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Hallman TA, Robinson WD. Supplemental structured surveys and pre-existing detection models improve fine-scale density and population estimation with opportunistic community science data. Sci Rep 2024; 14:11070. [PMID: 38745056 PMCID: PMC11094051 DOI: 10.1038/s41598-024-61582-6] [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: 12/05/2023] [Accepted: 05/07/2024] [Indexed: 05/16/2024] Open
Abstract
Density and population estimates aid in conservation and stakeholder communication. While free and broadly available community science data can effectively inform species distribution models, they often lack the information necessary to estimate imperfect detection and area sampled, thus limiting their use in fine-scale density modeling. We used structured distance-sampling surveys to model detection probability and calculate survey-specific detection offsets in community science models. We estimated density and population for 16 songbird species under three frameworks: (1) a fixed framework that assumes perfect detection within a specified survey radius, (2) an independent framework that calculates offsets from an independent source, and (3) a calibration framework that calculates offsets from supplemental surveys. Within the calibration framework, we examined the effects of calibration dataset size and data pooling. Estimates of density and population size were consistently biased low in the fixed framework. The independent and calibration frameworks produced reliable estimates for some species, but biased estimates for others, indicating discrepancies in detection probability between structured and community science surveys. The calibration framework produced reliable population estimates with as few as 10 calibration surveys with positive detections. Data pooling dramatically decreased bias. This study provides conservationists and managers with a cost-effective method of estimating density and population.
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Affiliation(s)
- Tyler A Hallman
- Oak Creek Lab of Biology, Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, OR, USA.
- Swiss Ornithological Institute, Seerose 1, 6204, Sempach, Switzerland.
- Department of Biology and Chemistry, Queens University of Charlotte, Charlotte, NC, USA.
- School of Environmental and Natural Sciences, Bangor University, Bangor, LL57 2DG, UK.
| | - W Douglas Robinson
- Oak Creek Lab of Biology, Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, OR, USA
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2
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Voltura EV, Tracy JL, Heatley JJ, Kiacz S, Brightsmith DJ, Filippi AM, Franco JG, Coulson R. Modelling Red-Crowned Parrot (Psittaciformes: Amazona viridigenalis [Cassin, 1853]) distributions in the Rio Grande Valley of Texas using elevation and vegetation indices and their derivatives. PLoS One 2023; 18:e0294118. [PMID: 38055729 DOI: 10.1371/journal.pone.0294118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 10/26/2023] [Indexed: 12/08/2023] Open
Abstract
Texas Rio Grande Valley Red-crowned Parrots (Psittaciformes: Amazona viridigenalis [Cassin, 1853]) primarily occupy vegetated urban rather than natural areas. We investigated the utility of raw vegetation indices and their derivatives as well as elevation in modelling the Red-crowned parrot's general use, nest site, and roost site habitat distributions. A feature selection algorithm was employed to create and select an ensemble of fine-scale, top-ranked MaxEnt models from optimally-sized, decorrelated subsets of four to seven of 199 potential variables. Variables were ranked post hoc by frequency of appearance and mean permutation importance in top-ranked models. Our ensemble models accurately predicted the three distributions of interest ([Formula: see text] Area Under the Curve [AUC] = 0.904-0.969). Top-ranked variables for different habitat distribution models included: (a) general use-percent cover of preferred ranges of entropy texture of Normalized Difference Vegetation Index (NDVI) values, entropy and contrast textures of NDVI, and elevation; (b) nest site-entropy textures of NDVI and Green-Blue NDVI, and percent cover of preferred range of entropy texture of NDVI values; (c) roost site-percent cover of preferred ranges of entropy texture of NDVI values, contrast texture of NDVI, and entropy texture of Green-Red Normalized Difference Index. Texas Rio Grande Valley Red-crowned Parrot presence was associated with urban areas with high heterogeneity and randomness in the distribution of vegetation and/or its characteristics (e.g., arrangement, type, structure). Maintaining existing preferred vegetation types and incorporating them into new developments should support the persistence of Red-crowned Parrots in southern Texas.
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Affiliation(s)
- Elise Varaela Voltura
- Department of Veterinary Pathobiology, Texas A&M University, College Station, Texas, United States of America
- Schubot Center for Avian Health, Texas A&M University, College Station, Texas, United States of America
| | - James L Tracy
- Department of Entomology, Texas A&M University, College Station, Texas, United States of America
| | - J Jill Heatley
- Schubot Center for Avian Health, Texas A&M University, College Station, Texas, United States of America
- Department of Small Animal Clinical Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Simon Kiacz
- Schubot Center for Avian Health, Texas A&M University, College Station, Texas, United States of America
- Department of Ecology and Evolutionary Biology, Texas A&M University, College Station, Texas, United States of America
| | - Donald J Brightsmith
- Department of Veterinary Pathobiology, Texas A&M University, College Station, Texas, United States of America
- Schubot Center for Avian Health, Texas A&M University, College Station, Texas, United States of America
| | - Anthony M Filippi
- Department of Geography, Texas A&M University, College Station, Texas, United States of America
| | - Jesús G Franco
- Rio Grande Joint Venture, American Bird Conservancy, McAllen, Texas, United States of America
| | - Robert Coulson
- Department of Entomology, Texas A&M University, College Station, Texas, United States of America
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3
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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. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023; 37:e14091. [PMID: 37021393 DOI: 10.1111/cobi.14091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 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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4
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Barker JR, MacIsaac HJ. Species distribution models: Administrative boundary centroid occurrences require careful interpretation. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2022.110107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Forest degradation drives widespread avian habitat and population declines. Nat Ecol Evol 2022; 6:709-719. [PMID: 35484222 PMCID: PMC9177422 DOI: 10.1038/s41559-022-01737-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 03/20/2022] [Indexed: 12/24/2022]
Abstract
In many regions of the world, forest management has reduced old forest and simplified forest structure and composition. We hypothesized that such forest degradation has resulted in long-term habitat loss for forest-associated bird species of eastern Canada (130,017 km2) which, in turn, has caused bird-population declines. Despite little change in overall forest cover, we found substantial reductions in old forest as a result of frequent clear-cutting and a broad-scale transformation to intensified forestry. Back-cast species distribution models revealed that breeding habitat loss occurred for 66% of the 54 most common species from 1985 to 2020 and was strongly associated with reduction in old age classes. Using a long-term, independent dataset, we found that habitat amount predicted population size for 94% of species, and habitat loss was associated with population declines for old-forest species. Forest degradation may therefore be a primary cause of biodiversity decline in managed forest landscapes.
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Conlisk EE, Golet GH, Reynolds MD, Barbaree BA, Sesser KA, Byrd KB, Veloz S, Reiter ME. Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2022; 32:e2510. [PMID: 34870360 PMCID: PMC9286402 DOI: 10.1002/eap.2510] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 05/05/2021] [Accepted: 07/09/2021] [Indexed: 06/13/2023]
Abstract
Highly mobile species, such as migratory birds, respond to seasonal and interannual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species-distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16 days), and 17-year long-term average surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. Although modeling with both real-time and long-term average data provided good fit to withheld validation data (the area under the receiver operating characteristic curve, or AUC, averaged between 0.79 and 0.89 for all taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g., perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions, whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.
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Affiliation(s)
| | | | | | | | | | - Kristin B. Byrd
- U.S. Geological Survey, Western Geographic Science CenterMoffett FieldCaliforniaUSA
| | - Sam Veloz
- Point Blue Conservation SciencePetalumaCaliforniaUSA
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7
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Crego RD, Stabach JA, Connette G. Implementation of species distribution models in Google Earth Engine. DIVERS DISTRIB 2022. [DOI: 10.1111/ddi.13491] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Affiliation(s)
- Ramiro D. Crego
- Conservation Ecology Center Smithsonian National Zoo and Conservation Biology Institute Front Royal Virginia USA
- Working Land and Seascapes Conservation CommonsSmithsonian Institution Washington District of Columbia USA
| | - Jared A. Stabach
- Conservation Ecology Center Smithsonian National Zoo and Conservation Biology Institute Front Royal Virginia USA
| | - Grant Connette
- Conservation Ecology Center Smithsonian National Zoo and Conservation Biology Institute Front Royal Virginia USA
- Working Land and Seascapes Conservation CommonsSmithsonian Institution Washington District of Columbia USA
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8
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Hallman TA, Robinson WD, Curtis JR, Alverson ER. Building a better baseline to estimate 160 years of avian population change and create historically informed conservation targets. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2021; 35:1256-1267. [PMID: 33274484 DOI: 10.1111/cobi.13676] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 11/24/2020] [Accepted: 11/27/2020] [Indexed: 06/12/2023]
Abstract
Globally, anthropogenic land-cover change has been dramatic over the last few centuries and is frequently invoked as a major cause of wildlife population declines. Baseline data currently used to assess population trends, however, began well after major changes to the landscape. In the United States and Canada, breeding bird population trends are assessed by the North American Breeding Bird Survey, which began in the 1960s. Estimates of distribution and abundance prior to major habitat alteration would add historical perspective to contemporary trends and allow for historically based conservation targets. We used a hindcasting framework to estimate change in distribution and abundance of 7 bird species in the Willamette Valley, Oregon (United States). After reconciling classification schemes of current and 1850s reconstructed land cover, we used multiscale species distribution models and hierarchical distance sampling models to predict spatially explicit densities in the modern and historical landscapes. We estimated that since the 1850s, White-breasted Nuthatch (Sitta carolinensis) and Western Meadowlark (Sturnella neglecta) populations, 2 species sensitive to fragmentation of oak woodlands and grasslands, declined by 93% and 97%, respectively. Five other species we estimated nearly stable or increasing populations, despite steep regional declines since the 1960s. Based on these estimates, we developed historically based conservation targets for amount of habitat, population, and density for each species. Hindcasted reconstructions provide historical perspective for assessing contemporary trends and allow for historically based conservation targets that can inform current management.
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Affiliation(s)
- Tyler A Hallman
- Monitoring Department, Swiss Ornithological Institute, Seerose 1, Sempach, CH-6204, Switzerland
- Department of Fisheries and Wildlife, Oregon State University, 104 Nash Hall, Corvallis, OR, 97331, U.S.A
| | - W Douglas Robinson
- Department of Fisheries and Wildlife, Oregon State University, 104 Nash Hall, Corvallis, OR, 97331, U.S.A
| | - Jenna R Curtis
- Cornell Lab of Ornithology, 159 Sapsucker Woods Rd. Ithaca, New York, NY, 14850, U.S.A
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9
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Austrich A, Kittlein MJ, Mora MS, Mapelli FJ. Potential distribution models from two highly endemic species of subterranean rodents of Argentina: which environmental variables have better performance in highly specialized species? Mamm Biol 2021. [DOI: 10.1007/s42991-021-00150-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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10
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Weinstein BG, Marconi S, Bohlman SA, Zare A, Singh A, Graves SJ, White EP. A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network. eLife 2021; 10:e62922. [PMID: 33605211 PMCID: PMC7895524 DOI: 10.7554/elife.62922] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 02/15/2021] [Indexed: 01/03/2023] Open
Abstract
Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data collection. While advances in remote sensing techniques allow surveys of individual trees at unprecedented extents, there remain technical challenges in turning sensor data into tangible information. Using deep learning methods, we produced an open-source data set of individual-level crown estimates for 100 million trees at 37 sites across the United States surveyed by the National Ecological Observatory Network's Airborne Observation Platform. Each canopy tree crown is represented by a rectangular bounding box and includes information on the height, crown area, and spatial location of the tree. These data have the potential to drive significant expansion of individual-level research on trees by facilitating both regional analyses and cross-region comparisons encompassing forest types from most of the United States.
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Affiliation(s)
- Ben G Weinstein
- Department of Wildlife Ecology and Conservation, University of FloridaGainesvilleUnited States
| | - Sergio Marconi
- Department of Wildlife Ecology and Conservation, University of FloridaGainesvilleUnited States
| | - Stephanie A Bohlman
- School of Forest Resources and Conservation, University of FloridaGainesvilleUnited States
| | - Alina Zare
- Department of Electrical and Computer Engineering, University of FloridaGainesvilleUnited States
| | - Aditya Singh
- Department of Agricultural & Biological Engineering, University of FloridaGainesvilleUnited States
| | - Sarah J Graves
- Nelson Institute for Environmental Studies, University of Wisconsin-MadisonMadisonUnited States
| | - Ethan P White
- Department of Wildlife Ecology and Conservation, University of FloridaGainesvilleUnited States
- Informatics Institute, University of FloridaGainesvilleUnited States
- Biodiversity Institute, University of FloridaGainesvilleUnited States
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11
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Hallman TA, Robinson WD. Deciphering ecology from statistical artefacts: Competing influence of sample size, prevalence and habitat specialization on species distribution models and how small evaluation datasets can inflate metrics of performance. DIVERS DISTRIB 2020. [DOI: 10.1111/ddi.13030] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Tyler A. Hallman
- Department of Fisheries and Wildlife Oregon State University Corvallis Oregon
| | - William D. Robinson
- Department of Fisheries and Wildlife Oregon State University Corvallis Oregon
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12
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Betts MG, Gutiérrez Illán J, Yang Z, Shirley SM, Thomas CD. Synergistic Effects of Climate and Land-Cover Change on Long-Term Bird Population Trends of the Western USA: A Test of Modeled Predictions. Front Ecol Evol 2019. [DOI: 10.3389/fevo.2019.00186] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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13
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Kaky E, Gilbert F. Predicting the distributions of Egypt's medicinal plants and their potential shifts under future climate change. PLoS One 2017; 12:e0187714. [PMID: 29136659 PMCID: PMC5685616 DOI: 10.1371/journal.pone.0187714] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 10/24/2017] [Indexed: 11/19/2022] Open
Abstract
Climate change is one of the most difficult of challenges to conserving biodiversity, especially for countries with few data on the distributions of their taxa. Species distribution modelling is a modern approach to the assessment of the potential effects of climate change on biodiversity, with the great advantage of being robust to small amounts of data. Taking advantage of a recently validated dataset, we use the medicinal plants of Egypt to identify hotspots of diversity now and in the future by predicting the effect of climate change on the pattern of species richness using species distribution modelling. Then we assess how Egypt's current Protected Area network is likely to perform in protecting plants under climate change. The patterns of species richness show that in most cases the A2a 'business as usual' scenario was more harmful than the B2a 'moderate mitigation' scenario. Predicted species richness inside Protected Areas was higher than outside under all scenarios, indicating that Egypt's PAs are well placed to help conserve medicinal plants.
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Affiliation(s)
- Emad Kaky
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
- Kalar Technical Institute, Sulaimani Polytechnic University, Sulaymaniyah, Iraq
| | - Francis Gilbert
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
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14
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Winiarski JM, Moorman CE, Carpenter JP, Hess GR. Reproductive consequences of habitat fragmentation for a declining resident bird of the longleaf pine ecosystem. Ecosphere 2017. [DOI: 10.1002/ecs2.1898] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Jason M. Winiarski
- Fisheries, Wildlife, and Conservation Biology Program; Department of Forestry and Environmental Resources; North Carolina State University; Raleigh North Carolina 27695 USA
| | - Christopher E. Moorman
- Fisheries, Wildlife, and Conservation Biology Program; Department of Forestry and Environmental Resources; North Carolina State University; Raleigh North Carolina 27695 USA
| | - John P. Carpenter
- North Carolina Wildlife Resources Commission; 1751 Varsity Drive Raleigh North Carolina 27606 USA
| | - George R. Hess
- Fisheries, Wildlife, and Conservation Biology Program; Department of Forestry and Environmental Resources; North Carolina State University; Raleigh North Carolina 27695 USA
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15
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Fontaine JJ, Jorgensen CF, Stuber EF, Gruber LF, Bishop AA, Lusk JJ, Zach ES, Decker KL. Species distributions models in wildlife planning: agricultural policy and wildlife management in the great plains. WILDLIFE SOC B 2017. [DOI: 10.1002/wsb.763] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Joseph J. Fontaine
- U.S. Geological Survey, Nebraska Cooperative Fish and Wildlife Research Unit; School of Natural Resources, University of Nebraska-Lincoln; Lincoln NE 68583 USA
| | | | - Erica F. Stuber
- Nebraska Cooperative Fish and Wildlife Research Unit; School of Natural Resources, University of Nebraska-Lincoln; Lincoln NE 68583 USA
| | - Lutz F. Gruber
- Nebraska Cooperative Fish and Wildlife Research Unit; School of Natural Resources, University of Nebraska-Lincoln; Lincoln NE 68583 USA
| | - Andrew A. Bishop
- U.S. Fish and Wildlife Service; Rainwater Basin Joint Venture; Grand Island NE 68801 USA
| | | | - Eric S. Zach
- Nebraska Game and Parks Commission; Lincoln NE 68503 USA
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16
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Skowronek S, Asner GP, Feilhauer H. Performance of one-class classifiers for invasive species mapping using airborne imaging spectroscopy. ECOL INFORM 2017. [DOI: 10.1016/j.ecoinf.2016.11.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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18
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Soley-Guardia M, Gutiérrez EE, Thomas DM, Ochoa-G J, Aguilera M, Anderson RP. Are we overestimating the niche? Removing marginal localities helps ecological niche models detect environmental barriers. Ecol Evol 2016; 6:1267-79. [PMID: 26848385 PMCID: PMC4730904 DOI: 10.1002/ece3.1900] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2015] [Revised: 11/09/2015] [Accepted: 11/23/2015] [Indexed: 11/08/2022] Open
Abstract
Correlative ecological niche models (ENMs) estimate species niches using occurrence records and environmental data. These tools are valuable to the field of biogeography, where they are commonly used to infer potential connectivity among populations. However, a recent study showed that when locally relevant environmental data are not available, records from patches of suitable habitat protruding into otherwise unsuitable regions (e.g., gallery forests within dry areas) can lead to overestimations of species niches and their potential distributions. Here, we test whether this issue obfuscates detection of an obvious environmental barrier existing in northern Venezuela - that of the hot and xeric lowlands separating the Península de Paraguaná from mainland South America. These conditions most likely promote isolation between mainland and peninsular populations of three rodent lineages occurring in mesic habitat in this region. For each lineage, we calibrated optimally parameterized ENMs using mainland records only, and leveraged existing habitat descriptions to assess whether those assigned low suitability values corresponded to instances where the species was collected within locally mesic conditions amidst otherwise hot dry areas. When this was the case, we built an additional model excluding these records. We projected both models onto the peninsula and assessed whether they differed in their ability to detect the environmental barrier. For the two lineages in which we detected such problematic records, only the models built excluding them detected the barrier, while providing additional insights regarding peninsular populations. Overall, the study reveals how a simple procedure like the one applied here can deal with records problematic for ENMs, leading to better predictions regarding the potential effects of the environment on lineage divergence.
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Affiliation(s)
- Mariano Soley-Guardia
- Department of Biology City College of New York City University of New York New York New York; The Graduate Center City University of New York New York New York
| | - Eliécer E Gutiérrez
- Department of Biology City College of New York City University of New York New York New York; The Graduate Center City University of New York New York New York; Department of Vertebrate Zoology Division of Mammals National Museum of Natural History Smithsonian Institution Washington District of Columbia
| | - Darla M Thomas
- Department of Biology City College of New York City University of New York New York New York
| | | | - Marisol Aguilera
- Departamento de Estudios Ambientales Universidad Simón Bolívar Caracas Venezuela
| | - Robert P Anderson
- Department of Biology City College of New York City University of New York New York New York; The Graduate Center City University of New York New York New York; Division of Vertebrate Zoology (Mammalogy) American Museum of Natural History New York New York
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19
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Monitoring Natural Ecosystem and Ecological Gradients: Perspectives with EnMAP. REMOTE SENSING 2015. [DOI: 10.3390/rs71013098] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Rhodes CJ, Henrys P, Siriwardena GM, Whittingham MJ, Norton LR. The relative value of field survey and remote sensing for biodiversity assessment. Methods Ecol Evol 2015. [DOI: 10.1111/2041-210x.12385] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Christopher J. Rhodes
- Centre for Ecology & Hydrology Lancaster Environment Centre Library Avenue Bailrigg Lancaster LA1 4AP UK
- School of Biology Newcastle University Newcastle‐Upon‐Tyne NE1 7RU UK
| | - Peter Henrys
- Centre for Ecology & Hydrology Lancaster Environment Centre Library Avenue Bailrigg Lancaster LA1 4AP UK
| | | | | | - Lisa R. Norton
- Centre for Ecology & Hydrology Lancaster Environment Centre Library Avenue Bailrigg Lancaster LA1 4AP UK
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Neumann W, Martinuzzi S, Estes AB, Pidgeon AM, Dettki H, Ericsson G, Radeloff VC. Opportunities for the application of advanced remotely-sensed data in ecological studies of terrestrial animal movement. MOVEMENT ECOLOGY 2015; 3:8. [PMID: 25941571 PMCID: PMC4418104 DOI: 10.1186/s40462-015-0036-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 03/04/2015] [Indexed: 06/01/2023]
Abstract
Animal movement patterns in space and time are a central aspect of animal ecology. Remotely-sensed environmental indices can play a key role in understanding movement patterns by providing contiguous, relatively fine-scale data that link animal movements to their environment. Still, implementation of newly available remotely-sensed data is often delayed in studies of animal movement, calling for a better flow of information to researchers less familiar with remotely-sensed data applications. Here, we reviewed the application of remotely-sensed environmental indices to infer movement patterns of animals in terrestrial systems in studies published between 2002 and 2013. Next, we introduced newly available remotely-sensed products, and discussed their opportunities for animal movement studies. Studies of coarse-scale movement mostly relied on satellite data representing plant phenology or climate and weather. Studies of small-scale movement frequently used land cover data based on Landsat imagery or aerial photographs. Greater documentation of the type and resolution of remotely-sensed products in ecological movement studies would enhance their usefulness. Recent advancements in remote sensing technology improve assessments of temporal dynamics of landscapes and the three-dimensional structures of habitats, enabling near real-time environmental assessment. Online movement databases that now integrate remotely-sensed data facilitate access to remotely-sensed products for movement ecologists. We recommend that animal movement studies incorporate remotely-sensed products that provide time series of environmental response variables. This would facilitate wildlife management and conservation efforts, as well as the predictive ability of movement analyses. Closer collaboration between ecologists and remote sensing experts could considerably alleviate the implementation gap. Ecologists should not expect that indices derived from remotely-sensed data will be directly analogous to field-collected data and need to critically consider which remotely-sensed product is best suited for a given analysis.
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Affiliation(s)
- Wiebke Neumann
- />Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706 USA
- />Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, SE-90183 Sweden
| | - Sebastian Martinuzzi
- />Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706 USA
| | - Anna B Estes
- />Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706 USA
- />The Huck Institutes of the Life Sciences, Pennsylvania State University, Pennsylvania, USA
| | - Anna M Pidgeon
- />Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706 USA
| | - Holger Dettki
- />Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, SE-90183 Sweden
| | - Göran Ericsson
- />Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, SE-90183 Sweden
| | - Volker C Radeloff
- />Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706 USA
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22
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Can Airborne Laser Scanning (ALS) and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest? REMOTE SENSING 2015. [DOI: 10.3390/rs70404233] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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23
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Illán JG, Thomas CD, Jones JA, Wong WK, Shirley SM, Betts MG. Precipitation and winter temperature predict long-term range-scale abundance changes in Western North American birds. GLOBAL CHANGE BIOLOGY 2014; 20:3351-3364. [PMID: 24863299 DOI: 10.1111/gcb.12642] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 04/07/2014] [Indexed: 06/03/2023]
Abstract
Predicting biodiversity responses to climate change remains a difficult challenge, especially in climatically complex regions where precipitation is a limiting factor. Though statistical climatic envelope models are frequently used to project future scenarios for species distributions under climate change, these models are rarely tested using empirical data. We used long-term data on bird distributions and abundance covering five states in the western US and in the Canadian province of British Columbia to test the capacity of statistical models to predict temporal changes in bird populations over a 32-year period. Using boosted regression trees, we built presence-absence and abundance models that related the presence and abundance of 132 bird species to spatial variation in climatic conditions. Presence/absence models built using 1970-1974 data forecast the distributions of the majority of species in the later time period, 1998-2002 (mean AUC = 0.79 ± 0.01). Hindcast models performed equivalently (mean AUC = 0.82 ± 0.01). Correlations between observed and predicted abundances were also statistically significant for most species (forecast mean Spearman's ρ = 0.34 ± 0.02, hindcast = 0.39 ± 0.02). The most stringent test is to test predicted changes in geographic patterns through time. Observed changes in abundance patterns were significantly positively correlated with those predicted for 59% of species (mean Spearman's ρ = 0.28 ± 0.02, across all species). Three precipitation variables (for the wettest month, breeding season, and driest month) and minimum temperature of the coldest month were the most important predictors of bird distributions and abundances in this region, and hence of abundance changes through time. Our results suggest that models describing associations between climatic variables and abundance patterns can predict changes through time for some species, and that changes in precipitation and winter temperature appear to have already driven shifts in the geographic patterns of abundance of bird populations in western North America.
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Affiliation(s)
- Javier Gutiérrez Illán
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97331, USA; Department of Biology (Area 18), University of York, Heslington, York, YO10 5DD, UK
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Bucklin DN, Basille M, Benscoter AM, Brandt LA, Mazzotti FJ, Romañach SS, Speroterra C, Watling JI. Comparing species distribution models constructed with different subsets of environmental predictors. DIVERS DISTRIB 2014. [DOI: 10.1111/ddi.12247] [Citation(s) in RCA: 105] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- David N. Bucklin
- Fort Lauderdale Research and Education Center University of Florida 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - Mathieu Basille
- Fort Lauderdale Research and Education Center University of Florida 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - Allison M. Benscoter
- Fort Lauderdale Research and Education Center University of Florida 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - Laura A. Brandt
- US Fish and Wildlife Service 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - Frank J. Mazzotti
- Fort Lauderdale Research and Education Center University of Florida 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - Stephanie S. Romañach
- US Geological Survey Southeast Ecological Science Center 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - Carolina Speroterra
- Fort Lauderdale Research and Education Center University of Florida 3205 College Avenue Fort Lauderdale FL 33314 USA
| | - James I. Watling
- Fort Lauderdale Research and Education Center University of Florida 3205 College Avenue Fort Lauderdale FL 33314 USA
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Pickens BA, King SL. Linking multi-temporal satellite imagery to coastal wetland dynamics and bird distribution. Ecol Modell 2014. [DOI: 10.1016/j.ecolmodel.2014.04.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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26
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Integrating Open Access Geospatial Data to Map the Habitat Suitability of the Declining Corn Bunting (Miliaria calandra). ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2013. [DOI: 10.3390/ijgi2040935] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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