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Van Lanen NJ, Monroe AP, Aldridge CL. Living on the edge: Predicting songbird response to management and environmental changes across an ecotone. Ecol Evol 2023; 13:e10648. [PMID: 38020705 PMCID: PMC10646169 DOI: 10.1002/ece3.10648] [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: 09/29/2023] [Accepted: 10/09/2023] [Indexed: 12/01/2023] Open
Abstract
Effective wildlife management requires robust information regarding population status, habitat requirements, and likely responses to changing resource conditions. Single-species management may inadequately conserve communities and result in undesired effects to non-target species. Thus, management can benefit from understanding habitat relationships for multiple species. Pinyon pine and juniper (Pinus spp. and Juniperus spp.) are expanding into sagebrush-dominated (Artemisia spp.) ecosystems within North America and mechanical removal of these trees is frequently conducted to restore sagebrush ecosystems and recover Greater Sage-grouse (Centrocercus urophasianus). However, pinyon-juniper removal effects on non-target species are poorly understood, and changing pinyon-juniper woodland dynamics, climate, and anthropogenic development may obscure conservation priorities. To better predict responses to changing resource conditions, evaluate non-target effects of pinyon-juniper removal, prioritize species for conservation, and inform species recovery within pinyon-juniper and sagebrush ecosystems, we modeled population trends and density-habitat relationships for four sagebrush-associated, four pinyon-juniper-associated, and three generalist songbird species with respect to these ecosystems. We fit hierarchical population models to point count data collected throughout the western United States from 2008 to 2020. We found regional population changes for 10 of 11 species investigated; 6 of which increased in the highest elevation region of our study. Our models indicate pinyon-juniper removal will benefit Brewer's Sparrow (Spizella breweri), Green-tailed Towhee (Pipilo chlorurus), and Sage Thrasher (Oreoscoptes montanus) densities. Conversely, we predict largest negative effects of pinyon-juniper removal for species occupying early successional pinyon-juniper woodlands: Bewick's Wren (Thryomanes bewickii), Black-throated Gray Warblers (Setophaga nigrescens), Gray Flycatcher (Empidonax wrightii), and Juniper Titmouse (Baeolophus ridgwayi). Our results highlight the importance of considering effects to non-target species before implementing large-scale habitat manipulations. Our modeling framework can help prioritize species and regions for conservation action, infer effects of management interventions and a changing environment on wildlife, and help land managers balance habitat requirements across ecosystems.
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Affiliation(s)
- Nicholas J. Van Lanen
- U.S. Geological Survey, Fort Collins Science CenterFort CollinsColoradoUSA
- Graduate Degree Program in Ecology, Colorado State UniversityFort CollinsColoradoUSA
- Bird Conservancy of the RockiesBrightonColoradoUSA
| | - Adrian P. Monroe
- U.S. Geological Survey, Fort Collins Science CenterFort CollinsColoradoUSA
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Zimmerman SJ, Aldridge CL, O'Donnell MS, Edmunds DR, Coates PS, Prochazka BG, Fike JA, Cross TB, Fedy BC, Oyler-McCance SJ. A genetic warning system for a hierarchically structured wildlife monitoring framework. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2023; 33:e2787. [PMID: 36482030 DOI: 10.1002/eap.2787] [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: 03/05/2022] [Revised: 10/10/2022] [Accepted: 10/20/2022] [Indexed: 06/17/2023]
Abstract
Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhood-scale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations. We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern. Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.
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Affiliation(s)
- Shawna J Zimmerman
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - Cameron L Aldridge
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - Michael S O'Donnell
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - David R Edmunds
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - Peter S Coates
- U.S. Geological Survey, Western Ecological Research Center, Dixon Field Station, Dixon, California, USA
| | - Brian G Prochazka
- U.S. Geological Survey, Western Ecological Research Center, Dixon Field Station, Dixon, California, USA
| | - Jennifer A Fike
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - Todd B Cross
- School of Environment, Resources and Sustainability, University of Waterloo, Waterloo, Ontario, Canada
| | - Bradley C Fedy
- School of Environment, Resources and Sustainability, University of Waterloo, Waterloo, Ontario, Canada
| | - Sara J Oyler-McCance
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
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O'Donnell MS, Edmunds DR, Aldridge CL, Heinrichs JA, Monroe AP, Coates PS, Prochazka BG, Hanser SE, Wiechman LA. Defining biologically relevant and hierarchically nested population units to inform wildlife management. Ecol Evol 2022; 12:e9565. [PMID: 36466138 PMCID: PMC9712811 DOI: 10.1002/ece3.9565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 10/29/2022] [Accepted: 11/11/2022] [Indexed: 12/05/2022] Open
Abstract
Wildlife populations are increasingly affected by natural and anthropogenic changes that negatively alter biotic and abiotic processes at multiple spatiotemporal scales and therefore require increased wildlife management and conservation efforts. However, wildlife management boundaries frequently lack biological context and mechanisms to assess demographic data across the multiple spatiotemporal scales influencing populations. To address these limitations, we developed a novel approach to define biologically relevant subpopulations of hierarchically nested population levels that could facilitate managing and conserving wildlife populations and habitats. Our approach relied on the Spatial "K"luster Analysis by Tree Edge Removal clustering algorithm, which we applied in an agglomerative manner (bottom-to-top). We modified the clustering algorithm using a workflow and population structure tiers from least-cost paths, which captured biological inferences of habitat conditions (functional connectivity), dispersal capabilities (potential connectivity), genetic information, and functional processes affecting movements. The approach uniquely included context of habitat resources (biotic and abiotic) summarized at multiple spatial scales surrounding locations with breeding site fidelity and constraint-based rules (number of sites grouped and population structure tiers). We applied our approach to greater sage-grouse (Centrocercus urophasianus), a species of conservation concern, across their range within the western United States. This case study produced 13 hierarchically nested population levels (akin to cluster levels, each representing a collection of subpopulations of an increasing number of breeding sites). These closely approximated population closure at finer ecological scales (smaller subpopulation extents with fewer breeding sites; cluster levels ≥2), where >92% of individual sage-grouse's time occurred within their home cluster. With available population monitoring data, our approaches can support the investigation of factors affecting population dynamics at multiple scales and assist managers with making informed, targeted, and cost-effective decisions within an adaptive management framework. Importantly, our approach provides the flexibility of including species-relevant context, thereby supporting other wildlife characterized by site fidelity.
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Affiliation(s)
| | - David R. Edmunds
- U.S. Geological SurveyFort Collins Science CenterFort CollinsColoradoUSA
| | | | - Julie A. Heinrichs
- Natural Resource Ecology Laboratory, U.S. Geological Survey, Fort Collins Science CenterColorado State UniversityFort CollinsColoradoUSA
| | - Adrian P. Monroe
- U.S. Geological SurveyFort Collins Science CenterFort CollinsColoradoUSA
| | - Peter S. Coates
- U.S. Geological SurveyWestern Ecological Research CenterDixonCaliforniaUSA
| | - Brian G. Prochazka
- U.S. Geological SurveyWestern Ecological Research CenterDixonCaliforniaUSA
| | - Steve E. Hanser
- U.S. Geological SurveyFort Collins Science CenterFort CollinsColoradoUSA
| | - Lief A. Wiechman
- U.S. Geological SurveyEcosystems Mission AreaFort CollinsColoradoUSA
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Monroe AP, Heinrichs JA, Whipple AL, O'Donnell MS, Edmunds DR, Aldridge CL. Spatial scale selection for informing species conservation in a changing landscape. Ecosphere 2022. [DOI: 10.1002/ecs2.4320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Affiliation(s)
- Adrian P. Monroe
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | - Julie A. Heinrichs
- Natural Resource Ecology Laboratory Colorado State University, in cooperation with the U.S. Geological Survey, Fort Collins Science Center Fort Collins Colorado USA
| | - Ashley L. Whipple
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | | | - David R. Edmunds
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | - Cameron L. Aldridge
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
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O'Donnell MS, Edmunds DR, Aldridge CL, Heinrichs JA, Monroe AP, Coates PS, Prochazka BG, Hanser SE, Wiechman LA. Defining fine‐scaled population structure among continuously distributed populations. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | - David R. Edmunds
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | - Cameron L. Aldridge
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | - Julie A. Heinrichs
- Natural Resource Ecology Laboratory Colorado State University, Fort Collins, CO in cooperation with the U.S. Geological Survey, Fort Collins Science Center Fort Collins Colorado USA
| | - Adrian P. Monroe
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | - Peter S. Coates
- U.S. Geological Survey, Western Ecological Research Center Dixon Field Station Dixon California USA
| | - Brian G. Prochazka
- U.S. Geological Survey, Western Ecological Research Center Dixon Field Station Dixon California USA
| | - Steve E. Hanser
- U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA
| | - Lief A. Wiechman
- U.S. Geological Survey Ecosystems Mission Area Fort Collins Colorado USA
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