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Nizamani MM, Papeş M, Wang H, Harris AJ. How does spatial extent and environmental limits affect the accuracy of species richness estimates from ecological niche models? A case study with North American Pinaceae and Cactaceae. Ecol Evol 2023; 13:e10007. [PMID: 37091570 PMCID: PMC10121319 DOI: 10.1002/ece3.10007] [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: 07/09/2022] [Revised: 03/13/2023] [Accepted: 03/31/2023] [Indexed: 04/25/2023] Open
Abstract
Measuring species richness at varying spatial extents can be challenging, especially at large extents where exhaustive species surveys are difficult or impossible. Our work aimed at determining the reliability of species richness estimates from stacked ecological niche models at different spatial extents for taxonomic groups with vastly different environmental dependencies and interactions. To accomplish this, we generated ecological niche models for the species of Cactaceae and Pinaceae that occur within 180 published floras from North America north of Mexico. We overlaid or stacked the resulting species' potential distribution estimates over the bounding boxes representing each of the 180 floras to generate predictions of species richness. In general, our stacked models of Cactaceae and Pinaceae were poor predictors of species richness. The relationships between observed and predicted values improved noticeably with the size of spatial extents. However, the stacked models tended to overpredict the richness of Cactaceae and over- and underpredict the richness of Pinaceae. Cactaceae stacked models showed higher sensitivity and lower specificity than those for Pinaceae. We conclude that stacked ecological niche models may be somewhat poor predictors of species richness at smaller spatial extents and should be used with caution for this purpose. Perhaps more importantly, abilities to compensate for their limitations or apply corrections to their reliability may vary with taxonomic groups.
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Affiliation(s)
- Mir Muhammad Nizamani
- Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed LaboratorySanyaChina
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresources, College of Tropical CropsHainan UniversityHaikouChina
| | - Monica Papeş
- Department of Ecology and Evolutionary BiologyUniversity of TennesseeKnoxvilleTennesseeUSA
| | - Hua‐Feng Wang
- Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed LaboratorySanyaChina
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresources, College of Tropical CropsHainan UniversityHaikouChina
| | - AJ Harris
- South China Botanical Garden, Chinese Academy of ScienceGuangzhouChina
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Chen Y, Jiang Z, Fan P, Ericson PGP, Song G, Luo X, Lei F, Qu Y. The combination of genomic offset and niche modelling provides insights into climate change-driven vulnerability. Nat Commun 2022; 13:4821. [PMID: 35974023 PMCID: PMC9381542 DOI: 10.1038/s41467-022-32546-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 08/01/2022] [Indexed: 11/09/2022] Open
Abstract
Global warming is increasingly exacerbating biodiversity loss. Populations locally adapted to spatially heterogeneous environments may respond differentially to climate change, but this intraspecific variation has only recently been considered when modelling vulnerability under climate change. Here, we incorporate intraspecific variation in genomic offset and ecological niche modelling to estimate climate change-driven vulnerability in two bird species in the Sino-Himalayan Mountains. We found that the cold-tolerant populations show higher genomic offset but risk less challenge for niche suitability decline under future climate than the warm-tolerant populations. Based on a genome-niche index estimated by combining genomic offset and niche suitability change, we identified the populations with the least genome-niche interruption as potential donors for evolutionary rescue, i.e., the populations tolerant to climate change. We evaluated potential rescue routes via a landscape genetic analysis. Overall, we demonstrate that the integration of genomic offset, niche suitability modelling, and landscape connectivity can improve climate change-driven vulnerability assessments and facilitate effective conservation management.
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Affiliation(s)
- Yilin Chen
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Zhiyong Jiang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ping Fan
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Per G P Ericson
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, SE-104 05, Stockholm, Sweden
| | - Gang Song
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Xu Luo
- Faculty of Biodiversity and Conservation, Southwest Forestry University, Kunming, China
| | - Fumin Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China. .,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Yanhua Qu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China. .,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
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Binley AD, Proctor CA, Pither R, Davis SA, Bennett JR. The unrealized potential of community science to support research on the resilience of protected areas. CONSERVATION SCIENCE AND PRACTICE 2021. [DOI: 10.1111/csp2.376] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
| | | | | | - Sierra A. Davis
- Department of Biology Carleton University Ottawa Ontario Canada
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Meehan TD, Kaminski RM, Lebaron GS, Michel NL, Bateman BL, Wilsey CB. Half‐Century Winter Duck Abundance and Temperature Trends in the Mississippi and Atlantic Flyways. J Wildl Manage 2021. [DOI: 10.1002/jwmg.22023] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
| | - Richard M. Kaminski
- James C. Kennedy Waterfowl and Wetlands Conservation Center, Belle W. Baruch Institute of Coastal Ecology and Forest Science Clemson University P.O. Box 596 Georgetown SC 29442 USA
| | | | - Nicole L. Michel
- National Audubon Society 225 Varick Street New York NY 10014 USA
| | | | - Chad B. Wilsey
- National Audubon Society 225 Varick Street New York NY 10014 USA
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Varghese J, Crawford SS. A cultural framework for Indigenous, Local, and Science knowledge systems in ecology and natural resource management. ECOL MONOGR 2020. [DOI: 10.1002/ecm.1431] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Jeji Varghese
- Department of Sociology and Anthropology University of Guelph Guelph OntarioN1G 2W1Canada
| | - Stephen S. Crawford
- Department of Integrative Biology University of Guelph Guelph OntarioN1G 2W1Canada
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