Berries and bullets: influence of food and mortality risk on grizzly bears in British Columbia Bayas y balas: influencia de la alimentación y el riesgo de mortalidad en los osos grizzly en la Columbia Británica Des baies et des balles: influence de l'alimentation et risques de mortalité chez les ours grizzlys de la Colombie-Britannique

IF 4.3 1区 生物学 Q1 ECOLOGY
Michael F. Proctor, Clayton. T. Lamb, John Boulanger, A. Grant MacHutchon, Wayne F. Kasworm, David Paetkau, Cori L. Lausen, Eric C. Palm, Mark S. Boyce, Christopher Servheen
{"title":"Berries and bullets: influence of food and mortality risk on grizzly bears in British Columbia\n Bayas y balas: influencia de la alimentación y el riesgo de mortalidad en los osos grizzly en la Columbia Británica\n Des baies et des balles: influence de l'alimentation et risques de mortalité chez les ours grizzlys de la Colombie-Britannique","authors":"Michael F. Proctor,&nbsp;Clayton. T. Lamb,&nbsp;John Boulanger,&nbsp;A. Grant MacHutchon,&nbsp;Wayne F. Kasworm,&nbsp;David Paetkau,&nbsp;Cori L. Lausen,&nbsp;Eric C. Palm,&nbsp;Mark S. Boyce,&nbsp;Christopher Servheen","doi":"10.1002/wmon.1078","DOIUrl":null,"url":null,"abstract":"<p>The influence of bottom-up food resources and top-down mortality risk underlies the demographic trajectory of wildlife populations. For species of conservation concern, understanding the factors driving population dynamics is crucial to effective management and, ultimately, conservation. In southeastern British Columbia, Canada, populations of the mostly omnivorous grizzly bear (<i>Ursus arctos</i>) are fragmented into a mosaic of small isolated or larger partially connected sub-populations. They obtain most of their energy from vegetative resources that are also influenced by human activities. Roads and associated motorized human access shape availability of food resources but also displace bears and facilitate human-caused mortality. Effective grizzly bear management requires an understanding of the relationship between habitat quality and mortality risk. We integrated analyses of bottom-up and top-down demographic parameters to understand and inform a comprehensive and efficient management paradigm across the region. Black huckleberry (<i>Vaccinium membranaceum</i>) is the key high-energy food for grizzly bears in much of southeastern British Columbia. Little is known about where and why huckleberries grow into patches that are useful for grizzly bears (i.e., densely clustered fruiting shrubs that provide efficient access to high energy food) and how forage supply and mortality risk influence population vital rates. By following 43 grizzly bears tracked with global positioning system (GPS) collars (57 bear years) in a 14,236-km<sup>2</sup> focal area spanning the Selkirk and Purcell mountain ranges, we developed a model to identify huckleberry patches from grizzly bear use data. Over 2 years we visited 512 sites used by bears, identifying more than 300 huckleberry patches. We used boosted regression tree modeling associating geophysical, ecological, soil, climate, and topographical variables with huckleberry patches. We integrated this modeled food layer depicting an important pre-hibernation resource, into broader bottom-up and top-down analyses. In addition to berries, we examined bottom-up variables indexing vegetative productivity that were previously found to be predictive of bear use (e.g., alpine, canopy cover, greenness, riparian). We also examined top-down variables including road presence, road density, distance-to-road, secure habitat (defined as 500 m away from a road open to vehicular access), highways, human development, and terrain ruggedness. We evaluated the relationship of these variables to female habitat selection, fitness, and population density, testing the predictability and interrelatedness of covariates relative to bottom-up and top-down influences. We estimated resource selection functions with 20,293 GPS telemetry locations collected over 10 years from 20 female grizzly bears. We modeled fitness using logistic regression of spatially explicit reproductive data derived from genetically identified family pedigrees consisting of a mother, father, and offspring. Data included 33 mothers and 72 offspring (1–8 offspring per female). We estimated density through spatial capture-recapture analysis of 126 grizzly bears detected with hair-sampled DNA 287 times between 1998 and 2005. In all 3 analyses (habitat selection, fitness, and density), huckleberry patches were the most influential bottom-up factor and secure habitat was the most consistent top-down variable (road density was similarly predictive). All of the best supported models contained bottom-up and top-down variables except the male density model, which only contained a top-down variable (secure habitat). These results suggest that both bottom-up and top-down forces drive several population processes of grizzly bears in the region, especially for females. We found that 38% of huckleberry patches (235 km<sup>2</sup>) predicted by the top model were in non-secure habitat and that these patches were associated with lower fitness and density relative to those in secure habitat. Grizzly bear density was 2.6 times higher in habitat with road densities &lt;0.6 km/km<sup>2</sup>, supporting the use of this road density target for management. The models predict that applying motorized access controls to backcountry areas with huckleberry patches would increase grizzly bear abundance by 23% on average across the region and 125% in the lowest density portion of the study area (Yahk). Managing both bottom-up and top-down influences is necessary to best mitigate the expanding human footprint, which is affecting many carnivore species worldwide. We provide evidence that bottom-up forces were more influential for female habitat selection, fitness, and density than top-down effects. We also uncovered a critical pattern in the magnitude of top-down and bottom-up influences on behavioral (habitat selection) and demographic (population density and fitness) responses. We show that the relative influence of top-down influences on habitat selection and fitness are relatively weak compared to bottom-up influences, whereas top-down pressures exert much stronger limiting forces on population density. Forming conservation decisions around behavioral responses alone may misdirect actions and have limited benefits to populations. This insight can facilitate more effective decision-making for grizzly bear conservation. Our findings highlight the importance of considering both bottom-up and top-down influences, suggesting cautious interpretation of habitat selection models for any species. A comprehensive examination with population-level metrics such as density, vital rates, and fitness may be needed for effective management.</p>","PeriodicalId":235,"journal":{"name":"Wildlife Monographs","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wmon.1078","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wildlife Monographs","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/wmon.1078","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The influence of bottom-up food resources and top-down mortality risk underlies the demographic trajectory of wildlife populations. For species of conservation concern, understanding the factors driving population dynamics is crucial to effective management and, ultimately, conservation. In southeastern British Columbia, Canada, populations of the mostly omnivorous grizzly bear (Ursus arctos) are fragmented into a mosaic of small isolated or larger partially connected sub-populations. They obtain most of their energy from vegetative resources that are also influenced by human activities. Roads and associated motorized human access shape availability of food resources but also displace bears and facilitate human-caused mortality. Effective grizzly bear management requires an understanding of the relationship between habitat quality and mortality risk. We integrated analyses of bottom-up and top-down demographic parameters to understand and inform a comprehensive and efficient management paradigm across the region. Black huckleberry (Vaccinium membranaceum) is the key high-energy food for grizzly bears in much of southeastern British Columbia. Little is known about where and why huckleberries grow into patches that are useful for grizzly bears (i.e., densely clustered fruiting shrubs that provide efficient access to high energy food) and how forage supply and mortality risk influence population vital rates. By following 43 grizzly bears tracked with global positioning system (GPS) collars (57 bear years) in a 14,236-km2 focal area spanning the Selkirk and Purcell mountain ranges, we developed a model to identify huckleberry patches from grizzly bear use data. Over 2 years we visited 512 sites used by bears, identifying more than 300 huckleberry patches. We used boosted regression tree modeling associating geophysical, ecological, soil, climate, and topographical variables with huckleberry patches. We integrated this modeled food layer depicting an important pre-hibernation resource, into broader bottom-up and top-down analyses. In addition to berries, we examined bottom-up variables indexing vegetative productivity that were previously found to be predictive of bear use (e.g., alpine, canopy cover, greenness, riparian). We also examined top-down variables including road presence, road density, distance-to-road, secure habitat (defined as 500 m away from a road open to vehicular access), highways, human development, and terrain ruggedness. We evaluated the relationship of these variables to female habitat selection, fitness, and population density, testing the predictability and interrelatedness of covariates relative to bottom-up and top-down influences. We estimated resource selection functions with 20,293 GPS telemetry locations collected over 10 years from 20 female grizzly bears. We modeled fitness using logistic regression of spatially explicit reproductive data derived from genetically identified family pedigrees consisting of a mother, father, and offspring. Data included 33 mothers and 72 offspring (1–8 offspring per female). We estimated density through spatial capture-recapture analysis of 126 grizzly bears detected with hair-sampled DNA 287 times between 1998 and 2005. In all 3 analyses (habitat selection, fitness, and density), huckleberry patches were the most influential bottom-up factor and secure habitat was the most consistent top-down variable (road density was similarly predictive). All of the best supported models contained bottom-up and top-down variables except the male density model, which only contained a top-down variable (secure habitat). These results suggest that both bottom-up and top-down forces drive several population processes of grizzly bears in the region, especially for females. We found that 38% of huckleberry patches (235 km2) predicted by the top model were in non-secure habitat and that these patches were associated with lower fitness and density relative to those in secure habitat. Grizzly bear density was 2.6 times higher in habitat with road densities <0.6 km/km2, supporting the use of this road density target for management. The models predict that applying motorized access controls to backcountry areas with huckleberry patches would increase grizzly bear abundance by 23% on average across the region and 125% in the lowest density portion of the study area (Yahk). Managing both bottom-up and top-down influences is necessary to best mitigate the expanding human footprint, which is affecting many carnivore species worldwide. We provide evidence that bottom-up forces were more influential for female habitat selection, fitness, and density than top-down effects. We also uncovered a critical pattern in the magnitude of top-down and bottom-up influences on behavioral (habitat selection) and demographic (population density and fitness) responses. We show that the relative influence of top-down influences on habitat selection and fitness are relatively weak compared to bottom-up influences, whereas top-down pressures exert much stronger limiting forces on population density. Forming conservation decisions around behavioral responses alone may misdirect actions and have limited benefits to populations. This insight can facilitate more effective decision-making for grizzly bear conservation. Our findings highlight the importance of considering both bottom-up and top-down influences, suggesting cautious interpretation of habitat selection models for any species. A comprehensive examination with population-level metrics such as density, vital rates, and fitness may be needed for effective management.

Abstract Image

浆果和子弹:食物和死亡率风险对不列颠哥伦比亚省灰熊的影响
自下而上的食物资源和自上而下的死亡风险的影响是野生动物种群人口轨迹的基础。对于受保护的物种来说,了解驱动种群动态的因素对于有效管理以及最终的保护至关重要。在加拿大不列颠哥伦比亚省东南部,以杂食性为主的灰熊(Ursus arctos)种群被分割成一个由小的孤立或较大的部分连接的亚种群组成的马赛克。它们的大部分能量来自植物资源,这些资源也受到人类活动的影响。道路和相关的机动人类通道影响了食物资源的可用性,但也使熊流离失所,并助长了人为死亡。有效的灰熊管理需要了解栖息地质量和死亡风险之间的关系。我们整合了自下而上和自上而下的人口统计参数分析,以了解并为整个地区的全面高效管理模式提供信息。黑越橘(膜越橘)是不列颠哥伦比亚省东南部大部分地区灰熊的主要高能食物。关于越橘在哪里以及为什么会长成对灰熊有用的斑块(即密集的结果灌木,可以有效地获得高能量食物),以及饲料供应和死亡风险如何影响种群生命率,人们知之甚少。通过在塞尔柯克山脉和珀塞尔山脉14236-km2的焦点区域跟踪43只使用全球定位系统(GPS)项圈追踪的灰熊(57熊年),我们开发了一个模型,从灰熊的使用数据中识别huckleberry斑块。在两年多的时间里,我们访问了512个熊使用的地点,确定了300多个杨梅斑块。我们使用了增强回归树模型,将地球物理、生态、土壤、气候和地形变量与杨梅斑块联系起来。我们将描绘冬眠前重要资源的建模食物层整合到更广泛的自下而上和自上而下的分析中。除了浆果,我们还研究了自下而上的变量,这些变量索引了以前被发现可以预测熊使用的营养生产力(例如,高山、树冠覆盖、绿色、河岸)。我们还研究了自上而下的变量,包括道路存在、道路密度、到道路的距离、安全栖息地(定义为500 m距离一条可供车辆通行的道路)、高速公路、人类发展和地形崎岖。我们评估了这些变量与雌性栖息地选择、适合度和种群密度的关系,测试了协变量相对于自下而上和自上而下影响的可预测性和相关性。我们用10年来从20只雌性灰熊身上收集的20293个GPS遥测位置估计了资源选择功能。我们使用从由母亲、父亲和后代组成的基因鉴定的家庭谱系中获得的空间显性生殖数据的逻辑回归来建模适合度。数据包括33名母亲和72名子女(每名女性生育1-8名子女)。我们通过对126只灰熊的空间捕获-再捕获分析来估计密度,这些灰熊在1998年至2005年间进行了287次毛发DNA采样。在所有3项分析(栖息地选择、适宜性和密度)中,越橘斑块是最具影响力的自下而上的因素,安全栖息地是最一致的自上而下的变量(道路密度也具有类似的预测性)。除雄性密度模型外,所有支持最好的模型都包含自下而上和自上而下的变量,该模型只包含自上而下的变量(安全栖息地)。这些结果表明,自下而上和自上而下的力量推动了该地区灰熊的几个种群过程,尤其是雌性灰熊。我们发现38%的杨梅斑块(235 km2)位于非安全栖息地,并且与安全栖息地相比,这些斑块的适应度和密度较低。灰熊的密度是栖息地的2.6倍,道路密度&lt;0.6 公里/平方公里,支持使用该道路密度目标进行管理。模型预测,对有杨梅斑块的偏远地区实施机动出入控制,将使整个地区的灰熊数量平均增加23%,在研究区密度最低的地区(Yahk)将增加125%。管理自下而上和自上而下的影响对于最好地减轻不断扩大的人类足迹是必要的,人类足迹正在影响世界各地的许多食肉动物物种。我们提供的证据表明,自下而上的力量对雌性栖息地的选择、适应性和密度的影响比自上而下的影响更大。我们还发现了自上而下和自下而上对行为(栖息地选择)和人口(种群密度和适应度)反应的影响程度的关键模式。 我们发现,与自下而上的影响相比,自上而下的影响对栖息地选择和适宜性的相对影响相对较弱,而自上而下的压力对种群密度施加了更强的限制力。仅围绕行为反应制定保护决策可能会误导行动,对种群的益处有限。这一见解可以促进灰熊保护的更有效决策。我们的研究结果强调了考虑自下而上和自上而下影响的重要性,建议对任何物种的栖息地选择模型进行谨慎的解释。为了有效管理,可能需要对人口水平指标进行全面检查,如密度、生命率和健康状况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Wildlife Monographs
Wildlife Monographs 生物-动物学
CiteScore
9.10
自引率
0.00%
发文量
3
审稿时长
>12 weeks
期刊介绍: Wildlife Monographs supplements The Journal of Wildlife Management with focused investigations in the area of the management and conservation of wildlife. Abstracting and Indexing Information Academic Search Alumni Edition (EBSCO Publishing) Agricultural & Environmental Science Database (ProQuest) Biological Science Database (ProQuest) CAB Abstracts® (CABI) Earth, Atmospheric & Aquatic Science Database (ProQuest) Global Health (CABI) Grasslands & Forage Abstracts (CABI) Helminthological Abstracts (CABI) Natural Science Collection (ProQuest) Poultry Abstracts (CABI) ProQuest Central (ProQuest) ProQuest Central K-543 Research Library (ProQuest) Research Library Prep (ProQuest) SciTech Premium Collection (ProQuest) Soils & Fertilizers Abstracts (CABI) Veterinary Bulletin (CABI)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信