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跟踪空间动态,为保护关注物种提供早期预警。

Tracking spatial regimes as an early warning for a species of conservation concern.

机构信息

Agronomy & Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68583-0915, USA.

School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska, 68583-0961, USA.

出版信息

Ecol Appl. 2022 Jan;32(1):e02480. doi: 10.1002/eap.2480. Epub 2021 Nov 23.

DOI:10.1002/eap.2480
PMID:34674399
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9746655/
Abstract

In this era of global environmental change and rapid regime shifts, managing core areas that species require to survive and persist is a grand challenge for conservation. Wildlife monitoring data are often limited or local in scale. The emerging ability to map and track spatial regimes (i.e., the spatial manifestation of state transitions) using advanced geospatial vegetation data has the potential to provide earlier warnings of habitat loss because many species of conservation concern strongly avoid spatial regime boundaries. Using 23 yr of data for the lek locations of Greater Prairie-Chicken (Tympanuchus cupido; GPC) in a remnant grassland ecosystem, we demonstrate how mapping changes in the boundaries between grassland and woodland spatial regimes provide a spatially explicit early warning signal for habitat loss for an iconic and vulnerable grassland-obligate known to be highly sensitive to woody plant encroachment. We tested whether a newly proposed metric for the quantification of spatial regimes captured well-known responses of GPC to woody plant expansion into grasslands. Resource selection functions showed that the grass:woody spatial regime boundary strength explained the probability of 80% of relative lek occurrence, and GPC strongly avoided grass:woody spatial regime boundaries at broad scales. Both findings are consistent with well-known expectations derived from GPC ecology. These results provide strong evidence for vegetation-derived delineations of spatial regimes to serve as generalized signals of early warning for state transitions that have major consequences to biodiversity conservation. Mapping spatial regime boundaries over time provided interpretable early warnings of habitat loss. Woody plant regimes displaced grassland regimes starting from the edges of the study area and constricting inward. Correspondingly, the relative probability of lek occurrence constricted in space. Similarly, the temporal trajectory of spatial regime boundary strength increased over time and moved closer to the observed limit of GPC lek site usage relative to grass:woody boundary strength. These novel spatial metrics allow managers to rapidly screen for early warning signals of spatial regime shifts and adapt management practices to defend and grow habitat cores at broad scales.

摘要

在这个全球环境变化和快速生态系统转变的时代,管理物种生存和延续所需的核心区域是保护面临的重大挑战。野生动物监测数据通常在规模上受到限制或具有局部性。利用先进的地理空间植被数据来绘制和跟踪空间格局(即状态转变的空间表现)的新兴能力有可能更早地发出栖息地丧失的警报,因为许多受到保护关注的物种强烈回避空间格局边界。我们利用遗留草原生态系统中大角草原松鸡(Tympanuchus cupido;GPC)求偶场位置的 23 年数据,展示了绘制草原和林地空间格局边界变化的方法如何为一种标志性和脆弱的草原专性物种提供栖息地丧失的空间明确早期预警信号,该物种已知对木本植物入侵非常敏感。我们测试了一种新提出的空间格局量化指标是否很好地捕捉了 GPC 对木本植物向草原扩张的反应。资源选择函数表明,草地:林地空间格局边界强度解释了相对求偶场发生概率的 80%,并且 GPC 在广泛的尺度上强烈回避草地:林地空间格局边界。这两个发现都与 GPC 生态学中已知的预期一致。这些结果为植被衍生的空间格局划分提供了有力证据,可以作为状态转变的广义早期预警信号,这些转变对生物多样性保护有重大影响。随着时间的推移绘制空间格局边界提供了可解释的栖息地丧失早期预警。木本植物格局从研究区域的边缘开始取代草地格局,并向内收缩。相应地,求偶场发生的相对概率在空间上收缩。同样,空间格局边界强度的时间轨迹随着时间的推移而增加,并且相对于草地:木本边界强度,与 GPC 求偶场使用的相对极限更加接近。这些新的空间指标使管理者能够快速筛选空间格局转变的早期预警信号,并调整管理实践,以在广泛的尺度上保护和扩大栖息地核心。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/a0da1a05842d/EAP-32-0-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/ab060596b774/EAP-32-0-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/2f2acc873483/EAP-32-0-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/a0da1a05842d/EAP-32-0-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/ab060596b774/EAP-32-0-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/2f2acc873483/EAP-32-0-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90be/9746655/a0da1a05842d/EAP-32-0-g003.jpg

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本文引用的文献

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