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Charre‐Medellín JF, Ferrer‐Ferrando D, Monterrubio‐Rico TC, Fernández‐López J, Acevedo P. Using species distribution modeling to generate relative abundance information in socio-politically unstable territories: Conservation of Felidae in the central-western region of Mexico. Ecol Evol 2023; 13:e10534. [PMID: 37727774 PMCID: PMC10505758 DOI: 10.1002/ece3.10534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/30/2023] [Accepted: 09/04/2023] [Indexed: 09/21/2023] Open
Abstract
The distribution range and population abundance of species provide fundamental information on the species-habitat relationship required for management and conservation. Abundance inherently provides more information about the ecology of species than do occurrence data. However, information on abundance is scarce for most species, mainly at large spatial scales. The objective of this work was, therefore, to provide information regarding the population status of six wild felids inhabiting territories in Mexico that are inaccessible or politically unstable. This was done using species distribution models derived from occurrence data. We used distribution data at a continental scale for the wild felids inhabiting Mexico: jaguar (Panthera onca), bobcat (Lynx rufus), ocelot (Leopardus pardalis), cougar (Puma concolor), margay (Leopardus wiedii), and jaguarundi (Herpailurus yagouaroundi) to predict environmental suitability (estimated by both Maxent and the distance to niche centroid, DNC). Suitability was then examined by relating to a capture rate-based index, in a well-monitored area in central western Mexico in order to assess their performance as proxies of relative abundance. Our results indicate that the environmental suitability patterns predicted by both algorithms were comparable. However, the strength of the relationship between the suitability and relative abundance of local populations differed across species and between algorithms, with the bobcat and DNC, respectively, having the best fit, although the relationship was not consistent in all the models. This paper presents the potential of implementing species distribution models in order to predict the relative abundance of wild felids in Mexico and offers guidance for the proper interpretation of the relationship between suitability and population abundance. The results obtained provide a robust information base on which to outline specific conservation actions and on which to examine the potential status of endangered species inhabiting remote or politically unstable territories in which on-field monitoring programs are not feasible.
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Affiliation(s)
- Juan F. Charre‐Medellín
- National School of Higher StudiesUniversidad Nacional Autónoma de MéxicoMoreliaMexico
- Laboratory of Priority Terrestrial Vertebrates, Faculty of BiologyUniversidad Michoacana de San Nicolás de HidalgoMoreliaMexico
| | - David Ferrer‐Ferrando
- Instituto de Investigación en Recursos Cinegéticos (IREC), CSIC‐UCLM‐JCCMCiudad RealSpain
| | - Tiberio C. Monterrubio‐Rico
- Laboratory of Priority Terrestrial Vertebrates, Faculty of BiologyUniversidad Michoacana de San Nicolás de HidalgoMoreliaMexico
| | | | - Pelayo Acevedo
- Instituto de Investigación en Recursos Cinegéticos (IREC), CSIC‐UCLM‐JCCMCiudad RealSpain
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2
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Monnier-Corbel A, Robert A, Hingrat Y, Benito BM, Monnet AC. Species Distribution Models predict abundance and its temporal variation in a steppe bird population. Glob Ecol Conserv 2023. [DOI: 10.1016/j.gecco.2023.e02442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023] Open
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3
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Drake J, Lambin X, Sutherland C. Spatiotemporal connectivity dynamics in spatially structured populations. J Anim Ecol 2022; 91:2050-2060. [PMID: 35871483 PMCID: PMC9796704 DOI: 10.1111/1365-2656.13783] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/17/2022] [Indexed: 01/07/2023]
Abstract
Connectivity is a fundamental concept linking dispersal to the emergent dynamics and persistence of spatially structured populations. Functional measures of connectivity typically seek to integrate aspects of landscape structure and animal movement to describe ecologically meaningful connectedness at the landscape and population scale. Despite this focus on function, traditional measures of landscape connectivity assume it is a static property of the landscape, hence abstracting out the underlying spatiotemporal population dynamics. Connectivity is, arguably, a dynamic property of landscapes, and is inherently related to the spatial distribution of individuals and populations across the landscape. Static representations of connectivity potentially overlook this variation and therefore adopting a dynamic approach should offer improved insights about connectivity and associated ecological processes. Using a large-scale, long-term time series of occupancy data from a metapopulation of water voles Arvicola amphibius, we tested competing hypotheses about how considering the dynamic nature of connectivity improves the ability of spatially explicit occupancy models to recover population dynamics. Iteratively relaxing standing assumptions of connectivity metrics, these models ranged from spatially and temporally fixed connectivity metrics that are widely applied, to the more flexible, but lesser used model that allowed temporally varying connectivity measures that incorporate spatiotemporally dynamic patch occupancy states. Our results provide empirical evidence that demographic weighting using patch occupancy dynamics and temporal variability in connectivity measures are important for describing metapopulation dynamics. We highlight the implications of commonly held assumption in connectivity modelling and demonstrate how they result in different and highly variable predictions of metapopulation capacity. Thus, we argue that the concept of connectivity and its potential applications would benefit from recognizing inherent spatiotemporal variation in connectivity that is explicitly linked to underlying ecological state variables.
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Affiliation(s)
- Joseph Drake
- Department of Environmental ConservationUniversity of Massachusetts‐AmherstAmherstMAUSA,Organismal and Evolutionary Biology Interdisciplinary ProgramUniversity of Massachusetts‐AmherstAmherstMAUSA
| | - Xavier Lambin
- School of Biological SciencesUniversity or AberdeenAberdeenUK
| | - Chris Sutherland
- Department of Environmental ConservationUniversity of Massachusetts‐AmherstAmherstMAUSA,Centre for Research into Ecological and Environmental ModellingUniversity of St AndrewsSt AndrewsUK
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4
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Gutiérrez-Molina R, Acevedo P, Sánchez-Montes S, Romero-Salas D, López-Ortiz S, Flores-Primo A, Cruz-Romero A. Spatial epidemiology of Leptospira sp. exposure in bovines from Veracruz, México. Transbound Emerg Dis 2022; 69:e682-e692. [PMID: 34657392 DOI: 10.1111/tbed.14346] [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: 05/24/2021] [Revised: 11/01/2020] [Accepted: 10/03/2021] [Indexed: 11/28/2022]
Abstract
Bovine leptospirosis is a bacterial disease that affects cattle herds, causing economic losses due to reproductive problems which require expensive treatments. The main source of transmission for cattle is still uncertain, but rodents and bats can play an important role in the transmission cycle by being maintenance hosts for the pathogenic species of the bacterium and spreading it through urine. In this study, we characterize possible risk areas for bovine leptospirosis exposure in the state of Veracruz, Mexico, based on the geographical distribution of flying (bats) and terrestrial (rodents and opossums) wild hosts of Leptospira sp. reported in Mexico, in addition to climate, geography, soil characteristics, land use and human activities (environmental variables). We used a generalized linear regression model to understand the association between the frequency of anti-Leptospira sp. antibodies (a proxy of exposure) in cattle herds exposed to Leptospira, the favourability of wild hosts of Leptospira as well as the environmental variables. The parameterized model explained 12.3% of the variance. The frequency of anti-Leptospira sp. antibodies exposure in cattle herds was associated with elevation, geographic longitude, pH of the soil surface and environmental favourability for the presence of rodents, opossums and bats. The variation in exposure was mainly explained by a longitudinal gradient (6.4% of the variance) and the favourability-based indices for wild hosts (9.6% of the variance). Describing the possible risks for exposure to Leptospira in an important and neglected livestock geographical region, we provide valuable information for the selection of areas for diagnosis and prevention of this relevant disease.
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Affiliation(s)
| | - Pelayo Acevedo
- Instituto de Investigación en Recursos Cinegéticos, IREC (UCLM-CSIC-JCCM), Ciudad Real, Spain
| | - Sokani Sánchez-Montes
- Facultad de Ciencias Biológicas y Agropecuarias región Tuxpan, Universidad Veracruzana, Tuxpan, Veracruz, México
- Centro de Medicina Tropical, Unidad de Investigación en Medicina Experimental, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, México
| | - Dora Romero-Salas
- Facultad de Medicina Veterinaria y Zootecnia, Universidad Veracruzana, Veracruz, México
| | | | - Argel Flores-Primo
- Facultad de Medicina Veterinaria y Zootecnia, Universidad Veracruzana, Veracruz, México
| | - Anabel Cruz-Romero
- Facultad de Medicina Veterinaria y Zootecnia, Universidad Veracruzana, Veracruz, México
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5
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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. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2022; 36:e13873. [PMID: 34865262 DOI: 10.1111/cobi.13873] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [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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6
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Density-dependence of reproductive success in a Houbara bustard population. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2022.e02071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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7
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Monnier‐Corbel A, Monnet A, Hingrat Y, Robert A. Patterns of abundance reveal evidence of translocation and climate effects on Houbara bustard population recovery. Anim Conserv 2021. [DOI: 10.1111/acv.12738] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- A. Monnier‐Corbel
- Centre d'Ecologie et des Sciences de la Conservation (CESCO) Muséum National d'Histoire Naturelle Centre National de la Recherche Scientifique Sorbonne Université Paris France
- Emirates Center for Wildlife Propagation Missour Morocco
| | - A.‐C. Monnet
- Centre d'Ecologie et des Sciences de la Conservation (CESCO) Muséum National d'Histoire Naturelle Centre National de la Recherche Scientifique Sorbonne Université Paris France
| | - Y. Hingrat
- RENECO International Wildlife Consultants LLC Abu Dhabi United Arab Emirates
| | - A. Robert
- Centre d'Ecologie et des Sciences de la Conservation (CESCO) Muséum National d'Histoire Naturelle Centre National de la Recherche Scientifique Sorbonne Université Paris France
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Thomas SM, Verhoeven MR, Walsh JR, Larkin DJ, Hansen GJA. Species distribution models for invasive Eurasian watermilfoil highlight the importance of data quality and limitations of discrimination accuracy metrics. Ecol Evol 2021; 11:12567-12582. [PMID: 34594521 PMCID: PMC8462136 DOI: 10.1002/ece3.8002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 06/20/2021] [Accepted: 07/19/2021] [Indexed: 11/12/2022] Open
Abstract
AIM Availability of uniformly collected presence, absence, and abundance data remains a key challenge in species distribution modeling (SDM). For invasive species, abundance and impacts are highly variable across landscapes, and quality occurrence and abundance data are critical for predicting locations at high risk for invasion and impacts, respectively. We leverage a large aquatic vegetation dataset comprising point-level survey data that includes information on the invasive plant Myriophyllum spicatum (Eurasian watermilfoil) to: (a) develop SDMs to predict invasion and impact from environmental variables based on presence-absence, presence-only, and abundance data, and (b) compare evaluation metrics based on functional and discrimination accuracy for presence-absence and presence-only SDMs. LOCATION Minnesota, USA. METHODS Eurasian watermilfoil presence-absence and abundance information were gathered from 468 surveyed lakes, and 801 unsurveyed lakes were leveraged as pseudoabsences for presence-only models. A Random Forest algorithm was used to model the distribution and abundance of Eurasian watermilfoil as a function of lake-specific predictors, both with and without a spatial autocovariate. Occurrence-based SDMs were evaluated using conventional discrimination accuracy metrics and functional accuracy metrics assessing correlation between predicted suitability and observed abundance. RESULTS Water temperature degree days and maximum lake depth were two leading predictors influencing both invasion risk and abundance, but they were relatively less important for predicting abundance than other water quality measures. Road density was a strong predictor of Eurasian watermilfoil invasion risk but not abundance. Model evaluations highlighted significant differences: Presence-absence models had high functional accuracy despite low discrimination accuracy, whereas presence-only models showed the opposite pattern. MAIN CONCLUSION Complementing presence-absence data with abundance information offers a richer understanding of invasive Eurasian watermilfoil's ecological niche and enables evaluation of the model's functional accuracy. Conventional discrimination accuracy measures were misleading when models were developed using pseudoabsences. We thus caution against the overuse of presence-only models and suggest directing more effort toward systematic monitoring programs that yield high-quality data.
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Affiliation(s)
- Shyam M. Thomas
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
| | - Michael R. Verhoeven
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
| | - Jake R. Walsh
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
- Minnesota Department of Natural ResourcesSt. PaulMinnesotaUSA
| | - Daniel J. Larkin
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
| | - Gretchen J. A. Hansen
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
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Mills NJ. Abundance–suitability relationships for invasive species: Epiphyas postvittana as a case study. Biol Invasions 2021. [DOI: 10.1007/s10530-021-02500-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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10
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Amini Tehrani N, Naimi B, Jaboyedoff M. Modeling current and future species distribution of breeding birds as regional essential biodiversity variables (SD EBVs): A bird perspective in Swiss Alps. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01596] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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11
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Giezendanner J, Pasetto D, Perez-Saez J, Cerrato C, Viterbi R, Terzago S, Palazzi E, Rinaldo A. Earth and field observations underpin metapopulation dynamics in complex landscapes: Near-term study on carabids. Proc Natl Acad Sci U S A 2020; 117:12877-12884. [PMID: 32461358 PMCID: PMC7293626 DOI: 10.1073/pnas.1919580117] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Understanding risks to biodiversity requires predictions of the spatial distribution of species adapting to changing ecosystems and, to that end, Earth observations integrating field surveys prove essential as they provide key numbers for assessing landscape-wide biodiversity scenarios. Here, we develop, and apply to a relevant case study, a method suited to merge Earth/field observations with spatially explicit stochastic metapopulation models to study the near-term ecological dynamics of target species in complex terrains. Our framework incorporates the use of species distribution models for a reasoned estimation of the initial presence of the target species and accounts for imperfect and incomplete detection of the species presence in the study area. It also uses a metapopulation fitness function derived from Earth observation data subsuming the ecological niche of the target species. This framework is applied to contrast occupancy of two species of carabids (Pterostichus flavofemoratus, Carabus depressus) observed in the context of a large ecological monitoring program carried out within the Gran Paradiso National Park (GPNP, Italy). Results suggest that the proposed framework may indeed exploit the hallmarks of spatially explicit ecological approaches and of remote Earth observations. The model reproduces well the observed in situ data. Moreover, it projects in the near term the two species' presence both in space and in time, highlighting the features of the metapopulation dynamics of colonization and extinction, and their expected trends within verifiable timeframes.
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Affiliation(s)
- Jonathan Giezendanner
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Damiano Pasetto
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Javier Perez-Saez
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | | | | | - Silvia Terzago
- National Research Council (CNR), Institute of Atmospheric Sciences and Climate, 10133 Torino, Italy
| | - Elisa Palazzi
- National Research Council (CNR), Institute of Atmospheric Sciences and Climate, 10133 Torino, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland;
- Dipartimento di Ingegneria Civile Edile e Ambientale (DICEA), Università di Padova, 35131 Padova, Italy
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12
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Johnston A, Auer T, Fink D, Strimas-Mackey M, Iliff M, Rosenberg KV, Brown S, Lanctot R, Rodewald AD, Kelling S. Comparing abundance distributions and range maps in spatial conservation planning for migratory species. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2020; 30:e02058. [PMID: 31838775 DOI: 10.1002/eap.2058] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 07/15/2019] [Accepted: 09/17/2019] [Indexed: 06/10/2023]
Abstract
Most spatial conservation planning for wide-ranging or migratory species is constrained by poor knowledge of species' spatiotemporal dynamics and is only based on static species' ranges. However, species have substantial variation in abundance across their range and migratory species have important spatiotemporal population dynamics. With growing ecological data and advancing analytics, both of these can be estimated and incorporated into spatial conservation planning. However, there is limited information on the degree to which including this information affects conservation planning. We compared the performance of systematic conservation prioritizations for different scenarios based on varying the input species' distributions by ecological metric (abundance distributions versus range maps) and temporal sampling resolution (weekly, monthly, or quarterly). We used the example of a community of 41 species of migratory shorebirds that breed in North America, and we used eBird data to produce weekly estimates of species' abundances and ranges. Abundance distributions at a monthly or weekly resolution led to prioritizations that most efficiently protected species throughout the full annual cycle. Conversely, spatial prioritizations based on species' ranges required more sites and left most species insufficiently protected for at least part of their annual cycle. Prioritizations with only quarterly species ranges were very inefficient as they needed to target 40% of species' ranges to include 10% of populations. We highlight the high value of abundance information for spatial conservation planning, which leads to more efficient and effective spatial prioritization for conservation. Overall, we provide evidence that spatial conservation planning for wide-ranging migratory species is most robust and efficient when informed by species' abundance information from the full annual cycle.
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Affiliation(s)
- A Johnston
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
- Conservation Science Group, Department of Zoology, University of Cambridge, The David Attenborough Building, Pembroke Street, Cambridge, CB2 3QZ, United Kingdom
| | - T Auer
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
| | - D Fink
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
| | - M Strimas-Mackey
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
| | - M Iliff
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
| | - K V Rosenberg
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
- American Bird Conservancy, The Plains, Virginia, 20198, USA
| | - S Brown
- Manomet Inc., P.O. Box 1770, Manomet, Massachusetts, 02345, USA
| | - R Lanctot
- U.S. Fish and Wildlife Service, 1011 East Tudor Road, MS 201, Anchorage, Alaska, 99503, USA
| | - A D Rodewald
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
- Department of Natural Resources, Cornell University, Ithaca, New York, 14853, USA
| | - S Kelling
- Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, New York, 14850, USA
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Osorio-Olvera L, Yañez-Arenas C, Martínez-Meyer E, Peterson AT. Relationships between population densities and niche-centroid distances in North American birds. Ecol Lett 2020; 23:555-564. [PMID: 31944513 DOI: 10.1111/ele.13453] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 10/15/2019] [Accepted: 11/07/2019] [Indexed: 01/18/2023]
Abstract
Correlational ecological niche models have seen intensive use and exploration as a means of estimating the limits of actual and potential geographic distributions of species, yet their application to explaining geographic abundance patterns has been debated. We developed a detailed test of this latter possibility based on the North American Breeding Bird Survey. Correlations between abundances and niche-centroid distances were mostly negative, as per expectations of niche theory and the abundant niche-centre relationship. The negative relationships were not distributed randomly among species: terrestrial, non-migratory, small-bodied, small-niche-breadth and restricted-range species had the strongest negative associations. Distances to niche centroids as estimated from correlational analyses of presence-only data thus offer a unique means by which to infer geographic abundance patterns, which otherwise are enormously difficult to characterise.
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Affiliation(s)
- Luis Osorio-Olvera
- Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, 04510, Mexico.,Biodiversity Institute, University of Kansas, Lawrence, KS, 66045, Mexico
| | - Carlos Yañez-Arenas
- Laboratorio de Ecología Geográfica, Unidad de Biología de la Conservación, Parque Científico Tecnológico de Yucatán, Universidad Nacional Autónoma de México. Mérida, 97302, Merida, Mexico
| | - Enrique Martínez-Meyer
- Instituto de Biología, Universidad Nacional Autónoma de México, Mexico City, 04510, Mexico.,Centro del Cambio Global y la Sustentabilidad, A.C, Villahermosa, Mexico, 86080, Mexico
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14
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Adhikari A, Mainali KP, Rangwala I, Hansen AJ. Various measures of potential evapotranspiration have species-specific impact on species distribution models. Ecol Modell 2019. [DOI: 10.1016/j.ecolmodel.2019.108836] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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15
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Farrell A, Wang G, Rush SA, Martin JA, Belant JL, Butler AB, Godwin D. Machine learning of large-scale spatial distributions of wild turkeys with high-dimensional environmental data. Ecol Evol 2019; 9:5938-5949. [PMID: 31161010 PMCID: PMC6540709 DOI: 10.1002/ece3.5177] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 03/27/2019] [Accepted: 03/28/2019] [Indexed: 11/05/2022] Open
Abstract
Species distribution modeling often involves high-dimensional environmental data. Large amounts of data and multicollinearity among covariates impose challenges to statistical models in variable selection for reliable inferences of the effects of environmental factors on the spatial distribution of species. Few studies have evaluated and compared the performance of multiple machine learning (ML) models in handling multicollinearity. Here, we assessed the effectiveness of removal of correlated covariates and regularization to cope with multicollinearity in ML models for habitat suitability. Three machine learning algorithms maximum entropy (MaxEnt), random forests (RFs), and support vector machines (SVMs) were applied to the original data (OD) of 27 landscape variables, reduced data (RD) with 14 highly correlated covariates being removed, and 15 principal components (PC) of the OD accounting for 90% of the original variability. The performance of the three ML models was measured with the area under the curve and continuous Boyce index. We collected 663 nonduplicated presence locations of Eastern wild turkeys (Meleagris gallopavo silvestris) across the state of Mississippi, United States. Of the total locations, 453 locations separated by a distance of ≥2 km were used to train the three ML algorithms on the OD, RD, and PC data, respectively. The remaining 210 locations were used to validate the trained ML models to measure ML performance. Three ML models had excellent performance on the RD and PC data. MaxEnt and SVMs had good performance on the OD data, indicating the adequacy of regularization of the default setting for multicollinearity. Weak learning of RFs through bagging appeared to alleviate multicollinearity and resulted in excellent performance on the OD data. Regularization of ML algorithms may help exploratory studies of the effects of environmental factors on the spatial distribution and habitat suitability of wildlife.
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Affiliation(s)
- Annie Farrell
- Department of Wildlife, Fisheries and AquacultureMississippi State UniversityMississippi StateMississippi
| | - Guiming Wang
- Department of Wildlife, Fisheries and AquacultureMississippi State UniversityMississippi StateMississippi
| | - Scott A. Rush
- Department of Wildlife, Fisheries and AquacultureMississippi State UniversityMississippi StateMississippi
| | - James A. Martin
- Warnell School of Forestry and Natural Resources and Savannah River Ecology LaboratoryUniversity of GeorgiaAthensGeorgia
| | - Jerrold L. Belant
- Camp Fire Program in Wildlife ConservationState University of New York College of Environmental Science and ForestrySyracuseNew York
| | - Adam B. Butler
- The Mississippi Department of Wildlife, Fisheries, and ParksJacksonMississippi
| | - Dave Godwin
- Mississippi Forestry AssociationJacksonMississippi
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16
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Lunghi E, Manenti R, Mulargia M, Veith M, Corti C, Ficetola GF. Environmental suitability models predict population density, performance and body condition for microendemic salamanders. Sci Rep 2018; 8:7527. [PMID: 29760473 PMCID: PMC5951833 DOI: 10.1038/s41598-018-25704-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 04/25/2018] [Indexed: 11/30/2022] Open
Abstract
Species can show strong variation of local abundance across their ranges. Recent analyses suggested that variation in abundance can be related to environmental suitability, as the highest abundances are often observed in populations living in the most suitable areas. However, there is limited information on the mechanisms through which variation in environmental suitability determines abundance. We analysed populations of the microendemic salamander Hydromantes flavus, and tested several hypotheses on potential relationships linking environmental suitability to population parameters. For multiple populations across the whole species range, we assessed suitability using species distribution models, and measured density, activity level, food intake and body condition index. In high-suitability sites, the density of salamanders was up to 30-times higher than in the least suitable ones. Variation in activity levels and population performance can explain such variation of abundance. In high-suitability sites, salamanders were active close to the surface, and showed a low frequency of empty stomachs. Furthermore, when taking into account seasonal variation, body condition was better in the most suitable sites. Our results show that the strong relationship between environmental suitability and population abundance can be mediated by the variation of parameters strongly linked to individual performance and fitness.
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Affiliation(s)
- Enrico Lunghi
- Biogeographie, Universität Trier Fachbereich VI, Raum- und Umweltwissenschaften, Trier, Germany. .,Museo di Storia Naturale dell'Università degli Studi di Firenze, Sezione di Zoologia "La Specola", Firenze, Italy. .,Natural Oasis, Prato, Italy.
| | - Raoul Manenti
- Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy
| | | | - Michael Veith
- Biogeographie, Universität Trier Fachbereich VI, Raum- und Umweltwissenschaften, Trier, Germany
| | - Claudia Corti
- Museo di Storia Naturale dell'Università degli Studi di Firenze, Sezione di Zoologia "La Specola", Firenze, Italy
| | - Gentile Francesco Ficetola
- Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy.,University Grenoble Alpes, CNRS, Laboratoire d'Écologie Alpine (LECA), F-38000, Grenoble, France
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