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Mancini G, Santini L, Cazalis V, Akçakaya HR, Lucas PM, Brooks TM, Foden W, Di Marco M. A standard approach for including climate change responses in IUCN Red List assessments. Conserv Biol 2023:e14227. [PMID: 38111977 DOI: 10.1111/cobi.14227] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/18/2023] [Accepted: 10/05/2023] [Indexed: 12/20/2023]
Abstract
The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.
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Affiliation(s)
- Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
| | - Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - H Reşit Akçakaya
- Department of Ecology and Evolution, Stony Brook University, New York, New York, USA
- IUCN Species Survival Commission (SSC), Gland, Switzerland
| | - Pablo M Lucas
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
- Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Sevilla, Spain
| | - Thomas M Brooks
- IUCN Species Survival Commission (SSC), Gland, Switzerland
- World Agroforestry Center (ICRAF), University of The Philippines Los Baños, Los Baños, Philippines
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
| | - Wendy Foden
- Cape Research Centre, South African National Parks, Cape Town, South Africa
- Global Change Biology Group, Department of Botany and Zoology, University of Stellenbosch, Stellenbosch, South Africa
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
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2
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Karuno AP, Mi X, Chen Y, Zou DH, Gao W, Zhang BL, Xu W, Jin JQ, Shen WJ, Huang S, Zhou WW, Che J. Impacts of climate change on herpetofauna diversity in the Qinghai-Tibetan Plateau. Conserv Biol 2023; 37:e14155. [PMID: 37551770 DOI: 10.1111/cobi.14155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 06/07/2023] [Accepted: 06/12/2023] [Indexed: 08/09/2023]
Abstract
Although numerous studies on the impacts of climate change on biodiversity have been published, only a handful are focused on the intraspecific level or consider population-level models (separate models per population). We endeavored to fill this knowledge gap relative to the Qinghai-Tibetan plateau (QTP) by combining species distribution modeling (SDMs) with population genetics (i.e., population-level models) and phylogenetic methods (i.e., phylogenetic tree reconstruction and phylogenetic diversity analyses). We applied our models to 11 endemic and widely distributed herpetofauna species inhabiting high elevations in the QTP. We aimed to determine the influence of environmental heterogeneity on species' responses to climate change, the magnitude of climate-change impacts on intraspecific diversity, and the relationship between species range loss and intraspecific diversity losses under 2 shared socioeconomic pathways (SSP245 and SSP585) and 3 future periods (2050s, 2070s, and 2090s). The effects of global climatic change were more pronounced at the intraspecific level (22% of haplotypes lost and 36% of populations lost) than the morphospecies level in the SSP585 climate change scenario. Maintenance of genetic diversity was in general determined by a combination of factors including range changes, species genetic structure, and the part of the range predicted to be lost. This is owing to the fact that the loss and survival of populations were observed in species irrespective of the predicted range changes (contraction or expansion). In the southeast (mountainous regions), climate change had less of an effect on range size (>100% in 3 species) than in central and northern QTP plateau regions (range size <100% in all species). This may be attributed to environmental heterogeneity, which provided pockets of suitable climate in the southeast, whereas ecosystems in the north and central regions were homogeneous. Generally, our results imply that mountainous regions with high environmental heterogeneity and high genetic diversity may buffer the adverse impacts of climate change on species distribution and intraspecific diversity. Therefore, genetic structure and characteristics of the ecosystem may be crucial for conservation under climate change.
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Affiliation(s)
- Alex Plimo Karuno
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, P. R. China
| | - Xue Mi
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, P. R. China
| | - Youhua Chen
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, P. R. China
| | - Da-Hu Zou
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
- Research Center for Ecology, College of Science, Tibet University, Lhasa, P. R. China
| | - Wei Gao
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
| | - Bao-Lin Zhang
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
| | - Wei Xu
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
| | - Jie-Qiong Jin
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
| | - Wen-Jing Shen
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
| | - Song Huang
- College of Life Sciences, Anhui Normal University, Wuhu, P. R. China
| | - Wei-Wei Zhou
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
- State Key Laboratory of Grassland Agro-ecosystems, Institute of Innovation Ecology & College of Life Sciences, Lanzhou University, Lanzhou, P. R. China
| | - Jing Che
- State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, P. R. China
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3
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Welch H, Liu OR, Riekkola L, Abrahms B, Hazen EL, Samhouri JF. Selection of planning unit size in dynamic management strategies to reduce human-wildlife conflict. Conserv Biol 2023:e14201. [PMID: 37855129 DOI: 10.1111/cobi.14201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/01/2023] [Accepted: 09/28/2023] [Indexed: 10/20/2023]
Abstract
Conservation planning traditionally relies upon static reserves; however, there is increasing emphasis on dynamic management (DM) strategies that are flexible in space and time. Due to its novelty, DM lacks best practices to guide design and implementation. We assessed the effect of planning unit size in a DM tool designed to reduce entanglement of protected whales in vertical ropes of surface buoys attached to crab traps in the lucrative U.S. Dungeness crab (Metacarcinus magister) fishery. We conducted a retrospective analysis from 2009 to 2019 with modeled distributions of blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales and observed fisheries effort and revenue to evaluate the effect of 7 planning unit sizes on DM tool performance. We measured performance as avoided whale entanglement risk and protected fisheries revenue. Small planning units avoided up to $47 million of revenue loss and reduced entanglement risk by up to 25% compared to the large planning units currently in use by avoiding the incidental closure of areas with low biodiversity value and high fisheries revenue. However, large planning units were less affected by an unprecedented marine heat wave in 2014-2016 and by delays in information on the distributions of whales and the fishery. Our findings suggest that the choice of planning unit size will require decision-makers to navigate multiple socioecological considerations-rather than a one-size-fits-all approach-to separate wildlife from threats under a changing climate.
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Affiliation(s)
- Heather Welch
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Monterey, California, USA
- Institute of Marine Sciences, University of California, Santa Cruz, Santa Cruz, California, USA
| | - Owen R Liu
- NRC Research Associateship Program, Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington, USA
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington, USA
- Ocean Associates, Inc., Arlington, Virginia, USA
| | - Leena Riekkola
- NRC Research Associateship Program, Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington, USA
| | - Briana Abrahms
- Center for Ecosystem Sentinels, Department of Biology, University of Washington, Seattle, Washington, USA
| | - Elliott L Hazen
- Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Monterey, California, USA
- Institute of Marine Sciences, University of California, Santa Cruz, Santa Cruz, California, USA
| | - Jameal F Samhouri
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington, USA
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4
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Valente JJ, Rivers JW, Yang Z, Nelson SK, Northrup JM, Roby DD, Meyer CB, Betts MG. Fragmentation effects on an endangered species across a gradient from the interior to edge of its range. Conserv Biol 2023; 37:e14091. [PMID: 37021393 DOI: 10.1111/cobi.14091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 05/26/2023]
Abstract
Understanding how habitat fragmentation affects individual species is complicated by challenges associated with quantifying species-specific habitat and spatial variability in fragmentation effects within a species' range. We aggregated a 29-year breeding survey data set for the endangered marbled murrelet (Brachyramphus marmoratus) from >42,000 forest sites throughout the Pacific Northwest (Oregon, Washington, and northern California) of the United States. We built a species distribution model (SDM) in which occupied sites were linked with Landsat imagery to quantify murrelet-specific habitat and then used occupancy models to test the hypotheses that fragmentation negatively affects murrelet breeding distribution and that these effects are amplified with distance from the marine foraging habitat toward the edge of the species' nesting range. Murrelet habitat declined in the Pacific Northwest by 20% since 1988, whereas the proportion of habitat comprising edges increased by 17%, indicating increased fragmentation. Furthermore, fragmentation of murrelet habitat at landscape scales (within 2 km of survey stations) negatively affected occupancy of potential breeding sites, and these effects were amplified near the range edge. On the coast, the odds of occupancy decreased by 37% (95% confidence interval [CI] -54 to 12) for each 10% increase in edge habitat (i.e., fragmentation), but at the range edge (88 km inland) these odds decreased by 99% (95% CI 98 to 99). Conversely, odds of murrelet occupancy increased by 31% (95% CI 14 to 52) for each 10% increase in local edge habitat (within 100 m of survey stations). Avoidance of fragmentation at broad scales but use of locally fragmented habitat with reduced quality may help explain the lack of murrelet population recovery. Further, our results emphasize that fragmentation effects can be nuanced, scale dependent, and geographically variable. Awareness of these nuances is critical for developing landscape-level conservation strategies for species experiencing broad-scale habitat loss and fragmentation.
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Affiliation(s)
- Jonathon J Valente
- Department of Forest Engineering, Resources, and Management, Oregon State University, Corvallis, Oregon, USA
- U.S. Geological Survey, Alabama Cooperative Fish and Wildlife Research Unit, College of Forestry, Wildlife and Environment, Auburn University, Auburn, Alabama, USA
| | - James W Rivers
- Department of Forest Engineering, Resources, and Management, Oregon State University, Corvallis, Oregon, USA
| | - Zhiqiang Yang
- U.S. Department of Agriculture Forest Service, Rocky Mountain Research Station, Ogden, Utah, USA
| | - S Kim Nelson
- Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, Oregon, USA
| | - Joseph M Northrup
- Wildlife Research and Monitoring Section, Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry, and Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
| | - Daniel D Roby
- Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, Oregon, USA
| | | | - Matthew G Betts
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, Oregon, USA
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5
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Sales LP, Pires MM. Identifying climate change refugia for South American biodiversity. Conserv Biol 2023:e14087. [PMID: 36919472 DOI: 10.1111/cobi.14087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 02/16/2023] [Accepted: 03/07/2023] [Indexed: 06/07/2023]
Abstract
Refugia-based conservation offers long-term effectiveness and minimize uncertainty on strategies for climate change adaptation. We used distribution modelling to identify climate change refugia for 617 terrestrial mammals and to quantify the role of protected areas (PAs) in providing refugia across South America. To do so, we compared species potential distribution across different scenarios of climate change, highlighting those regions likely to retain suitable climatic conditions by year 2090, and explored the proportion of refugia inside PAs. Moist tropical forests in high-elevation areas with complex topography concentrated the highest local diversity of species refugia, although regionally important refugia centers occurred elsewhere. Andean-Amazon forests contained climate change refugia for more than half of the continental species' pool and for up to 87 species locally (17 × 17 km2 grid cell). The highlands of the southern Atlantic Forest also included megadiverse refugia for up to 76 species per cell. Almost half of the species that may find refugia in the Atlantic Forest will do so in a single region-the Serra do Mar and Serra do Espinhaço. Most of the refugia we identified, however, were not in PAs, which may contain <6% of the total area of climate change refugia, leaving 129-237 species with no refugia inside the territorial limits of PAs of any kind. Our results reveal a dismal scenario for the level of refugia protection in some of the most biodiverse regions of the world. Nonetheless, because refugia tend to be in high-elevation, topographically complex, and remote areas, with lower anthropogenic pressure, formally protecting them may require a comparatively modest investment.
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Affiliation(s)
- Lilian P Sales
- Department of Animal Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
- Department of Biology, Faculty of Arts and Science, Concordia University, Montreal, Quebec, Canada
| | - Mathias M Pires
- Department of Animal Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
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6
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Mi C, Huettmann F, Li X, Jiang Z, Du W, Sun B. Effects of climate and human activity on the current distribution of amphibians in China. Conserv Biol 2022; 36:e13964. [PMID: 35674098 DOI: 10.1111/cobi.13964] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 05/22/2022] [Accepted: 05/25/2022] [Indexed: 06/15/2023]
Abstract
In China, as elsewhere, amphibians are highly endangered. Anthropogenic environmental change has affected the distribution and population dynamics of species, and species distributions at a broad scale are strongly driven by climate and species' ability to disperse. Yet, current knowledge remains limited on how widespread human activity affects the distribution patterns of amphibians in China and whether this effect extends beyond climate. We compiled a relatively comprehensive database on the distribution of 196 amphibian species in China from the literature, public databases, and field data. We obtained 25,826 records on almost 50% of known species in China. To test how environmental factors and human activities influence the current distribution of amphibians (1960-1990), we used range filling, which is species realized ranges relative to their potential climate distribution. We used all species occurrence records to represent realized range and niche models to predict potential distribution range. To reduce uncertainty, we used 3 regression methods (beta regression, generalized boosted regression models, and random forest) to test the associations of species range filling with human activity, climate, topography, and range size. The results of the 3 approaches were consistent. At the species level, mean annual precipitation (climate) had the most effect on spatial distribution pattern of amphibians in China, followed by range size. Human activity ranked last. At the spatial level, mean annual precipitation remained the most important factor. Regions in southeastern of China that are currently moist supported the highest amphibian diversity, but were predicted to experience a decline in precipitation under climate change scenarios. Consequently, the distributions of amphibians will likely shift to the northwest in the future, which could affect future conservation efforts.
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Affiliation(s)
- Chunrong Mi
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Falk Huettmann
- EWHALE Lab, Department of Biology and Wildlife, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, Alaska, USA
| | - Xinhai Li
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Zhongwen Jiang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Weiguo Du
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Baojun Sun
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
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7
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Gaisberger H, Fremout T, Kettle CJ, Vinceti B, Kemalasari D, Kanchanarak T, Thomas E, Serra-Diaz JM, Svenning JC, Slik F, Eiadthong W, Palanisamy K, Ravikanth G, Bodos V, Sang J, Warrier RR, Wee AKS, Elloran C, Ramos LT, Henry M, Hossain MA, Theilade I, Laegaard S, Bandara KMA, Weerasinghe DP, Changtragoon S, Yuskianti V, Wilkie P, Nghia NH, Elliott S, Pakkad G, Tiansawat P, Maycock C, Bounithiphonh C, Mohamed R, Nazre M, Siddiqui BN, Lee SL, Lee CT, Zakaria NF, Hartvig I, Lehmann L, David DBD, Lillesø JPB, Phourin C, Yongqi Z, Ping H, Volkaert HA, Graudal L, Hamidi A, Thea S, Sreng S, Boshier D, Tolentino E, Ratnam W, Aung MM, Galante M, Isa SFM, Dung NQ, Hoa TT, Le TC, Miah MD, Zuhry ALM, Alawathugoda D, Azman A, Pushpakumara G, Sumedi N, Siregar IZ, Nak HK, Linsky J, Barstow M, Koh LP, Jalonen R. Tropical and subtropical Asia's valued tree species under threat. Conserv Biol 2022; 36:e13873. [PMID: 34865262 DOI: 10.1111/cobi.13873] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/14/2021] [Accepted: 11/25/2021] [Indexed: 06/13/2023]
Abstract
Tree diversity in Asia's tropical and subtropical forests is central to nature-based solutions. Species vulnerability to multiple threats, which affect provision of ecosystem services, is poorly understood. We conducted a region-wide, spatially explicit assessment of the vulnerability of 63 socioeconomically important tree species to overexploitation, fire, overgrazing, habitat conversion, and climate change. Trees were selected for assessment from national priority lists, and selections were validated by an expert network representing 20 countries. We used Maxent suitability modeling to predict species distribution ranges, freely accessible spatial data sets to map threat exposures, and functional traits to estimate threat sensitivities. Species-specific vulnerability maps were created as the product of exposure maps and sensitivity estimates. Based on vulnerability to current threats and climate change, we identified priority areas for conservation and restoration. Overall, 74% of the most important areas for conservation of these trees fell outside protected areas, and all species were severely threatened across an average of 47% of their native ranges. The most imminent threats were overexploitation and habitat conversion; populations were severely threatened by these factors in an average of 24% and 16% of their ranges, respectively. Our model predicted limited overall climate change impacts, although some study species were likely to lose over 15% of their habitat by 2050 due to climate change. We pinpointed specific natural areas in Borneo rain forests as hotspots for in situ conservation of forest genetic resources, more than 82% of which fell outside designated protected areas. We also identified degraded areas in Western Ghats, Indochina dry forests, and Sumatran rain forests as hotspots for restoration, where planting or assisted natural regeneration will help conserve these species, and croplands in southern India and Thailand as potentially important agroforestry options. Our results highlight the need for regionally coordinated action for effective conservation and restoration.
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Affiliation(s)
- Hannes Gaisberger
- Bioversity International, Rome, Italy
- Department of Geoinformatics, Paris Lodron University of Salzburg, Salzburg, Austria
| | - Tobias Fremout
- Division of Forest, Nature and Landscape, KU Leuven, Leuven-Heverlee, Belgium
- Bioversity International, La Molina, Peru
| | - Chris J Kettle
- Bioversity International, Rome, Italy
- Department of Environmental System Science, ETH Zurich, Zurich, Switzerland
| | | | - Della Kemalasari
- Bioversity International, Universiti Putra Malaysia Off Lebuh Silikon, Selangor, Malaysia
| | - Tania Kanchanarak
- Bioversity International, Universiti Putra Malaysia Off Lebuh Silikon, Selangor, Malaysia
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | | | | | - Jens-Christian Svenning
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Ferry Slik
- Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, Brunei Darussalam
| | | | | | | | - Vilma Bodos
- Forest Department Sarawak, Bangunan Baitul Makmur II, Kuching, Malaysia
| | - Julia Sang
- Forest Department Sarawak, Bangunan Baitul Makmur II, Kuching, Malaysia
| | - Rekha R Warrier
- Institute of Forest Genetics and Tree Breeding, Tamil Nadu, India
| | - Alison K S Wee
- School of Environmental and Geographical Sciences, University of Nottingham Malaysia Campus, Semenyih, Malaysia
- Selangor Darul Ehsan, Malaysia and College of Forestry, Guangxi University, Nanning, People's Republic of China
| | | | | | - Matieu Henry
- Food and Agriculture Organization of the United Nations (FAO), Dhaka, Bangladesh
| | - Md Akhter Hossain
- Institute of Forestry and Environmental Sciences, University of Chittagong, Chittagong, Bangladesh
| | - Ida Theilade
- Department of Food and Resource Economics, University of Copenhagen, Frederiksberg C, Denmark
| | | | - K M A Bandara
- Sri Lanka Forestry Institute, Nuwara Eliya, Sri Lanka
| | | | | | - Vivi Yuskianti
- Forest Research and Development Center (FRDC), Bogor, Indonesia
| | | | | | - Stephen Elliott
- Forest Restoration Research Unit, Biology Department and Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Greuk Pakkad
- Forest Restoration Research Unit, Biology Department and Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Pimonrat Tiansawat
- Forest Restoration Research Unit, Biology Department and Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Colin Maycock
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Malaysia
| | - Chaloun Bounithiphonh
- Forest Research Center, National Agriculture and Forestry Research Institute, Xaythany District, Lao P.D.R
| | - Rozi Mohamed
- Faculty of Forestry & Environment, Universiti Putra Malaysia, UPM Serdang, Malaysia
| | - M Nazre
- Faculty of Forestry & Environment, Universiti Putra Malaysia, UPM Serdang, Malaysia
| | | | - Soon-Leong Lee
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | - Chai-Ting Lee
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | - Nurul Farhanah Zakaria
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | - Ida Hartvig
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Smithsonian Environmental Research Center, Smithsonian Institute, Washington, DC, USA
| | - Lutz Lehmann
- Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Bonn, Germany
| | | | | | - Chhang Phourin
- Institute of Forest and Wildlife Research and Development, Khan Sen Sokh, Cambodia
| | - Zheng Yongqi
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Huang Ping
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Hugo A Volkaert
- Center for Agricultural Biotechnology, Kasetsart University Kamphaengsaen Campus, Mu6 Malaimaen Rd, Kamphaengsaen Nakhonpathom 73140, Thailand, Lat Yao, Thailand
| | - Lars Graudal
- Department of Food and Resource Economics, University of Copenhagen, Frederiksberg C, Denmark
- World Agroforestry Center (ICRAF), United Nations Avenue, Nairobi, Kenya
| | - Arief Hamidi
- Fauna and Flora International, Nusa Tenggara, Indonesia
| | - So Thea
- Institute of Forest and Wildlife Research and Development, Khan Sen Sokh, Cambodia
| | - Sineath Sreng
- Institute of Forest and Wildlife Research and Development, Khan Sen Sokh, Cambodia
| | | | - Enrique Tolentino
- University of the Philippines Los Baños, College, Laguna 4031, Philippines, Los Baños, Philippines
| | | | - Mu Mu Aung
- Forest Department Myanmar, Mon State, Myanmar
| | - Michael Galante
- Climate Forestry Limited, Kensington Gardens, Labuan, Malaysia
| | - Siti Fatimah Md Isa
- Department of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang, Malaysia
| | - Nguyen Quoc Dung
- Forest Inventory and Planning Institute, Quy hoạch Rừng, Vietnam
| | - Tran Thi Hoa
- Institute of Agricultural Genetics (AGI), Forest Genetics and Conservation, Vietnamese Academy of Agricultural Sciences, Hanoi, Vietnam
| | - Tran Chan Le
- Institute of Agricultural Genetics (AGI), Forest Genetics and Conservation, Vietnamese Academy of Agricultural Sciences, Hanoi, Vietnam
| | | | | | | | - Amelia Azman
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | | | - Nur Sumedi
- Forest Research and Development Center (FRDC), Bogor, Indonesia
| | | | - Hong Kyung Nak
- Forest Bioinformation Division, National Institute of Forest Science (NIFOS), Seoul, Republic of Korea
| | - Jean Linsky
- Atlanta Botanical Garden, Atlanta, Georgia, USA
| | - Megan Barstow
- Botanic Gardens Conservation International, Richmond, UK
| | - Lian Pin Koh
- Centre for Nature-based Climate Solutions, and Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Riina Jalonen
- Bioversity International, Universiti Putra Malaysia Off Lebuh Silikon, Selangor, Malaysia
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8
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Gilbert NA, Clare JDJ, Stenglein JL, Zuckerberg B. Abundance estimation of unmarked animals based on camera-trap data. Conserv Biol 2021; 35:88-100. [PMID: 32297655 DOI: 10.1111/cobi.13517] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 04/02/2020] [Accepted: 04/10/2020] [Indexed: 06/11/2023]
Abstract
The rapid improvement of camera traps in recent decades has revolutionized biodiversity monitoring. Despite clear applications in conservation science, camera traps have seldom been used to model the abundance of unmarked animal populations. We sought to summarize the challenges facing abundance estimation of unmarked animals, compile an overview of existing analytical frameworks, and provide guidance for practitioners seeking a suitable method. When a camera records multiple detections of an unmarked animal, one cannot determine whether the images represent multiple mobile individuals or a single individual repeatedly entering the camera viewshed. Furthermore, animal movement obfuscates a clear definition of the sampling area and, as a result, the area to which an abundance estimate corresponds. Recognizing these challenges, we identified 6 analytical approaches and reviewed 927 camera-trap studies published from 2014 to 2019 to assess the use and prevalence of each method. Only about 5% of the studies used any of the abundance-estimation methods we identified. Most of these studies estimated local abundance or covariate relationships rather than predicting abundance or density over broader areas. Next, for each analytical approach, we compiled the data requirements, assumptions, advantages, and disadvantages to help practitioners navigate the landscape of abundance estimation methods. When seeking an appropriate method, practitioners should evaluate the life history of the focal taxa, carefully define the area of the sampling frame, and consider what types of data collection are possible. The challenge of estimating abundance of unmarked animal populations persists; although multiple methods exist, no one method is optimal for camera-trap data under all circumstances. As analytical frameworks continue to evolve and abundance estimation of unmarked animals becomes increasingly common, camera traps will become even more important for informing conservation decision-making.
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Affiliation(s)
- Neil A Gilbert
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, U.S.A
| | - John D J Clare
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, U.S.A
| | - Jennifer L Stenglein
- Wisconsin Department of Natural Resources, 2901 Progress Drive, Madison, WI, 53716, U.S.A
| | - Benjamin Zuckerberg
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, U.S.A
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9
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Bellis J, Bourke D, Maschinski J, Heineman K, Dalrymple S. Climate suitability as a predictor of conservation translocation failure. Conserv Biol 2020; 34:1473-1481. [PMID: 32304113 DOI: 10.1111/cobi.13518] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 04/03/2020] [Accepted: 04/10/2020] [Indexed: 05/28/2023]
Abstract
The continuing decline and loss of biodiversity has caused an increase in the use of interventionist conservation tools, such as translocation. However, many translocation attempts fail to establish viable populations, with poor release site selection often flagged as an inhibitor of success. We used species distribution models (SDMs) to predict the climate suitability of 102 release sites for amphibians, reptiles, and terrestrial insects and compared suitability predictions between successful and failed attempts. We then quantified the importance of climate suitability relative to 5 other variables frequently considered in the literature as important determinants of translocation success: number of release years, number of individuals released, life stage released, origin of the source population, and position of the release site relative to the species' range. Probability of translocation success increased as predicted climate suitability increased and this effect was the strongest among the variables we considered, accounting for 48.3% of the variation in translocation outcome. These findings should encourage greater consideration of climate suitability when selecting release sites for conservation translocations and we advocate the use of SDMs as an effective way to do this.
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Affiliation(s)
- Joe Bellis
- School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool, L3 3AF, U.K
| | - David Bourke
- School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool, L3 3AF, U.K
| | - Joyce Maschinski
- San Diego Zoo Global and Center for Plant Conservation, 15600 San Pasqual Valley Road, Escondido, CA, 92027, U.S.A
| | - Katie Heineman
- San Diego Zoo Global and Center for Plant Conservation, 15600 San Pasqual Valley Road, Escondido, CA, 92027, U.S.A
| | - Sarah Dalrymple
- School of Biological and Environmental Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool, L3 3AF, U.K
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10
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Mainali K, Hefley T, Ries L, Fagan WF. Matching expert range maps with species distribution model predictions. Conserv Biol 2020; 34:1292-1304. [PMID: 32115748 PMCID: PMC7540670 DOI: 10.1111/cobi.13492] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 02/17/2020] [Accepted: 02/21/2020] [Indexed: 05/19/2023]
Abstract
Species' range maps based on expert opinion are a critical resource for conservation planning. Expert maps are usually accompanied by species descriptions that specify sources of internal range heterogeneity, such as habitat associations, but these are rarely considered when using expert maps for analyses. We developed a quantitative metric (expert score) to evaluate the agreement between an expert map and a habitat probability surface obtained from a species distribution model. This method rewards both the avoidance of unsuitable sites and the inclusion of suitable sites in the expert map. We obtained expert maps of 330 butterfly species from each of 2 widely used North American sources (Glassberg [1999, 2001] and Scott [1986]) and computed species-wise expert scores for each. Overall, the Glassberg maps secured higher expert scores than Scott (0.61 and 0.41, respectively) due to the specific rules (e.g., Glassberg only included regions where the species was known to reproduce whereas Scott included all areas a species expanded to each year) they used to include or exclude areas from ranges. The predictive performance of expert maps was almost always hampered by the inclusion of unsuitable sites, rather than by exclusion of suitable sites (deviance outside of expert maps was extremely low). Map topology was the primary predictor of expert performance rather than any factor related to species characteristics such as mobility. Given the heterogeneity and discontinuity of suitable landscapes, expert maps drawn with more detail are more likely to agree with species distribution models and thus minimize both commission and omission errors.
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Affiliation(s)
- Kumar Mainali
- Department of BiologyUniversity of Maryland1210 Biology‐Psychology BuildingCollege ParkMD20742U.S.A.
| | - Trevor Hefley
- Department of StatisticsKansas State University205 Dickens Hall, 1116 Mid‐Campus Drive NorthManhattanKS66506U.S.A.
| | - Leslie Ries
- Department of BiologyGeorgetown UniversityReiss Science Building, Room 406, 37th and O StreetsWashington DCNW20057U.S.A.
| | - William F. Fagan
- Department of BiologyUniversity of Maryland1210 Biology‐Psychology BuildingCollege ParkMD20742U.S.A.
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11
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Taylor AT, Papeş M, Long JM. Incorporating fragmentation and non-native species into distribution models to inform fluvial fish conservation. Conserv Biol 2018; 32:171-182. [PMID: 28877382 DOI: 10.1111/cobi.13024] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 07/12/2017] [Accepted: 09/01/2017] [Indexed: 06/07/2023]
Abstract
Fluvial fishes face increased imperilment from anthropogenic activities, but the specific factors contributing most to range declines are often poorly understood. For example, the range of the fluvial-specialist shoal bass (Micropterus cataractae) continues to decrease, yet how perceived threats have contributed to range loss is largely unknown. We used species distribution models to determine which factors contributed most to shoal bass range loss. We estimated a potential distribution based on natural abiotic factors and a series of currently occupied distributions that incorporated variables characterizing land cover, non-native species, and river fragmentation intensity (no fragmentation, dams only, and dams and large impoundments). We allowed interspecific relationships between non-native congeners and shoal bass to vary across fragmentation intensities. Results from the potential distribution model estimated shoal bass presence throughout much of their native basin, whereas models of currently occupied distribution showed that range loss increased as fragmentation intensified. Response curves from models of currently occupied distribution indicated a potential interaction between fragmentation intensity and the relationship between shoal bass and non-native congeners, wherein non-natives may be favored at the highest fragmentation intensity. Response curves also suggested that >100 km of interconnected, free-flowing stream fragments were necessary to support shoal bass presence. Model evaluation, including an independent validation, suggested that models had favorable predictive and discriminative abilities. Similar approaches that use readily available, diverse, geospatial data sets may deliver insights into the biology and conservation needs of other fluvial species facing similar threats.
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Affiliation(s)
- Andrew T Taylor
- Department of Natural Resource Ecology and Management, Oklahoma State University, 007 Agriculture Hall, Stillwater, OK 74078, U.S.A
| | - Monica Papeş
- Department of Integrative Biology, Oklahoma State University, Stillwater, OK 74078, U.S.A
| | - James M Long
- U.S. Geological Survey, Oklahoma Cooperative Fish and Wildlife Research Unit, Department of Natural Resource Ecology and Management, Oklahoma State University, 007 Agriculture Hall, Stillwater, OK 74078, U.S.A
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