)
- Loyriane Moura Sousa
- Programa de Pós-Graduação em Zoologia, Universidade Federal do Pará, Campus de Belém, Rua Augusto Corrêa, No 01, Guamá, 66075-110, Brazil
| | - Letícia Lima Correia
- Programa de Pós-Graduação em Ecologia, Universidade Federal do Pará, Campus de Belém, Rua Augusto Corrêa, No 01, Guamá, 66075-110, Brazil.
- Laboratório de Ecologia, Faculdade Federal do Pará, Campus de Altamira, Rua Coronel José Porfirio, No 030, Altamira, PA, Brazil.
| | - Rafaela Jemely Rodrigues Alexandre
- Programa de Pós-Graduação em Zoologia, Universidade Federal do Pará, Campus de Belém, Rua Augusto Corrêa, No 01, Guamá, 66075-110, Brazil
| | - Simone Almeida Pena
- Programa de Pós-Graduação em Ecologia, Universidade Federal do Pará, Campus de Belém, Rua Augusto Corrêa, No 01, Guamá, 66075-110, Brazil
| | - Thiago Bernardi Vieira
- Programa de Pós-Graduação em Zoologia, Universidade Federal do Pará, Campus de Belém, Rua Augusto Corrêa, No 01, Guamá, 66075-110, Brazil
- Programa de Pós-Graduação em Ecologia, Universidade Federal do Pará, Campus de Belém, Rua Augusto Corrêa, No 01, Guamá, 66075-110, Brazil
- Laboratório de Ecologia, Faculdade Federal do Pará, Campus de Altamira, Rua Coronel José Porfirio, No 030, Altamira, PA, Brazil
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Ninsin KD, Souza PGC, Amaro GC, Aidoo OF, Barry EJDV, da Silva RS, Osei-Owusu J, Dofuor AK, Ablormeti FK, Heve WK, Edusei G, Agboyi LK, Beseh P, Boafo HA, Borgemeister C, Sétamou M. Risk of spread of the Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) in Ghana. BULLETIN OF ENTOMOLOGICAL RESEARCH 2024:1-20. [PMID: 38699867 DOI: 10.1017/s0007485324000105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The impact of invasive species on biodiversity, food security and economy is increasingly noticeable in various regions of the globe as a consequence of climate change. Yet, there is limited research on how climate change affects the distribution of the invasive Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera:Liviidae) in Ghana. Using maxnet package to fit the Maxent model in R software, we answered the following questions; (i) what are the main drivers for D. citri distribution, (ii) what are the D. citri-specific habitat requirements and (iii) how well do the risk maps fit with what we know to be correctly based on the available evidence?. We found that temperature seasonality (Bio04), mean temperature of warmest quarter (Bio10), precipitation of driest quarter (Bio17), moderate resolution imaging spectroradiometer land cover and precipitation seasonality (Bio15), were the most important drivers of D. citri distribution. The results follow the known distribution records of the pest with potential expansion of habitat suitability in the future. Because many invasive species, including D. citri, can adapt to the changing climates, our findings can serve as a guide for surveillance, tracking and prevention of D. citri spread in Ghana.
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Affiliation(s)
- Kodwo Dadzie Ninsin
- Department of Biological Sciences, School of Natural and Environmental Sciences, University of Environment and Sustainable Development, PMB, Somanya, E/R, Ghana
| | - Philipe Guilherme Corcino Souza
- Department of Agronomy, Instituto Federal de Ciência e Tecnologia do Triângulo Mineiro (IFTM Campus Uberlândia), Uberlândia, MG 38400-970, Brazil
| | | | - Owusu Fordjour Aidoo
- Department of Biological Sciences, School of Natural and Environmental Sciences, University of Environment and Sustainable Development, PMB, Somanya, E/R, Ghana
- Department of Entomology, College of Agricultural, Human, and Natural Resource Sciences, Washington State University, Pullman, WA 99164, USA
| | | | - Ricardo Siqueira da Silva
- Department of Agronomy, Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM), Diamantina, MG 39100-000, Brazil
| | - Jonathan Osei-Owusu
- Department of Physical and Mathematical Sciences, School of Natural and Environmental Sciences, University of Environment and Sustainable Development, PMB, Somanya, E/R, Ghana
| | - Aboagye Kwarteng Dofuor
- Department of Biological Sciences, School of Natural and Environmental Sciences, University of Environment and Sustainable Development, PMB, Somanya, E/R, Ghana
| | - Fred Kormla Ablormeti
- Council for Scientific and Industrial Research (CSIR), P. O. Box 245, Sekondi, W/R, Ghana
| | - William K Heve
- Department of Biological Sciences, School of Natural and Environmental Sciences, University of Environment and Sustainable Development, PMB, Somanya, E/R, Ghana
| | - George Edusei
- Department of Physical and Mathematical Sciences, School of Natural and Environmental Sciences, University of Environment and Sustainable Development, PMB, Somanya, E/R, Ghana
| | - Lakpo Koku Agboyi
- Centre for Agriculture and Biosciences International (CABI), CSIR Campus, No. 6 Agostino Neto Road, Airport Residential Area, P. O. Box CT 8630, Cantonments, Ghana
| | - Patrick Beseh
- Plant Protection and Regulatory Services Directorate. P. O. Box M37, Accra, Ghana
| | - Hettie Arwoh Boafo
- Centre for Agriculture and Biosciences International (CABI), CSIR Campus, No. 6 Agostino Neto Road, Airport Residential Area, P. O. Box CT 8630, Cantonments, Ghana
| | - Christian Borgemeister
- Centre for Development Research (ZEF), University of Bonn, Genscherallee 3, 53113 Bonn, Germany
| | - Mamoudou Sétamou
- Citrus Center, Texas A & M University-Kingsville, 312 N. International Blvd., Weslaco, TX 78599, USA
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Gonzalez‐Aragon D, Rivadeneira MM, Lara C, Torres FI, Vásquez JA, Broitman BR. A species distribution model of the giant kelp Macrocystis pyrifera: Worldwide changes and a focus on the Southeast Pacific. Ecol Evol 2024; 14:e10901. [PMID: 38435006 PMCID: PMC10905252 DOI: 10.1002/ece3.10901] [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: 04/21/2023] [Revised: 11/29/2023] [Accepted: 12/14/2023] [Indexed: 03/05/2024] Open
Abstract
Worldwide climate-driven shifts in the distribution of species is of special concern when it involves habitat-forming species. In the coastal environment, large Laminarian algae-kelps-form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat-forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios with a focus on the Southeast Pacific shores. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the single most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the Southeast Pacific, we observed an upper range contraction of -17.08° S of latitude for 2090-2100 under the RCP8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to -27.83° S in Chile. Along the area of Northern Chile where a complete habitat loss is predicted by our model, natural stands are under heavy exploitation. The loss of habitat suitability will take place worldwide: Significant impacts on marine biodiversity and ecosystem functioning are likely. Furthermore, changes in habitat suitability are a harbinger of massive impacts in the socio-ecological systems of the Southeast Pacific.
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Affiliation(s)
- Daniel Gonzalez‐Aragon
- Doctorado en Ciencias, mención en Biodiversidad y Biorecursos, Facultad de CienciasUniversidad Católica de la Santísima ConcepciónConcepcionChile
- Instituto Milenio en Socio‐Ecología Costera (SECOS)SantiagoChile
- Núcleo Milenio UPWELL
| | - Marcelo M. Rivadeneira
- Centro de Estudios Avanzados en Zonas ÁridasCoquimboChile
- Departamento de Biología Marina, Facultad de Ciencias del MarUniversidad Católica del NorteCoquimboChile
| | - Carlos Lara
- Departamento de Ecología, Facultad de CienciasUniversidad Católica de la Santísima ConcepciónConcepcionChile
- Centro de Investigación en Recursos Naturales y SustentabilidadUniversidad Bernardo O'HigginsSantiagoChile
| | - Felipe I. Torres
- Doctorado en Ciencias, mención en Biodiversidad y Biorecursos, Facultad de CienciasUniversidad Católica de la Santísima ConcepciónConcepcionChile
- Instituto Milenio en Socio‐Ecología Costera (SECOS)SantiagoChile
- Data Observatory Foundation, ANID Technology Center No. DO210001SantiagoChile
| | - Julio A. Vásquez
- Instituto Milenio en Socio‐Ecología Costera (SECOS)SantiagoChile
- Departamento de Biología Marina, Facultad de Ciencias del MarUniversidad Católica del NorteCoquimboChile
- Centro de Investigación y Desarrollo Tecnológico en Algas y Otros Recursos Biológicos (CIDTA)CoquimboChile
| | - Bernardo R. Broitman
- Instituto Milenio en Socio‐Ecología Costera (SECOS)SantiagoChile
- Núcleo Milenio UPWELL
- Facultad de Artes LiberalesUniversidad Adolfo IbañezViña Del MarChile
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Singh AP, De K, Uniyal VP, Sathyakumar S. Unveiling of climate change-driven decline of suitable habitat for Himalayan bumblebees. Sci Rep 2024; 14:4983. [PMID: 38424143 PMCID: PMC10904386 DOI: 10.1038/s41598-024-52340-9] [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: 04/16/2023] [Accepted: 01/17/2024] [Indexed: 03/02/2024] Open
Abstract
Insect pollinators, especially bumblebees are rapidly declining from their natural habitat in the mountain and temperate regions of the world due to climate change and other anthropogenic activities. We still lack reliable information about the current and future habitat conditions of bumblebees in the Himalaya. In this study, we used the maximum entropy algorithm for SDM to look at current and future (in 2050 and 2070) suitable habitats for bumblebees in the Himalaya. We found that the habitat conditions in the Himalayan mountain range do not have a very promising future as suitable habitat for most species will decrease over the next 50 years. By 2050, less than 10% of the Himalayan area will remain a suitable habitat for about 72% of species, and by 2070 this number will be raised to 75%. During this time period, the existing suitable habitat of bumblebees will be declined but some species will find new suitable habitat which clearly indicates possibility of habitat range shift by Himalayan bumblebees. Overall, about 15% of the Himalayan region is currently highly suitable for bumblebees, which should be considered as priority areas for the conservation of these pollinators. Since suitable habitats for bumblebees lie between several countries, nations that share international borders in the Himalayan region should have international agreements for comprehensive pollinator diversity conservation to protect these indispensable ecosystem service providers.
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Affiliation(s)
- Amar Paul Singh
- Wildlife Institute of India, Chandrabani, Dehradun, Uttarakhand, 248001, India.
| | - Kritish De
- Wildlife Institute of India, Chandrabani, Dehradun, Uttarakhand, 248001, India
- Department of Life Sciences, Sri Sathya Sai University for Human Excellence, Navanihal, Okali Post, Kamalapur, Kalaburagi, Karnataka, 585313, India
| | - Virendra Prasad Uniyal
- Wildlife Institute of India, Chandrabani, Dehradun, Uttarakhand, 248001, India
- Graphic Era (Deemed to be) University, Bell Road, Clement Town, Dehradun, Uttarakhand, 248002, India
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Zimmer SN, Holsinger KW, Dawson CA. A field-validated ensemble species distribution model of Eriogonum pelinophilum, an endangered subshrub in Colorado, USA. Ecol Evol 2023; 13:e10816. [PMID: 38107426 PMCID: PMC10721943 DOI: 10.1002/ece3.10816] [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: 07/20/2023] [Revised: 10/10/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023] Open
Abstract
Understanding the suitable habitat of endangered species is crucial for agencies such as the Bureau of Land Management to plan management and conservation. However, few species distribution models are directly validated, potentially limiting their application in management. In preparation for a Species Status Assessment of clay-loving wild buckwheat (Eriogonum pelinophilum), an endangered subshrub found in southwest Colorado, we ran a series of species distribution models to estimate the species' potential occupied habitat and validated these models in the field. A 1-meter resolution digital elevation model derived from LiDAR and a high-resolution geology mapping helped identify biologically relevant characteristics of the species' habitat. We employed a weighted ensemble model based on two Random Forest and one Boosted Regression Tree model, and discrimination performance of the ensemble model was high (AUC-PR = 0.793). We then conducted a systematic field survey of model habitat suitability predictions, during which we discovered 55 new subpopulations of the species and demonstrated that new species observations were strongly associated with model predictions (p < .0001, Cliff's delta = 0.575). We further refined our original models by incorporating the additional species occurrences collected in the field survey, a new explanatory variable, and a more diverse set of models. These iterative changes marginally improved performance of the ensemble model (AUC-PR = 0.825). Direct validation of species distribution models is extremely rare, and our field survey provides strong validation of our model results. This helps increase confidence to utilize predictions in planning. The final model predictions greatly improve the Bureau of Land Management's understanding of the species' habitat and increase our ability to consider potential habitat in planning land use activities such as road development and travel management.
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Affiliation(s)
- Scott N. Zimmer
- Uncompahgre Field OfficeBureau of Land ManagementMontroseColoradoUSA
- Fire Sciences LaboratoryRocky Mountain Research Station, U.S. Forest ServiceMissoulaMontanaUSA
| | | | - Carol A. Dawson
- Colorado State OfficeBureau of Land ManagementLakewoodColoradoUSA
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7
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Häkkinen H, Hodgson D, Early R. Global terrestrial invasions: Where naturalised birds, mammals, and plants might spread next and what affects this process. PLoS Biol 2023; 21:e3002361. [PMID: 37963110 PMCID: PMC10645288 DOI: 10.1371/journal.pbio.3002361] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 10/04/2023] [Indexed: 11/16/2023] Open
Abstract
More species live outside their native range than at any point in human history. Yet, there is little understanding of the geographic regions that will be threatened if these species continue to spread, nor of whether they will spread. We predict the world's terrestrial regions to which 833 naturalised plants, birds, and mammals are most imminently likely to spread, and investigate what factors have hastened or slowed their spread to date. There is huge potential for further spread of naturalised birds in North America, mammals in Eastern Europe, and plants in North America, Eastern Europe, and Australia. Introduction history, dispersal, and the spatial distribution of suitable areas are more important predictors of species spread than traits corresponding to habitat usage or biotic interactions. Natural dispersal has driven spread in birds more than in plants. Whether these taxa continue to spread more widely depends partially on connectivity of suitable environments. Plants show the clearest invasion lag, and the putative importance of human transportation indicates opportunities to slow their spread. Despite strong predictive effects, questions remain, particularly why so many birds in North America do not occupy climatically suitable areas close to their existing ranges.
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Affiliation(s)
- Henry Häkkinen
- Centre for Ecology and Conservation, Faculty of Environment, Science and Economy, University of Exeter, Penryn, United Kingdom
| | - Dave Hodgson
- Centre for Ecology and Conservation, Faculty of Environment, Science and Economy, University of Exeter, Penryn, United Kingdom
| | - Regan Early
- Centre for Ecology and Conservation, Faculty of Environment, Science and Economy, University of Exeter, Penryn, United Kingdom
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8
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Gaier AG, Resasco J. Does adding community science observations to museum records improve distribution modeling of a rare endemic plant? Ecosphere 2023. [DOI: 10.1002/ecs2.4419] [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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Pio Caetano Machado L, de Oliveira Caetano GH, Lacerda Cavalcante VH, B. Miles D, Rinaldi Colli G. Climate change shrinks environmental suitability for a viviparous
N
eotropical skink. CONSERVATION SCIENCE AND PRACTICE 2023. [DOI: 10.1111/csp2.12895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023] Open
Affiliation(s)
| | - Gabriel Henrique de Oliveira Caetano
- Jacob Blaustein Center for Scientific Cooperation The Jacob Blaustein Institutes for Desert Research, Ben‐Gurion University of the Negev Midreshet Ben‐Gurion Israel
| | | | - Donald B. Miles
- Department of Biological Sciences and Ohio Center for Ecological and Evolutionary Studies Ohio University Athens Ohio USA
| | - Guarino Rinaldi Colli
- University of Brasília, Institute of Biological Sciences Brasília Distrito Federal Brazil
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Dawood F, Flemming A, van Vuuren J. Modelling the efficacy of a threshold-triggered control strategy for the invasive tree species Prosopis. ECOL INFORM 2022. [DOI: 10.1016/j.ecoinf.2022.101793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Koirala S, Baral S, Garber PA, Basnet H, Katuwal HB, Gurung S, Rai D, Gaire R, Sharma B, Pun T, Li M. Identifying the environmental and anthropogenic causes, distribution, and intensity of human rhesus macaque conflict in Nepal. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 316:115276. [PMID: 35576709 DOI: 10.1016/j.jenvman.2022.115276] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/04/2022] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
Reducing conflict between humans and wildlife is considered a top conservation priority. However, increasingly human-induced disturbances across natural landscapes have escalated encounters between humans and wildlife. In Nepal, forests have been destroyed, fragmented, and developed for human settlements, agricultural production, and urban centers for decades. As a result, human-wildlife conflict, in the form of crop-raiding, livestock predation, and injuries to humans and wildlife, is common throughout the country. In particular, crop-raiding by macaques is an increasingly common form of human-wildlife conflict. Rhesus macaques (Macaca mulatta) have been identified as a top ten crop-raiding wildlife species in Nepal. In order to better understand the nationwide distribution and intensity of human-rhesus macaque conflict (HRMC), we conducted an extensive literature review of reported incidences of HRMC during the period 2000 to 2021 in Nepal. We also created an online survey to obtain nationwide data on the location and severity of HRMC, and modeled the set of ecological factors that affect habitat suitability for rhesus macaques. An ensemble of three different species distribution model (SDM) algorithms were used to analyze these data. We found that almost 44% of Nepal's land area contains suitable habitat for rhesus macaques, with less than 8% of all suitable habitat located in protected national parks. As humans continue to alter and fragment natural landscapes, HRMC in Nepal has intensified. At present, nearly 15% of the country's land area in which human settlements are permitted, is characterized by moderate or high rates of HRMC. We argue that prioritizing programs of forest restoration, strategic management plans designed to connect isolated forest fragments with high rhesus macaque population densities, creating government programs that compensate farmers for income lost due to crop-raiding, and educational outreach that informs local villagers of the importance of conservation and protecting biodiversity, offer the most effective solutions to reduce HRMC in Nepal.
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Affiliation(s)
- Sabina Koirala
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Chaoyang District, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Suraj Baral
- Amrit Science Campus, Tribhuvan University, Kathmandu, Nepal.
| | - Paul A Garber
- Department of Anthropology, And Program in Ecology, Evolution, and Conservation Biology, University of Illinois, Urbana, IL, 61801, USA.
| | - Hari Basnet
- Nepalese Ornithological Union, Kathmandu, Nepal.
| | - Hem Bahadur Katuwal
- Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, 666303, China.
| | | | - Devi Rai
- Golden Gate International College, Kathmandu, Nepal.
| | - Raju Gaire
- University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, 666303, China.
| | - Bishal Sharma
- Environment Protection and Study Center (ENPROSC), Kathmandu, Nepal.
| | - Tejab Pun
- Shree Surya Chandra Secondary School, Kalimatigadi, Sanfebagar 1, Achham, Nepal.
| | - Ming Li
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Chaoyang District, Beijing, 100101, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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Pimenta M, Andrade AFAD, Fernandes FHS, Amboni MPDM, Almeida RS, Soares AHSDB, Falcon GB, Raíces DSL, De Marco Júnior P. One size does not fit all: Priority areas for real world problems. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2022.110013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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13
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Muylaert RL, Kingston T, Luo J, Vancine MH, Galli N, Carlson CJ, John RS, Rulli MC, Hayman DTS. Present and future distribution of bat hosts of sarbecoviruses: implications for conservation and public health. Proc Biol Sci 2022; 289:20220397. [PMID: 35611534 PMCID: PMC9130791 DOI: 10.1098/rspb.2022.0397] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Global changes in response to human encroachment into natural habitats and carbon emissions are driving the biodiversity extinction crisis and increasing disease emergence risk. Host distributions are one critical component to identify areas at risk of viral spillover, and bats act as reservoirs of diverse viruses. We developed a reproducible ecological niche modelling pipeline for bat hosts of SARS-like viruses (subgenus Sarbecovirus), given that several closely related viruses have been discovered and sarbecovirus-host interactions have gained attention since SARS-CoV-2 emergence. We assessed sampling biases and modelled current distributions of bats based on climate and landscape relationships and project future scenarios for host hotspots. The most important predictors of species distributions were temperature seasonality and cave availability. We identified concentrated host hotspots in Myanmar and projected range contractions for most species by 2100. Our projections indicate hotspots will shift east in Southeast Asia in locations greater than 2°C hotter in a fossil-fuelled development future. Hotspot shifts have implications for conservation and public health, as loss of population connectivity can lead to local extinctions, and remaining hotspots may concentrate near human populations.
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Affiliation(s)
| | | | - Jinhong Luo
- Central China Normal University, Wuhan, People's Republic of China
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14
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Duarte G, Branco P, Haidvogl G, Ferreira MT, Pont D, Segurado P. iPODfish - A new method to infer the historical occurrence of diadromous fish species along river networks. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 812:152437. [PMID: 34942248 DOI: 10.1016/j.scitotenv.2021.152437] [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: 08/13/2021] [Revised: 11/29/2021] [Accepted: 12/11/2021] [Indexed: 06/14/2023]
Abstract
Available information on diadromous fish species historical occurrences is generally biased and incomplete across species distribution range and spatial scales. This work aims to establish a new methodological framework (iPODfish - Inferring Past Occurrences of Diadromous Fish) to obtain a more complete representation of the historical occurrences of diadromous fish species over their full distribution range. The iPODfish is based on assumptions, rules and thresholds derived from the interplay between freshwater network features, diadromous fish species ecology and known historical occurrence. These are used to establish historical pseudo-occurrences at the segment scale, i.e., locations where the species was most likely to be present or absent. The methodology is expressed by a tree-like representation of a stepwise, information supported, decision process. It has five steps (separating main river segments from tributary segments; accounting for segments specificities; imposing the relative distance threshold; imposing the Strahler value threshold, and; establishing the sub-basin Strahler threshold), divides into two moments of application (main river followed by the tributaries) and establishes presences, pseudo-presences and pseudo-absences. The iPODfish can deal with multiple information sources, cope with data bias and provide a reliable consistent historical occurrence output at the segment scale for the known historical geographical range of the species. Despite its inference nature, iPODfish is still a conservative procedure leading to ecologically coherent outputs that may be applied to any diadromous fish species (with a relevant amount of historical data available) in any river network throughout the globe because the concepts and definitions used are general ecological features of diadromous and freshwater networks. The method outputs are applicable in biogeographical and/or macroecological studies using historical data and may prove useful to the management and conservation of diadromous fish species.
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Affiliation(s)
- Gonçalo Duarte
- Forest Research Centre, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal.
| | - Paulo Branco
- Forest Research Centre, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal
| | - Gertrud Haidvogl
- Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
| | - Maria Teresa Ferreira
- Forest Research Centre, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal
| | - Didier Pont
- Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria
| | - Pedro Segurado
- Forest Research Centre, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal
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15
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Early R, Rwomushana I, Chipabika G, Day R. Comparing, evaluating and combining statistical species distribution models and CLIMEX to forecast the distributions of emerging crop pests. PEST MANAGEMENT SCIENCE 2022; 78:671-683. [PMID: 34647405 DOI: 10.1002/ps.6677] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/14/2021] [Accepted: 10/13/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Forecasting the spread of emerging pests is widely requested by pest management agencies in order to prioritise and target efforts. Two widely used approaches are statistical Species Distribution Models (SDMs) and CLIMEX, which uses ecophysiological parameters. Each have strengths and weaknesses. SDMs can incorporate almost any environmental condition and their accuracy can be formally evaluated to inform managers. However, accuracy is affected by data availability and can be limited for emerging pests, and SDMs usually predict year-round distributions, not seasonal outbreaks. CLIMEX can formally incorporate expert ecophysiological knowledge and predicts seasonal outbreaks. However, the methods for formal evaluation are limited and rarely applied. We argue that both approaches can be informative and complementary, but we need tools to integrate and evaluate their accuracy. Here we develop such an approach, and test it by forecasting the potential global range of the tomato pest Tuta absoluta. RESULTS The accuracy of previously developed CLIMEX and new statistical SDMs were comparable on average, but the best statistical SDM techniques and environmental data substantially outperformed CLIMEX. The ensembled approach changes expectations of T. absoluta's spread. The pest's environmental tolerances and potential range in Africa, the Arabian Peninsula, Central Asia and Australia will be larger than previous estimates. CONCLUSION We recommend that CLIMEX be considered one of a suite of SDM techniques and thus evaluated formally. CLIMEX and statistical SDMs should be compared and ensembled if possible. We provide code that can be used to do so when employing the biomod suite of SDM techniques. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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Affiliation(s)
- Regan Early
- Centre for Ecology and Conservation, Exeter University, Penryn, UK
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16
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Combining Citizen Science Data and Satellite Descriptors of Ecosystem Functioning to Monitor the Abundance of a Migratory Bird during the Non-Breeding Season. REMOTE SENSING 2022. [DOI: 10.3390/rs14030463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Migratory birds are particularly exposed to habitat changes in their breeding and non-breeding grounds. Remote sensing technologies offer an excellent opportunity to monitor species’ habitats from space at unprecedented spatiotemporal scales. We analyzed if remotely sensed ecosystem functioning attributes (EFAs) adequately predict the spatiotemporal variation of the Woodcock’s (Scolopax rusticola) relative abundance in southwest Europe, during autumn migration and wintering periods. We used data gathered from Woodcock monitoring through citizen science (N = 355,654 hunting trips) between 2009 and 2018. We computed a comprehensive set of EFAs on a weekly basis from three MODIS satellite products: enhanced vegetation index (EVI), tasseled cap transformation (TCT), and land surface temperature (LST). We developed generalized linear mixed models to explore the predictive power of EFAs on Woodcock’s abundance during the non-breeding season. Results showed that Woodcock abundance is correlated with spatiotemporal dynamics in primary productivity (measured through the EVI), water cycle dynamics (wetness component of TCT), and surface energy balance (LST) in both periods. Our findings underline the potential of combining citizen science and remote sensing data to monitor migratory birds throughout their life cycles—an issue of critical importance to ensure adequate habitat management in the non-breeding areas.
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17
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Projecting the remaining habitat for the western spadefoot (Spea hammondii) in heavily urbanized southern California. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2021.e01944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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18
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Landscape-scale drivers of endangered Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis) presence using an ensemble modeling approach. Ecol Modell 2021. [DOI: 10.1016/j.ecolmodel.2021.109774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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19
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Tagliari MM, Danthu P, Leong Pock Tsy JM, Cornu C, Lenoir J, Carvalho-Rocha V, Vieilledent G. Not all species will migrate poleward as the climate warms: The case of the seven baobab species in Madagascar. GLOBAL CHANGE BIOLOGY 2021; 27:6071-6085. [PMID: 34418236 DOI: 10.1111/gcb.15859] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 06/25/2021] [Accepted: 08/06/2021] [Indexed: 06/13/2023]
Abstract
It is commonly accepted that species should move toward higher elevations and latitudes to track shifting isotherms as climate warms. However, temperature might not be the only limiting factor determining species distribution. Species might move to opposite directions to track changes in other climatic variables. Here, we used an extensive occurrence data set and an ensemble modelling approach to model the climatic niche and to predict the distribution of the seven baobab species (genus Adansonia) present in Madagascar. Using climatic projections from three global circulation models, we predicted species' future distribution and extinction risk for 2055 and 2085 under two representative concentration pathways (RCPs) and two dispersal scenarios. We disentangled the role of each climatic variable in explaining species range shift looking at relative variable importance and future climatic anomalies. Four baobab species (Adansonia rubrostipa, Adansonia madagascariensis, Adansonia perrieri¸ and Adansonia suarezensis) could experience a severe range contraction in the future (>70% for year 2085 under RCP 8.5, assuming a zero-dispersal hypothesis). For three out of the four threatened species, range contraction was mainly explained by an increase in temperature seasonality, especially in the North of Madagascar, where they are currently distributed. In tropical regions, where species are commonly adapted to low seasonality, we found that temperature seasonality will generally increase. It is, thus, very likely that many species in the tropics will be forced to move equatorward to avoid an increase in temperature seasonality. Yet, several ecological (e.g., equatorial limit, or unsuitable deforested habitat) or geographical barriers (absence of lands) could prevent species to move equatorward, thus increasing the extinction risk of many tropical species, like endemic baobab species in Madagascar.
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Affiliation(s)
- Mario M Tagliari
- AMAP, Univ Montpellier, CIRAD, CNRS, INRA, IRD, Montpellier, France
- Human Ecology and Ethnobotany Lab, ECOHE, Ecology and Zoology Department, Universidade Federal de Santa Catarina, Florianópolis, Brazil
| | - Pascal Danthu
- CIRAD, UPR HortSys, Montpellier, France
- HortSys, Univ Montpellier, CIRAD, Montpellier, France
| | | | - Cyrille Cornu
- CIRAD, UMR TETIS, TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, IRSTEA, Montpellier, France
| | - Jonathan Lenoir
- Unité de Recherche "Ecologie et Dynamique des Systèmes Anthropisés" (EDYSAN, UMR 7058 CNRS), Université de Picardie Jules Verne, Amiens, France
| | - Vítor Carvalho-Rocha
- Amphibians and Reptiles Ecology Lab, LEAR, Ecology and Zoology Department, Universidade Federal de Santa Catarina, Florianópolis, Brazil
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20
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Valavi R, Guillera‐Arroita G, Lahoz‐Monfort JJ, Elith J. Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code. ECOL MONOGR 2021. [DOI: 10.1002/ecm.1486] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Roozbeh Valavi
- School of Biosciences University of Melbourne Parkville Victoria 3010 Australia
| | | | - José J. Lahoz‐Monfort
- School of Ecosystem and Forest Sciences University of Melbourne Parkville Victoria 3010 Australia
| | - Jane Elith
- School of Ecosystem and Forest Sciences University of Melbourne Parkville Victoria 3010 Australia
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21
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Gregr EJ, Haggarty DR, Davies SC, Fields C, Lessard J. Comprehensive marine substrate classification applied to Canada's Pacific shelf. PLoS One 2021; 16:e0259156. [PMID: 34714844 PMCID: PMC8555849 DOI: 10.1371/journal.pone.0259156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 10/13/2021] [Indexed: 11/22/2022] Open
Abstract
Maps of bottom type are essential to the management of marine resources and biodiversity because of their foundational role in characterizing species’ habitats. They are also urgently needed as countries work to define marine protected areas. Current approaches are time consuming, focus largely on grain size, and tend to overlook shallow waters. Our random forest classification of almost 200,000 observations of bottom type is a timely alternative, providing maps of coastal substrate at a combination of resolution and extents not previously achieved. We correlated the observations with depth, depth-derivatives, and estimates of energy to predict marine substrate at 100 m resolution for Canada’s Pacific shelf, a study area of over 135,000 km2. We built five regional models with the same data at 20 m resolution. In addition to standard tests of model fit, we used three independent data sets to test model predictions. We also tested for regional, depth, and resolution effects. We guided our analysis by asking: 1) does weighting for prevalence improve model predictions? 2) does model resolution influence model performance? And 3) is model performance influenced by depth? All our models fit the build data well with true skill statistic (TSS) scores ranging from 0.56 to 0.64. Weighting models with class prevalence improved fit and the correspondence with known spatial features. Class-based metrics showed differences across both resolutions and spatial regions, indicating non-stationarity across these spatial categories. Predictive power was lower (TSS from 0.10 to 0.36) based on independent data evaluation. Model performance was also a function of depth and resolution, illustrating the challenge of accurately representing heterogeneity. Our work shows the value of regional analyses to assessing model stationarity and how independent data evaluation and the use of error metrics can improve understanding of model performance and sampling bias.
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Affiliation(s)
- Edward J. Gregr
- SciTech Environmental Consulting, Vancouver, British Columbia, Canada
- Institute for Resources, Environment, and Sustainability, University of British Columbia, Vancouver, British Columbia, Canada
- * E-mail:
| | - Dana R. Haggarty
- Fisheries and Oceans Canada, Pacific Biological Station, Nanaimo, British Columbia, Canada
- Department of Biology, University of Victoria, Victoria, British Columbia, Canada
| | - Sarah C. Davies
- Fisheries and Oceans Canada, Pacific Biological Station, Nanaimo, British Columbia, Canada
| | - Cole Fields
- Fisheries and Oceans Canada, Institute of Ocean Sciences, Sidney, British Columbia, Canada
| | - Joanne Lessard
- Fisheries and Oceans Canada, Pacific Biological Station, Nanaimo, British Columbia, Canada
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22
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Potential distribution of piscivores across the Atlantic Forest: From bats and marsupials to large-bodied mammals under a trophic-guild viewpoint. ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2021.101357] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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23
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Long T, Tang J, Pilfold NW, Zhao X, Dong T. Predicting range shifts of Davidia involucrata Ball. under future climate change. Ecol Evol 2021; 11:12779-12789. [PMID: 34594538 PMCID: PMC8462142 DOI: 10.1002/ece3.8023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/25/2021] [Accepted: 07/30/2021] [Indexed: 12/01/2022] Open
Abstract
Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one-third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high-latitude regions. Similarly, at least one-fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.
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Affiliation(s)
- Teng Long
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education)China West Normal UniversityNanchongChina
| | - Junfeng Tang
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education)China West Normal UniversityNanchongChina
| | - Nicholas W. Pilfold
- Conservation Science and Wildlife HealthSan Diego Zoo Wildlife AllianceEscondidoCAUSA
| | - Xuzhe Zhao
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education)China West Normal UniversityNanchongChina
| | - Tingfa Dong
- Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education)China West Normal UniversityNanchongChina
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24
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Arenas-Castro S, Sillero N. Cross-scale monitoring of habitat suitability changes using satellite time series and ecological niche models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 784:147172. [PMID: 34088022 DOI: 10.1016/j.scitotenv.2021.147172] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 04/06/2021] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
One of the biggest challenges to deal with the global crisis of biodiversity loss is the lack of efficient and viable monitoring systems across scales. Unlike traditional in situ biodiversity monitoring, a usually costly and time-consuming enterprise, satellite remote sensing (SRS) data offer a technically feasible and sustainable in time solution. Here, we devise a cost-effective and upgradeable spatiotemporal framework for monitoring the species-specific habitat availability changes across scales by trend analysis of habitat suitability index (HSI) derived from ecological niche models (ENMs; Maxent) and using time series of SRS data (MODIS). The SRS-ENM framework was applied for a large suite of native species (911), from major taxonomic groups (flora (vascular plants), amphibians, reptiles, birds and mammals), and listed in the IUCN Red List at regional (Iberian Peninsula) and continental (Europe) scales. The HSI-trend analyses predict cumulative reductions in habitat suitability for Threatened and Non-Threatened species across scales for the period 2002-2016. Specifically, 19% and 66% of the total grid cells for both species' groups showed negative trends at both regional and continental scales, respectively. Results were similar when considering all IUCN threat categories. All taxa groups showed a decrease in habitat suitability, but amphibians and reptiles groups hosted the largest number of negative HSI-trends grid cells. Considering all groups together, 12% and 34% of both study areas have strong reductions in habitat quality. We conclude that our framework detects increases and decreases in species' habitat suitability regardless of the spatial scale, extent, and pixel size. Species' range predictions across space and time based on SRS time series represent a promising Earth observation tool to support traditional risk assessment protocols and anticipate the decision-making process, while serving as a cross-scale biodiversity monitoring system.
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Affiliation(s)
- Salvador Arenas-Castro
- CICGE - Centro de Investigação em Ciências Geo-Espaciais, Faculdade de Ciências, Universidade do Porto, Observatório Astronómico "Prof. Manuel de Barros", Alameda do Monte da Virgem, 4430-146 Vila Nova de Gaia, Portugal.
| | - Neftalí Sillero
- CICGE - Centro de Investigação em Ciências Geo-Espaciais, Faculdade de Ciências, Universidade do Porto, Observatório Astronómico "Prof. Manuel de Barros", Alameda do Monte da Virgem, 4430-146 Vila Nova de Gaia, Portugal.
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25
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Predicting 1-Year Mortality after Hip Fracture Surgery: An Evaluation of Multiple Machine Learning Approaches. J Pers Med 2021; 11:jpm11080727. [PMID: 34442370 PMCID: PMC8401745 DOI: 10.3390/jpm11080727] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 07/24/2021] [Accepted: 07/24/2021] [Indexed: 12/15/2022] Open
Abstract
Postoperative death within 1 year following hip fracture surgery is reported to be up to 27%. In the current study, we benchmarked the predictive precision and accuracy of the algorithms support vector machine (SVM), naïve Bayes classifier (NB), and random forest classifier (RF) against logistic regression (LR) in predicting 1-year postoperative mortality in hip fracture patients as well as assessed the relative importance of the variables included in the LR model. All adult patients who underwent primary emergency hip fracture surgery in Sweden, between 1 January 2008 and 31 December 2017 were included in the study. Patients with pathological fractures and non-operatively managed hip fractures, as well as those who died within 30 days after surgery, were excluded from the analysis. A LR model with an elastic net regularization were fitted and compared to NB, SVM, and RF. The relative importance of the variables in the LR model was then evaluated using the permutation importance. The LR model including all the variables demonstrated an acceptable predictive ability on both the training and test datasets for predicting one-year postoperative mortality (Area under the curve (AUC) = 0.74 and 0.74 respectively). NB, SVM, and RF tended to over-predict the mortality, particularly NB and SVM algorithms. In contrast, LR only over-predicted mortality when the predicted probability of mortality was larger than 0.7. The LR algorithm outperformed the other three algorithms in predicting 1-year postoperative mortality in hip fracture patients. The most important predictors of 1-year mortality were the presence of a metastatic carcinoma, American Society of Anesthesiologists(ASA) classification, sex, Charlson Comorbidity Index (CCI) ≤ 4, age, dementia, congestive heart failure, hypertension, surgery using pins/screws, and chronic kidney disease.
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26
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Cao Y, Forssten MP, Mohammad Ismail A, Borg T, Ioannidis I, Montgomery S, Mohseni S. Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients. J Pers Med 2021; 11:353. [PMID: 33924993 PMCID: PMC8146802 DOI: 10.3390/jpm11050353] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/21/2021] [Accepted: 04/23/2021] [Indexed: 12/23/2022] Open
Abstract
Hip fracture patients have a high risk of mortality after surgery, with 30-day postoperative rates as high as 10%. This study aimed to explore the predictive ability of preoperative characteristics in traumatic hip fracture patients as they relate to 30-day postoperative mortality using readily available variables in clinical practice. All adult patients who underwent primary emergency hip fracture surgery in Sweden between 2008 and 2017 were included in the analysis. Associations between the possible predictors and 30-day mortality was performed using a multivariate logistic regression (LR) model; the bidirectional stepwise method was used for variable selection. An LR model and convolutional neural network (CNN) were then fitted for prediction. The relative importance of individual predictors was evaluated using the permutation importance and Gini importance. A total of 134,915 traumatic hip fracture patients were included in the study. The CNN and LR models displayed an acceptable predictive ability for predicting 30-day postoperative mortality using a test dataset, displaying an area under the ROC curve (AUC) of as high as 0.76. The variables with the highest importance in prediction were age, sex, hypertension, dementia, American Society of Anesthesiologists (ASA) classification, and the Revised Cardiac Risk Index (RCRI). Both the CNN and LR models achieved an acceptable performance in identifying patients at risk of mortality 30 days after hip fracture surgery. The most important variables for prediction, based on the variables used in the current study are age, hypertension, dementia, sex, ASA classification, and RCRI.
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Affiliation(s)
- Yang Cao
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, 70182 Örebro, Sweden;
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institute, 17177 Stockholm, Sweden
| | - Maximilian Peter Forssten
- Department of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, Sweden; (M.P.F.); (A.M.I.); (T.B.); (I.I.)
- School of Medical Sciences, Orebro University, 70182 Orebro, Sweden;
| | - Ahmad Mohammad Ismail
- Department of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, Sweden; (M.P.F.); (A.M.I.); (T.B.); (I.I.)
- School of Medical Sciences, Orebro University, 70182 Orebro, Sweden;
| | - Tomas Borg
- Department of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, Sweden; (M.P.F.); (A.M.I.); (T.B.); (I.I.)
- School of Medical Sciences, Orebro University, 70182 Orebro, Sweden;
| | - Ioannis Ioannidis
- Department of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, Sweden; (M.P.F.); (A.M.I.); (T.B.); (I.I.)
- School of Medical Sciences, Orebro University, 70182 Orebro, Sweden;
| | - Scott Montgomery
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, 70182 Örebro, Sweden;
- Clinical Epidemiology Division, Department of Medicine, Karolinska Institutet, 17177 Stockholm, Sweden
- Department of Epidemiology and Public Health, University College London, London WC1E 6BT, UK
| | - Shahin Mohseni
- School of Medical Sciences, Orebro University, 70182 Orebro, Sweden;
- Division of Trauma and Emergency Surgery, Department of Surgery, Orebro University Hospital, 70185 Orebro, Sweden
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Dakhil MA, El-Keblawy A, El-Sheikh MA, Halmy MWA, Ksiksi T, Hassan WA. Global Invasion Risk Assessment of Prosopis juliflora at Biome Level: Does Soil Matter? BIOLOGY 2021; 10:biology10030203. [PMID: 33803081 PMCID: PMC7999975 DOI: 10.3390/biology10030203] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 02/23/2021] [Accepted: 02/25/2021] [Indexed: 11/16/2022]
Abstract
Prosopis juliflora is one of the most problematic invasive trees in tropical and subtropical regions. Understanding driving forces affecting the potential global distribution would help in managing its current and future spread. The role of climate on the global spatial distribution of P. juliflora has been well studied, but little is known about the role of soil and human impacts as potential drivers. Here, we used maximum entropy (MaxEnt) for species distribution modelling to understand the role of climate (C), soil (S) and human impacts (H), C+S, and C+S+H in controlling the potential invasion range of P. juliflora, and to project its global potential invasive risk. We defined the top threatened global biomes, as predicted by the best-selected model. The incorporation of the edaphic factors improved the model performance and enhanced the accuracy of the outcome. Our findings revealed that the potential invasion risk increases with increases in mean temperature of the driest quarter (Bio9), soil alkalinity and clay fractions. Arid and semi-arid lands are at the highest risk of invasion than other moist biomes.
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Affiliation(s)
- Mohammed A. Dakhil
- Botany and Microbiology Department, Faculty of Science, Helwan University, Cairo 11790, Egypt;
| | - Ali El-Keblawy
- Department of Applied Biology, Faculty of Science, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
- Correspondence:
| | - Mohamed A. El-Sheikh
- Botany & Microbiology Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia;
| | - Marwa Waseem A. Halmy
- Department of Environmental Sciences, Faculty of Science, Alexandria University, Alexandria 21511, Egypt;
| | - Taoufik Ksiksi
- Biology Department, United Arab Emirates University, Al Ain 15258, United Arab Emirates;
| | - Walaa A. Hassan
- Botany and Microbiology Department, Faculty of Science, Beni-Suef University, Beni-Suef 62511, Egypt;
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Van Eupen C, Maes D, Herremans M, Swinnen KR, Somers B, Luca S. The impact of data quality filtering of opportunistic citizen science data on species distribution model performance. Ecol Modell 2021. [DOI: 10.1016/j.ecolmodel.2021.109453] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Santini L, Benítez‐López A, Maiorano L, Čengić M, Huijbregts MAJ. Assessing the reliability of species distribution projections in climate change research. DIVERS DISTRIB 2021. [DOI: 10.1111/ddi.13252] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Affiliation(s)
- Luca Santini
- Department of Biology and Biotechnologies “Charles Darwin” Sapienza University of Rome Rome Italy
- Institute of Research on Terrestrial Ecosystems (CNR‐IRET) National Research Council Monterotondo, Rome Italy
- Department of Environmental Science Institute for Wetland and Water Research Faculty of Science Radboud University Nijmegen The Netherlands
| | - Ana Benítez‐López
- Department of Environmental Science Institute for Wetland and Water Research Faculty of Science Radboud University Nijmegen The Netherlands
- Integrative Ecology Group Estación Biológica de Doñana (EBD‐CSIC) Sevilla Spain
| | - Luigi Maiorano
- Department of Biology and Biotechnologies “Charles Darwin” Sapienza University of Rome Rome Italy
| | - Mirza Čengić
- Department of Environmental Science Institute for Wetland and Water Research Faculty of Science Radboud University Nijmegen The Netherlands
| | - Mark A. J. Huijbregts
- Department of Environmental Science Institute for Wetland and Water Research Faculty of Science Radboud University Nijmegen The Netherlands
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Kapitza S, Van Ha P, Kompas T, Golding N, Cadenhead NCR, Bal P, Wintle BA. Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity. Sci Rep 2021; 11:3304. [PMID: 33558621 PMCID: PMC7870812 DOI: 10.1038/s41598-021-82474-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 01/18/2021] [Indexed: 01/30/2023] Open
Abstract
Climate change threatens biodiversity directly by influencing biophysical variables that drive species' geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.
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Affiliation(s)
- Simon Kapitza
- Quantitative and Applied Ecology Group, School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - Pham Van Ha
- Crawford School of Public Policy, Australian National University, Acton, ACT, 2601, Australia
| | - Tom Kompas
- Crawford School of Public Policy, Australian National University, Acton, ACT, 2601, Australia
- Centre of Excellence for Biosecurity Risk Analysis, School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Nick Golding
- Quantitative and Applied Ecology Group, School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Natasha C R Cadenhead
- Quantitative and Applied Ecology Group, School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
- NESP Threatened Species Recovery Hub, University of Melbourne and University of Queensland, St Lucia, QLD, 4072, Australia
| | - Payal Bal
- Quantitative and Applied Ecology Group, School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Brendan A Wintle
- Quantitative and Applied Ecology Group, School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia
- NESP Threatened Species Recovery Hub, University of Melbourne and University of Queensland, St Lucia, QLD, 4072, Australia
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31
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Steen VA, Tingley MW, Paton PWC, Elphick CS. Spatial thinning and class balancing: Key choices lead to variation in the performance of species distribution models with citizen science data. Methods Ecol Evol 2020. [DOI: 10.1111/2041-210x.13525] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Valerie A. Steen
- Ecology & Evolutionary Biology University of Connecticut Storrs CT USA
- Department of Natural Resources Science University of Rhode Island Kingston RI USA
| | - Morgan W. Tingley
- Ecology & Evolutionary Biology University of Connecticut Storrs CT USA
- Ecology and Evolutionary Biology University of California Los Angeles CA USA
| | - Peter W. C. Paton
- Department of Natural Resources Science University of Rhode Island Kingston RI USA
| | - Chris S. Elphick
- Ecology & Evolutionary Biology University of Connecticut Storrs CT USA
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32
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Mod HK, Scherrer D, Di Cola V, Broennimann O, Blandenier Q, Breiner FT, Buri A, Goudet J, Guex N, Lara E, Mitchell EAD, Niculita‐Hirzel H, Pagni M, Pellissier L, Pinto‐Figueroa E, Sanders IR, Schmidt BR, Seppey CVW, Singer D, Ursenbacher S, Yashiro E, van der Meer JR, Guisan A. Greater topoclimatic control of above- versus below-ground communities. GLOBAL CHANGE BIOLOGY 2020; 26:6715-6728. [PMID: 32866994 PMCID: PMC7756268 DOI: 10.1111/gcb.15330] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 06/04/2020] [Accepted: 08/04/2020] [Indexed: 06/11/2023]
Abstract
Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above-ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above- and below-ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above-ground species than on below-ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above-ground than for below-ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above- and below-ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems.
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Affiliation(s)
- Heidi K. Mod
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
- Department of Geosciences and GeographyUniversity of HelsinkiHelsinkiFinland
| | - Daniel Scherrer
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
- Swiss Federal Institute for Forest, Snow and Landscape Research WSLBirmensdorfSwitzerland
| | - Valeria Di Cola
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
| | - Olivier Broennimann
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
- Institute of Earth Surface DynamicsUniversity of LausanneLausanneSwitzerland
| | - Quentin Blandenier
- Laboratory of Soil BiodiversityInstitute of BiologyUniversity of NeuchâtelNeuchâtelSwitzerland
- Real Jardín BotánicoCSICMadridSpain
| | - Frank T. Breiner
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
| | - Aline Buri
- Institute of Earth Surface DynamicsUniversity of LausanneLausanneSwitzerland
| | - Jérôme Goudet
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
- Swiss Institute of BioinformaticsUniversity of LausanneLausanneSwitzerland
| | - Nicolas Guex
- Bioinformatics Competence CenterUniversity of LausanneLausanneSwitzerland
- Vital‐IT GroupSwiss Institute of BioinformaticsLausanneSwitzerland
| | | | - Edward A. D. Mitchell
- Laboratory of Soil BiodiversityInstitute of BiologyUniversity of NeuchâtelNeuchâtelSwitzerland
- Jardin Botanique de NeuchâtelNeuchâtelSwitzerland
| | - Hélène Niculita‐Hirzel
- Department of Occupational Health and EnvironmentCenter for Primary Care and Public Health (Unisanté)University of LausanneLausanneSwitzerland
| | - Marco Pagni
- Vital‐IT GroupSwiss Institute of BioinformaticsLausanneSwitzerland
| | - Loïc Pellissier
- Swiss Federal Institute for Forest, Snow and Landscape Research WSLBirmensdorfSwitzerland
- Landscape EcologyDepartment of Environmental Systems ScienceETH ZürichZürichSwitzerland
| | | | - Ian R. Sanders
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
| | - Benedikt R. Schmidt
- Info Fauna KarchNeuchâtelSwitzerland
- Department of Evolutionary Biology and Environmental StudiesUniversity of ZurichZurichSwitzerland
| | | | - David Singer
- Laboratory of Soil BiodiversityInstitute of BiologyUniversity of NeuchâtelNeuchâtelSwitzerland
- Department of ZoologyInstitute of BiosciencesUniversity of São PauloSão PauloBrazil
| | - Sylvain Ursenbacher
- Info Fauna KarchNeuchâtelSwitzerland
- Department of Environmental SciencesSection of Conservation BiologyUniversity of BaselBaselSwitzerland
| | - Erika Yashiro
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
- Department of Fundamental MicrobiologyUniversity of LausanneLausanneSwitzerland
| | - Jan R. van der Meer
- Department of Fundamental MicrobiologyUniversity of LausanneLausanneSwitzerland
| | - Antoine Guisan
- Department of Ecology and EvolutionUniversity of LausanneLausanneSwitzerland
- Institute of Earth Surface DynamicsUniversity of LausanneLausanneSwitzerland
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33
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Wilkinson DP, Golding N, Guillera‐Arroita G, Tingley R, McCarthy MA. Defining and evaluating predictions of joint species distribution models. Methods Ecol Evol 2020. [DOI: 10.1111/2041-210x.13518] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
| | - Nick Golding
- School of BioSciences University of Melbourne Parkville Vic. Australia
- Telethon Kids InstitutePerth Children's Hospital Nedlands WA Australia
- Curtin University Bentley WA Australia
| | | | - Reid Tingley
- School of Biological Sciences Monash University Clayton Vic. Australia
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34
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Ingram M, Vukcevic D, Golding N. Multi‐output Gaussian processes for species distribution modelling. Methods Ecol Evol 2020. [DOI: 10.1111/2041-210x.13496] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Martin Ingram
- School of BioSciences University of Melbourne Parkville Vic. Australia
| | - Damjan Vukcevic
- School of Mathematics and Statistics University of Melbourne Parkville Vic. Australia
- Melbourne Integrative Genomics University of Melbourne Parkville Vic. Australia
| | - Nick Golding
- School of BioSciences University of Melbourne Parkville Vic. Australia
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35
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Gobeyn S, Goethals PLM. Multi-objective optimisation of species distribution models for river management. WATER RESEARCH 2019; 163:114863. [PMID: 31349090 DOI: 10.1016/j.watres.2019.114863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 07/09/2019] [Accepted: 07/13/2019] [Indexed: 06/10/2023]
Abstract
Environmental and measure implementation costs are two key factors to be considered by river managers in decision making. To balance effects and costs of an action, practitioners can rely on diagnostic analysis of presence/absence freshwater species distribution models (SDMs) trained to over- or underestimating species presence. Prevalence-adjusted model training aims to balance under- and overestimation depending on study objectives and training data characteristics. The objective of minimising under- and overestimation is a typical example of multi-objective optimisation (MOO). The aim of this paper is to address, for the first time, the practice of MOO-based prevalence-adjusted SDM training for freshwater decision management. In a numerical experiment, the use of Pareto-based MOO, specifically the non-dominated sorting genetic algorithm II (NSGA-II), is compared to commonly-used single-objective optimisation. SDMs for 11 pollution-sensitive freshwater macroinvertebrate species are trained with a subset of the Limnodata, a large data set holding records in the Netherlands over 30 years at 20,000 locations. An increase of two to four times is observed for the ability to identify a large range distribution of the solutions in the Pareto space, when using NSGA-II counter to repeated single-objective optimisation, this by increasing the average runtime with only four percent for a single run. In addition, the use of NSGA-II is found to be effective to identify reliable SDMs useful for diagnostic analysis. By applying and comparing a broad range of MOO methodologies for prevalence-adjusted model training, we believe a closer collaboration between model developers and freshwater managers can be facilitated and environmental standard limits can be set on a more objective basis. In conclusion, the use of MOO for prevalence-adjusted model training is assessed as a valuable tool to support river - and potentially all environmental - decision making.
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Affiliation(s)
- Sacha Gobeyn
- Ghent University, Department of Animal Sciences and Aquatic Ecology, Coupure Links 653, B-9000, Ghent, Belgium.
| | - Peter L M Goethals
- Ghent University, Department of Animal Sciences and Aquatic Ecology, Coupure Links 653, B-9000, Ghent, Belgium
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36
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A checklist for maximizing reproducibility of ecological niche models. Nat Ecol Evol 2019; 3:1382-1395. [PMID: 31548646 DOI: 10.1038/s41559-019-0972-5] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 07/29/2019] [Indexed: 11/08/2022]
Abstract
Reporting specific modelling methods and metadata is essential to the reproducibility of ecological studies, yet guidelines rarely exist regarding what information should be noted. Here, we address this issue for ecological niche modelling or species distribution modelling, a rapidly developing toolset in ecology used across many aspects of biodiversity science. Our quantitative review of the recent literature reveals a general lack of sufficient information to fully reproduce the work. Over two-thirds of the examined studies neglected to report the version or access date of the underlying data, and only half reported model parameters. To address this problem, we propose adopting a checklist to guide studies in reporting at least the minimum information necessary for ecological niche modelling reproducibility, offering a straightforward way to balance efficiency and accuracy. We encourage the ecological niche modelling community, as well as journal reviewers and editors, to utilize and further develop this framework to facilitate and improve the reproducibility of future work. The proposed checklist framework is generalizable to other areas of ecology, especially those utilizing biodiversity data, environmental data and statistical modelling, and could also be adopted by a broader array of disciplines.
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37
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38
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Climate change and the potential expansion of buffelgrass (Cenchrus ciliaris L., Poaceae) in biotic communities of Southwest United States and northern Mexico. Biol Invasions 2019. [DOI: 10.1007/s10530-019-02050-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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39
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Wunderlich RF, Lin YP, Anthony J, Petway JR. Two alternative evaluation metrics to replace the true skill statistic in the assessment of species distribution models. NATURE CONSERVATION 2019. [DOI: 10.3897/natureconservation.35.33918] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Model evaluation metrics play a critical role in the selection of adequate species distribution models for conservation and for any application of species distribution modelling (SDM) in general. The responses of these metrics to modelling conditions, however, are rarely taken into account. This leads to inadequate model selection, downstream analyses and uniformed decisions. To aid modellers in critically assessing modelling conditions when choosing and interpreting model evaluation metrics, we analysed the responses of the True Skill Statistic (TSS) under a variety of presence-background modelling conditions using purely theoretical scenarios. We then compared these responses with those of two evaluation metrics commonly applied in the field of meteorology which have potential for use in SDM: the Odds Ratio Skill Score (ORSS) and the Symmetric Extremal Dependence Index (SEDI). We demonstrate that (1) large cell number totals in the confusion matrix, which is strongly biased towards ‘true’ absences in presence-background SDM and (2) low prevalence both compromise model evaluation with TSS. This is since (1) TSS fails to differentiate useful from random models at extreme prevalence levels if the confusion matrix cell number total exceeds ~30,000 cells and (2) TSS converges to hit rate (sensitivity) when prevalence is lower than ~2.5%. We conclude that SEDI is optimal for most presence-background SDM initiatives. Further, ORSS may provide a better alternative if absence data are available or if equal error weighting is strictly required.
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40
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Jerosch K, Scharf FK, Deregibus D, Campana GL, Zacher K, Pehlke H, Falk U, Hass HC, Quartino ML, Abele D. Ensemble Modeling of Antarctic Macroalgal Habitats Exposed to Glacial Melt in a Polar Fjord. Front Ecol Evol 2019. [DOI: 10.3389/fevo.2019.00207] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
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41
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Norberg A, Abrego N, Blanchet FG, Adler FR, Anderson BJ, Anttila J, Araújo MB, Dallas T, Dunson D, Elith J, Foster SD, Fox R, Franklin J, Godsoe W, Guisan A, O'Hara B, Hill NA, Holt RD, Hui FKC, Husby M, Kålås JA, Lehikoinen A, Luoto M, Mod HK, Newell G, Renner I, Roslin T, Soininen J, Thuiller W, Vanhatalo J, Warton D, White M, Zimmermann NE, Gravel D, Ovaskainen O. A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels. ECOL MONOGR 2019. [DOI: 10.1002/ecm.1370] [Citation(s) in RCA: 169] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Anna Norberg
- Organismal and Evolutionary Biology Research Programme University of Helsinki P.O. Box 65 Helsinki FI‐00014 Finland
| | - Nerea Abrego
- Department of Biology Centre for Biodiversity Dynamics Norwegian University of Science and Technology Trondheim N‐7491 Norway
- Department of Agricultural Sciences University of Helsinki P.O. Box 27 Helsinki FI‐00014 Finland
| | - F. Guillaume Blanchet
- Département de Biologie Université de Sherbrooke 2500 boulevard de l'Université Sherbrooke Quebec J1K 2R1 Canada
| | - Frederick R. Adler
- Department of Mathematics University of Utah 155 South 1400 East Salt Lake City Utah 84112 USA
- School of Biological Sciences University of Utah 257 South 1400 East Salt Lake City Utah 84112 USA
| | | | - Jani Anttila
- Organismal and Evolutionary Biology Research Programme University of Helsinki P.O. Box 65 Helsinki FI‐00014 Finland
| | - Miguel B. Araújo
- Departmento de Biogeografía y Cambio Global Museo Nacional de Ciencias Naturales Consejo Superior de Investigaciones Científicas (CSIC) Calle José Gutiérrez Abascal 2 Madrid 28006 Spain
- Rui Nabeiro Biodiversity Chair Universidade de Évora Largo dos Colegiais Evora 7000 Portugal
- Center for Macroecology, Evolution and Climate Natural History Museum of Denmark University of Copenhagen Copenhagen 2100 Denmark
| | - Tad Dallas
- Organismal and Evolutionary Biology Research Programme University of Helsinki P.O. Box 65 Helsinki FI‐00014 Finland
| | - David Dunson
- Department of Statistical Science Duke University P.O. Box 90251 Durham North Carolina 27708 USA
| | - Jane Elith
- School of BioSciences University of Melbourne Parkville Victoria 3010 Australia
| | - Scott D. Foster
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Hobart Tasmania Australia
| | - Richard Fox
- Butterfly Conservation Manor Yard, East Lulworth Wareham BH20 5QP United Kingdom
| | - Janet Franklin
- Department of Botany and Plant Sciences University of California Riverside California 92521 USA
| | - William Godsoe
- Bio‐Protection Research Centre Lincoln University P.O. Box 85084 Lincoln 7647 New Zealand
| | - Antoine Guisan
- Department of Ecology and Evolution (DEE) University of Lausanne, Biophore Lausanne CH‐1015 Switzerland
- Institute of Earth Surface Dynamics (IDYST) University of Lausanne, Geopolis Lausanne CH‐1015 Switzerland
| | - Bob O'Hara
- Department of Mathematical Sciences Norwegian University of Science and Technology Trondheim N‐7491 Norway
| | - Nicole A. Hill
- Institute for Marine and Antarctic Studies University of Tasmania Private Bag 49 Hobart Tasmania 7001 Australia
| | - Robert D. Holt
- Department of Biology The University of Florida Gainesville Florida 32611 USA
| | - Francis K. C. Hui
- Mathematical Sciences Institute The Australian National University Acton Australian Capital Territory 2601 Australia
| | - Magne Husby
- Nord University Røstad Levanger 7600 Norway
- BirdLife Norway Sandgata 30B Trondheim 7012 Norway
| | - John Atle Kålås
- Norwegian Institute for Nature Research P.O. Box 5685, Torgarden Trondheim NO‐7485 Norway
| | - Aleksi Lehikoinen
- The Helsinki Lab of Ornithology Finnish Museum of Natural History University of Helsinki P.O. Box 17 Helsinki FI‐00014 Finland
| | - Miska Luoto
- Department of Geosciences and Geography University of Helsinki P.O. Box 64 Helsinki 00014 Finland
| | - Heidi K. Mod
- Institute of Earth Surface Dynamics (IDYST) University of Lausanne, Geopolis Lausanne CH‐1015 Switzerland
| | - Graeme Newell
- Biodiversity Division Department of Environment, Land, Water & Planning Arthur Rylah Institute for Environmental Research 123 Brown Street Heidelberg Victoria 3084 Australia
| | - Ian Renner
- School of Mathematical and Physical Sciences The University of Newcastle University Drive Callaghan New South Wales 2308 Australia
| | - Tomas Roslin
- Department of Agricultural Sciences University of Helsinki P.O. Box 27 Helsinki FI‐00014 Finland
- Department of Ecology Swedish University of Agricultural Sciences Box 7044 Uppsala 750 07 Sweden
| | - Janne Soininen
- Department of Geosciences and Geography University of Helsinki P.O. Box 64 Helsinki 00014 Finland
| | - Wilfried Thuiller
- CNRS LECA Laboratoire d’Écologie Alpine University Grenoble Alpes Grenoble F‐38000 France
| | - Jarno Vanhatalo
- Organismal and Evolutionary Biology Research Programme University of Helsinki P.O. Box 65 Helsinki FI‐00014 Finland
| | - David Warton
- School of Mathematics and Statistics Evolution & Ecology Research Centre University of New South Wales Sydney New South Wales 2052 Australia
| | - Matt White
- Biodiversity Division Department of Environment, Land, Water & Planning Arthur Rylah Institute for Environmental Research 123 Brown Street Heidelberg Victoria 3084 Australia
| | - Niklaus E. Zimmermann
- Dynamic Macroecology Swiss Federal Research Institute WSL Zuercherstrasse 111 Birmensdorf CH‐8903 Switzerland
| | - Dominique Gravel
- Département de Biologie Université de Sherbrooke 2500 boulevard de l'Université Sherbrooke Quebec J1K 2R1 Canada
| | - Otso Ovaskainen
- Organismal and Evolutionary Biology Research Programme University of Helsinki P.O. Box 65 Helsinki FI‐00014 Finland
- Department of Biology Centre for Biodiversity Dynamics Norwegian University of Science and Technology Trondheim N‐7491 Norway
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42
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Stevens BS, Conway CJ. Predicting species distributions: unifying model selection and scale optimization for multi‐scale occupancy models. Ecosphere 2019. [DOI: 10.1002/ecs2.2748] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Bryan S. Stevens
- Idaho Cooperative Fish and Wildlife Research Unit Department of Fish and Wildlife Sciences University of Idaho Moscow Idaho 83844 USA
| | - Courtney J. Conway
- U.S. Geological Survey Idaho Cooperative Fish and Wildlife Research Unit University of Idaho Moscow Idaho 83844 USA
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43
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Fletcher RJ, Hefley TJ, Robertson EP, Zuckerberg B, McCleery RA, Dorazio RM. A practical guide for combining data to model species distributions. Ecology 2019; 100:e02710. [PMID: 30927270 DOI: 10.1002/ecy.2710] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 11/09/2018] [Accepted: 01/02/2019] [Indexed: 12/25/2022]
Abstract
Understanding and accurately modeling species distributions lies at the heart of many problems in ecology, evolution, and conservation. Multiple sources of data are increasingly available for modeling species distributions, such as data from citizen science programs, atlases, museums, and planned surveys. Yet reliably combining data sources can be challenging because data sources can vary considerably in their design, gradients covered, and potential sampling biases. We review, synthesize, and illustrate recent developments in combining multiple sources of data for species distribution modeling. We identify five ways in which multiple sources of data are typically combined for modeling species distributions. These approaches vary in their ability to accommodate sampling design, bias, and uncertainty when quantifying environmental relationships in species distribution models. Many of the challenges for combining data are solved through the prudent use of integrated species distribution models: models that simultaneously combine different data sources on species locations to quantify environmental relationships for explaining species distribution. We illustrate these approaches using planned survey data on 24 species of birds coupled with opportunistically collected eBird data in the southeastern United States. This example illustrates some of the benefits of data integration, such as increased precision in environmental relationships, greater predictive accuracy, and accounting for sample bias. Yet it also illustrates challenges of combining data sources with vastly different sampling methodologies and amounts of data. We provide one solution to this challenge through the use of weighted joint likelihoods. Weighted joint likelihoods provide a means to emphasize data sources based on different criteria (e.g., sample size), and we find that weighting improves predictions for all species considered. We conclude by providing practical guidance on combining multiple sources of data for modeling species distributions.
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Affiliation(s)
- Robert J Fletcher
- Department of Wildlife Ecology and Conservation, University of Florida, P.O. Box 110430, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611-0430, USA
| | - Trevor J Hefley
- Department of Statistics, Kansas State University, 205 Dickens Hall, Manhattan, Kansas, 66506-0802, USA
| | - Ellen P Robertson
- Department of Wildlife Ecology and Conservation, University of Florida, P.O. Box 110430, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611-0430, USA
| | - Benjamin Zuckerberg
- Department of Forest and Wildlife Ecology, University of Wisconsin, 226 Russell Labs, 1630 Linden Drive, Madison, Wisconsin, 53706-1598, USA
| | - Robert A McCleery
- Department of Wildlife Ecology and Conservation, University of Florida, P.O. Box 110430, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611-0430, USA
| | - Robert M Dorazio
- Department of Biology, San Francisco State University, 1600 Holloway Avenue, San Francisco, California, 94132, USA
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Leung B, Hudgins EJ, Potapova A, Ruiz-Jaen MC. A new baseline for countrywide α-diversity and species distributions: illustration using >6,000 plant species in Panama. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2019; 29:e01866. [PMID: 30706569 DOI: 10.1002/eap.1866] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 01/02/2019] [Accepted: 01/07/2019] [Indexed: 06/09/2023]
Abstract
Estimating α-diversity and species distributions provides baseline information to understand factors such as biodiversity loss and erosion of ecosystem services. Yet, species surveys typically cover a small portion of any country's landmass. Public, global databases could help, but contain biases. Thus, the magnitude of bias should be identified and ameliorated, the value of integration determined, and application to current policy issues illustrated. The ideal integrative approach should be powerful, flexible, efficient, and conceptually straightforward. We estimated distributions for >6,000 species, integrating species sightings (S) from the Global Biodiversity Information Facility (GBIF), systematic survey data (S2 ), and "bias-adjustment kernels" (BaK) using spatial and species trait databases (S2 BaK). We validated our approach using both locational and species holdout sets, and then applied our predictive model to Panama. Using sightings alone (the most common approach) discriminated relative probabilities of occurrences well (area under the curve [AUC] = 0.88), but underestimated actual probabilities by ~4,000%, while using survey data alone omitted over three-quarters of the >6,000 species. Comparatively, S2 BaK had no systematic underestimation, and substantially stronger discrimination (AUC = 0.96) and predictive power (deviance explained = 47%). Our model suggested high diversity (~200% countrywide mean) where urban development is projected to occur (the Panama Canal watershed) and also suggested this is not due to higher sampling intensity. However, portions of the Caribbean coast and eastern Panama (the Darién Gap) were even higher, both for total plant biodiversity (~250% countrywide mean), and CITES listed species. Finally, indigenous territories appeared half as diverse as other regions, based on survey observations. However, our model suggested this was largely due to site selection, and that richness in and out of indigenous territories was roughly equal. In brief, we provide arguably the best estimate of countrywide plant α-diversity and species distributions in the Neotropics, and make >6,000 species distributions available. We identify regions of overlap between development and high biodiversity, and improve interpretation of biodiversity patterns, including for policy-relevant CITES species, and locations with limited access (i.e., indigenous territories). We derive a powerful, flexible, efficient and simple estimation approach for biodiversity science.
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Affiliation(s)
- Brian Leung
- Department of Biology, McGill University, Montreal, Quebec, H3A 1B1, Canada
- School of Environment, McGill University, Montreal, Quebec, H3A 2A7, Canada
- Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Panama City, Panama
| | - Emma J Hudgins
- Department of Biology, McGill University, Montreal, Quebec, H3A 1B1, Canada
| | - Anna Potapova
- Department of Biology, McGill University, Montreal, Quebec, H3A 1B1, Canada
- School of Environment, McGill University, Montreal, Quebec, H3A 2A7, Canada
| | - Maria C Ruiz-Jaen
- Subregional Office for Mesoamerica, Food and Agriculture Organization of the United Nations, Panama City, Panama
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Sofaer HR, Hoeting JA, Jarnevich CS. The area under the precision‐recall curve as a performance metric for rare binary events. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13140] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Helen R. Sofaer
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado
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Liang J, Xing W, Zeng G, Li X, Peng Y, Li X, Gao X, He X. Where will threatened migratory birds go under climate change? Implications for China's national nature reserves. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 645:1040-1047. [PMID: 30248829 DOI: 10.1016/j.scitotenv.2018.07.196] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 07/14/2018] [Accepted: 07/15/2018] [Indexed: 06/08/2023]
Abstract
Climate change, regarded as one of the major threats to biodiversity and ecosystems, can impact on the distribution and survival of migratory birds. To investigate the threats of climate change to threatened migratory bird distributions, we used species distribution model (SDM) and climatic data under current and future climate scenarios to predict future changes in species distributions and how the geographic distribution of these threatened birds may respond to climate change by 2050. Our results show the hotspots for all species may remain in the lower and middle reaches of the Yangtze River, while more species may dwell in the coastal regions of the Bohai Gulf and the Yellow Sea in the future. Our findings show that the percentage of all species distributions or hotspots for all threatened species covered by national nature reserves (NNRs) in China remain low by 2050. Thus, we propose that China should increase and expand reserves in eastern China. Significantly, we emphasize the creation of protected areas to make it the Ramsar sites in the world and recommend that China should (1) strengthen the cooperation with neighboring countries to share maximum species occurrence data (especially the threatened species), (2) overlay maps of individual species for each taxon to assess the efficiency of coastal nature reserves and predict the hotspots shift under climate change, (3) trade off urban development and ecosystem stability to create new and dynamic protected areas to make it the Ramsar sites, (4) appeal for long-term protection of ecosystem stability to achieve sustainable development in the world.
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Affiliation(s)
- Jie Liang
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China.
| | - Wenle Xing
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China
| | - Guangming Zeng
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China.
| | - Xin Li
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China
| | - Yuhui Peng
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China
| | - Xiaodong Li
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China
| | - Xiang Gao
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China
| | - Xinyue He
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, PR China; Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, PR China
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Early R, González-Moreno P, Murphy ST, Day R. Forecasting the global extent of invasion of the cereal pest Spodoptera frugiperda, the fall armyworm. NEOBIOTA 2018. [DOI: 10.3897/neobiota.40.28165] [Citation(s) in RCA: 142] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Fall armyworm, Spodopterafrugiperda, is a crop pest native to the Americas, which has invaded and spread throughout sub-Saharan Africa within two years. Recent estimates of 20–50% maize yield loss in Africa suggest severe impact on livelihoods. Fall armyworm is still infilling its potential range in Africa and could spread to other continents. In order to understand fall armyworm’s year-round, global, potential distribution, we used evidence of the effects of temperature and precipitation on fall armyworm life-history, combined with data on native and African distributions to construct Species Distribution Models (SDMs). We also investigated the strength of trade and transportation pathways that could carry fall armyworm beyond Africa. Up till now, fall armyworm has only invaded areas that have a climate similar to the native distribution, validating the use of climatic SDMs. The strongest climatic limits on fall armyworm’s year-round distribution are the coldest annual temperature and the amount of rain in the wet season. Much of sub-Saharan Africa can host year-round fall armyworm populations, but the likelihoods of colonising North Africa and seasonal migrations into Europe are hard to predict. South and Southeast Asia and Australia have climate conditions that would permit fall armyworm to invade. Current trade and transportation routes reveal Australia, China, India, Indonesia, Malaysia, Philippines and Thailand face high threat of fall armyworm invasions originating from Africa.
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How much should one sample to accurately predict the distribution of species assemblages? A virtual community approach. ECOL INFORM 2018. [DOI: 10.1016/j.ecoinf.2018.09.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Ecosystem Services in a Protected Mountain Range of Portugal: Satellite-Based Products for State and Trend Analysis. REMOTE SENSING 2018. [DOI: 10.3390/rs10101573] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Mountains are facing strong environmental pressures, which may jeopardize the supply of various ecosystem services. For sustainable land management, ecosystem services and their supporting functions should thus be evaluated and monitored. Satellite products have been receiving growing attention for monitoring ecosystem functioning, mainly due to their increasing temporal and spatial resolutions. Here, we aim to illustrate the high potential of satellite products, combined with ancillary in situ and statistical data, to monitor the current state and trend of ecosystem services in the Peneda-Gerês National Park, a protected mountain range in Portugal located in a transition climatic zone (Atlantic to Mediterranean). We focused on three ecosystem services belonging to three broad categories: provisioning (reared animals), regulating (of water flows), and cultural (conservation of an endemic and iconic species). These services were evaluated using a set of different satellite products, namely grassland cover, soil moisture, and ecosystem functional attributes. In situ and statistical data were also used to compute final indicators of ecosystem services. We found a decline in the provision of reared animals since year 2000, although the area of grasslands had remained stable. The regulation of water flows had been maintained, and a strong relationship with interannual precipitation pattern was noted. In the same period, conservation of the focal iconic species might have been affected by interannual fluctuations of suitable habitat areas, with a possible influence of wildfires and precipitation. We conclude that satellite products can efficiently provide information about the current state and trend in the supply of various categories of ecosystem services, especially when combined with in situ or statistical data in robust modeling frameworks.
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