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Dai G, Yang J, Lu S, Huang C, Jin J, Jiang P, Yan P. The potential impact of invasive woody oil plants on protected areas in China under future climate conditions. Sci Rep 2018; 8:1041. [PMID: 29348468 PMCID: PMC5773687 DOI: 10.1038/s41598-018-19477-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Accepted: 01/03/2018] [Indexed: 12/04/2022] Open
Abstract
Biodiesel produced from woody oil plants is considered a green substitute for fossil fuels. However, a potential negative impact of growing woody oil plants on a large scale is the introduction of highly invasive species into susceptible regions. In this study, we examined the potential invasion risk of woody oil plants in China's protected areas under future climate conditions. We simulated the current and future potential distributions of three invasive woody oil plants, Jatropha curcas, Ricinus communis, and Aleurites moluccana, under two climate change scenarios (RCP2.6 and RCP8.5) up to 2050 using species distribution models. Protected areas in China that will become susceptible to these species were then identified using a spatial overlay analysis. Our results showed that by 2050, 26 and 41 protected areas would be threatened by these invasive woody oil plants under scenarios RCP2.6 and RCP8.5, respectively. A total of 10 unique forest ecosystems and 17 rare plant species could be potentially affected. We recommend that the invasive potential of woody oil plants be fully accounted for when developing forest-based biodiesel, especially around protected areas.
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Affiliation(s)
- Guanghui Dai
- Ministry of Education Key Laboratory for Silviculture and Conservation, Beijing Forestry University, Beijing, 100083, China
| | - Jun Yang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
- Joint Center for Global Change Studies, Beijing, 100875, China.
| | - Siran Lu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Conghong Huang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jing Jin
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Peng Jiang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Pengbo Yan
- Ministry of Education Key Laboratory for Silviculture and Conservation, Beijing Forestry University, Beijing, 100083, China
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52
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Tjaden NB, Caminade C, Beierkuhnlein C, Thomas SM. Mosquito-Borne Diseases: Advances in Modelling Climate-Change Impacts. Trends Parasitol 2017; 34:227-245. [PMID: 29229233 DOI: 10.1016/j.pt.2017.11.006] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 11/21/2017] [Accepted: 11/21/2017] [Indexed: 01/15/2023]
Abstract
Vector-borne diseases are on the rise globally. As the consequences of climate change are becoming evident, climate-based models of disease risk are of growing importance. Here, we review the current state-of-the-art in both mechanistic and correlative disease modelling, the data driving these models, the vectors and diseases covered, and climate models applied to assess future risk. We find that modelling techniques have advanced considerably, especially in terms of using ensembles of climate models and scenarios. Effects of extreme events, precipitation regimes, and seasonality on diseases are still poorly studied. Thorough validation of models is still a challenge and is complicated by a lack of field and laboratory data. On a larger scale, the main challenges today lie in cross-disciplinary and cross-sectoral transfer of data and methods.
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Affiliation(s)
| | - Cyril Caminade
- Institute of Infection and Global Health, University of Liverpool, UK; NIHR, Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, UK
| | - Carl Beierkuhnlein
- Department of Biogeography, University of Bayreuth, Germany; BayCEER, Bayreuth Center for Ecology and Environmental Research, Bayreuth, Germany; GIB, Geographisches Institut Bayreuth, Bayreuth, Germany
| | - Stephanie Margarete Thomas
- Department of Biogeography, University of Bayreuth, Germany; BayCEER, Bayreuth Center for Ecology and Environmental Research, Bayreuth, Germany.
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53
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Freer JJ, Partridge JC, Tarling GA, Collins MA, Genner MJ. Predicting ecological responses in a changing ocean: the effects of future climate uncertainty. MARINE BIOLOGY 2017; 165:7. [PMID: 29170567 PMCID: PMC5680362 DOI: 10.1007/s00227-017-3239-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2017] [Accepted: 09/26/2017] [Indexed: 05/15/2023]
Abstract
Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica. Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.
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Affiliation(s)
- Jennifer J. Freer
- School of Biological Sciences, University of Bristol, Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ UK
| | - Julian C. Partridge
- School of Biological Sciences and Oceans Institute, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009 Australia
| | - Geraint A. Tarling
- British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET UK
| | - Martin A. Collins
- Centre for Environment, Fisheries and Aquaculture Science, Lowestoft, NR33 0HT UK
| | - Martin J. Genner
- School of Biological Sciences, University of Bristol, Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ UK
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54
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Noce S, Collalti A, Santini M. Likelihood of changes in forest species suitability, distribution, and diversity under future climate: The case of Southern Europe. Ecol Evol 2017; 7:9358-9375. [PMID: 29187974 PMCID: PMC5696419 DOI: 10.1002/ece3.3427] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 06/27/2017] [Accepted: 08/03/2017] [Indexed: 01/15/2023] Open
Abstract
Forest conservation strategies and plans can be unsuccessful if the new habitat conditions determined by climate change are not considered. Our work aims at investigating the likelihood of future suitability, distribution and diversity for some common European forest species under the projected changes in climate, focusing on Southern Europe. We combine an Ensemble Platform for Species Distribution Models (SDMs) to five Global Circulation Models (GCMs) driven by two Representative Concentration Pathways (RCPs), to produce maps of future climate-driven habitat suitability for ten categories of forest species and two time horizons. For each forest category and time horizon, ten maps of future distribution (5 GCMs by 2 RCPs) are thus combined in a single suitability map supplied with information about the "likelihood" adopting the IPCC terminology based on consensus among projections. Then, the statistical significance of spatially aggregated changes in forest composition at local and regional level is analyzed. Finally, we discuss the importance, among SDMs, that environmental predictors seem to have in influencing forest distribution. Future impacts of climate change appear to be diversified across forest categories. A strong change in forest regional distribution and local diversity is projected to take place, as some forest categories will find more suitable conditions in previously unsuitable locations, while for other categories the same new conditions will become less suited. A decrease in species diversity is projected in most of the area, with Alpine region showing the potentiality to become a refuge for species migration.
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Affiliation(s)
- Sergio Noce
- Foundation Euro‐Mediterranean Center on Climate Change (CMCC) – Impacts on Agriculture, Forests and Ecosystem Services (IAFES) DivisionViterboItaly
- Department for Innovation in Biological, Agro‐food and Forest systems (DIBAF)University of TusciaViterboItaly
| | - Alessio Collalti
- Foundation Euro‐Mediterranean Center on Climate Change (CMCC) – Impacts on Agriculture, Forests and Ecosystem Services (IAFES) DivisionViterboItaly
- CNR‐ISAFOM – National Research Council of ItalyInstitute for Agriculture and Forestry Systems in the MediterraneanRendeItaly
| | - Monia Santini
- Foundation Euro‐Mediterranean Center on Climate Change (CMCC) – Impacts on Agriculture, Forests and Ecosystem Services (IAFES) DivisionViterboItaly
- Far East Federal University (FEFU)VladivostokRussia
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55
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Koch LK, Kochmann J, Klimpel S, Cunze S. Modeling the climatic suitability of leishmaniasis vector species in Europe. Sci Rep 2017; 7:13325. [PMID: 29042642 PMCID: PMC5645347 DOI: 10.1038/s41598-017-13822-1] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 09/29/2017] [Indexed: 12/14/2022] Open
Abstract
Climate change will affect the geographical distribution of many species in the future. Phlebotomine sandflies are vector species for leishmaniasis, a tropical neglected disease. We applied an ensemble forecasting niche modeling approach to project future changes in climatic suitability for ten vector competent sandfly species in Europe. Whereas the main area of sandfly distribution currently lies in the Mediterranean region, models generally projected a northwards expansion of areas with suitable climatic conditions for most species (P. alexandri, P. neglectus, P. papatasi, P. perfiliewi, P. tobbi) in the future. The range of distribution for only two species (P. ariasi, P. mascittii) was projected to decline in the future. According to our results, a higher number of vector competent species in Central Europe can generally be expected, assuming no limitations to dispersal. We recommend monitoring for the establishment of vector species, especially in areas with projected climatic suitability for multiple vector species, as a precautious strategy. An increased number of vector species, or a higher abundance of a single species, might result in a higher transmission risk of leishmaniasis, provided that the pathogens follow the projected range shifts.
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Affiliation(s)
- Lisa K Koch
- Goethe-University, Institute of Ecology, Evolution and Diversity, Frankfurt/Main, D-60438, Germany.
- Senckenberg Gesellschaft für Naturforschung, Senckenberg Biodiversity and Climate Research Centre, Frankfurt/Main, D-60325, Germany.
| | - Judith Kochmann
- Goethe-University, Institute of Ecology, Evolution and Diversity, Frankfurt/Main, D-60438, Germany
- Senckenberg Gesellschaft für Naturforschung, Senckenberg Biodiversity and Climate Research Centre, Frankfurt/Main, D-60325, Germany
| | - Sven Klimpel
- Goethe-University, Institute of Ecology, Evolution and Diversity, Frankfurt/Main, D-60438, Germany
- Senckenberg Gesellschaft für Naturforschung, Senckenberg Biodiversity and Climate Research Centre, Frankfurt/Main, D-60325, Germany
| | - Sarah Cunze
- Goethe-University, Institute of Ecology, Evolution and Diversity, Frankfurt/Main, D-60438, Germany
- Senckenberg Gesellschaft für Naturforschung, Senckenberg Biodiversity and Climate Research Centre, Frankfurt/Main, D-60325, Germany
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56
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Mahony CR, Cannon AJ, Wang T, Aitken SN. A closer look at novel climates: new methods and insights at continental to landscape scales. GLOBAL CHANGE BIOLOGY 2017; 23:3934-3955. [PMID: 28145063 DOI: 10.1111/gcb.13645] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 01/18/2017] [Indexed: 05/12/2023]
Abstract
Novel climates - emerging conditions with no analog in the observational record - are an open problem in ecological modeling. Detecting extrapolation into novel conditions is a critical step in evaluating bioclimatic projections of how species and ecosystems will respond to climate change. However, biologically informed novelty detection methods remain elusive for many modeling algorithms. To assist with bioclimatic model design and evaluation, we present a first-approximation assessment of general novelty based on a simple and consistent characterization of climate. We build on the seminal global analysis of Williams et al. (2007 PNAS, 104, 5738) by assessing of end-of-21st-century novelty for North America at high spatial resolution and by refining their standardized Euclidean distance into an intuitive Mahalanobian metric called sigma dissimilarity. Like this previous study, we found extensive novelty in end-of-21st-century projections for the warm southern margin of the continent as well as the western Arctic. In addition, we detected localized novelty in lower topographic positions at all latitudes: By the end of the 21st century, novel climates are projected to emerge at low elevations in 80% and 99% of ecoregions in the RCP4.5 and RCP8.5 emissions scenarios, respectively. Novel climates are limited to 7% of the continent's area in RCP4.5, but are much more extensive in RCP8.5 (40% of area). These three risk factors for novel climates - regional susceptibility, topographic position, and the magnitude of projected climate change - represent a priori evaluation criteria for the credibility of bioclimatic projections. Our findings indicate that novel climates can emerge in any landscape. Interpreting climatic novelty in the context of nonlinear biological responses to climate is an important challenge for future research.
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Affiliation(s)
- Colin R Mahony
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, BC, V6T1Z4, Canada
| | - Alex J Cannon
- Environment and Climate Change Canada, 3800 Finnerty Rd, Victoria, BC, V8P 5C2, Canada
| | - Tongli Wang
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, BC, V6T1Z4, Canada
| | - Sally N Aitken
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, BC, V6T1Z4, Canada
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57
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The Effects of Climate Change on the Development of Tree Plantations for Biodiesel Production in China. FORESTS 2017. [DOI: 10.3390/f8060207] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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58
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Fourcade Y. Comparing species distributions modelled from occurrence data and from expert-based range maps. Implication for predicting range shifts with climate change. ECOL INFORM 2016. [DOI: 10.1016/j.ecoinf.2016.09.002] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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59
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Chaalali A, Beaugrand G, Raybaud V, Lassalle G, Saint-Béat B, Le Loc’h F, Bopp L, Tecchio S, Safi G, Chifflet M, Lobry J, Niquil N. From species distributions to ecosystem structure and function: A methodological perspective. Ecol Modell 2016. [DOI: 10.1016/j.ecolmodel.2016.04.022] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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60
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Estrada A, Delgado MP, Arroyo B, Traba J, Morales MB. Forecasting Large-Scale Habitat Suitability of European Bustards under Climate Change: The Role of Environmental and Geographic Variables. PLoS One 2016; 11:e0149810. [PMID: 26939133 PMCID: PMC4777476 DOI: 10.1371/journal.pone.0149810] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2015] [Accepted: 02/04/2016] [Indexed: 11/30/2022] Open
Abstract
We modelled the distribution of two vulnerable steppe birds, Otis tarda and Tetrax tetrax, in the Western Palearctic and projected their suitability up to the year 2080. We performed two types of models for each species: one that included environmental and geographic variables (space-included model) and a second one that only included environmental variables (space-excluded model). Our assumption was that ignoring geographic variables in the modelling procedure may result in inaccurate forecasting of species distributions. On the other hand, the inclusion of geographic variables may generate an artificial constraint on future projections. Our results show that space-included models performed better than space-excluded models. While distribution of suitable areas for T. tetrax in the future was approximately the same as at present in the space-included model, the space-excluded model predicted a pronounced geographic change of suitable areas for this species. In the case of O. tarda, the space-included model showed that many areas of current presence shifted to low or medium suitability in the future, whereas a northward expansion of intermediate suitable areas was predicted by the space-excluded one. According to the best models, current distribution of these species can restrict future distribution, probably due to dispersal constraints and site fidelity. Species ranges would be expected to shift gradually over the studied time period and, therefore, we consider it unlikely that most of the current distribution of these species in southern Europe will disappear in less than one hundred years. Therefore, populations currently occupying suitable areas should be a priority for conservation policies. Our results also show that climate-only models may have low explanatory power, and could benefit from adjustments using information on other environmental variables and biological traits; if the latter are not available, including the geographic predictor may improve the reliability of predicted results.
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Affiliation(s)
- Alba Estrada
- CIBIO/InBIO, Universidade de Évora, Évora, Portugal
- Instituto de Investigación en Recursos Cinegéticos—IREC (CSIC-UCLM-JCCM), Ciudad Real, Spain
- * E-mail:
| | - M. Paula Delgado
- Terrestrial Ecology Group (TEG), Department of Ecology, Universidad Autónoma de Madrid, Madrid, Spain
| | - Beatriz Arroyo
- Instituto de Investigación en Recursos Cinegéticos—IREC (CSIC-UCLM-JCCM), Ciudad Real, Spain
| | - Juan Traba
- Terrestrial Ecology Group (TEG), Department of Ecology, Universidad Autónoma de Madrid, Madrid, Spain
| | - Manuel B. Morales
- Terrestrial Ecology Group (TEG), Department of Ecology, Universidad Autónoma de Madrid, Madrid, Spain
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61
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Projected distribution shifts and protected area coverage of range-restricted Andean birds under climate change. Glob Ecol Conserv 2015. [DOI: 10.1016/j.gecco.2015.08.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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