東華大學圖書館 |

The Ecology of Fear in a Wild Social Primate.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The Ecology of Fear in a Wild Social Primate./
作者:	LaBarge, Laura R.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	206 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-01, Section: B.
Contained By:	Dissertations Abstracts International83-01B.
標題:	Biology. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28412878
ISBN:	9798516935084

The Ecology of Fear in a Wild Social Primate.
LaBarge, Laura R.

The Ecology of Fear in a Wild Social Primate. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 206 p.

Source: Dissertations Abstracts International, Volume: 83-01, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2021.

This item must not be sold to any third party vendors.

Predation is a key species interaction that often has strong direct and indirect effects on ecological communities. These indirect effects are shaped by changes in prey densities and the behavioral tactics that prey consistently use to avoid being detected. Human-induced fear in wildlife similarly has the potential to alter animal behavior, with especially strong effects on non-prey animals like large carnivores (Lindsey et al., 2017; Smith et al., 2017; Wolf & Ripple, 2017). This presents a challenge to researchers used to collecting behavioral data via direct observations of wildlife in natural settings because study subjects purposefully habituated to researcher presence will necessarily be much more tolerant of humans than surrounding wildlife. In Chapter 2, I review methods used for studying antipredator behavior in primates to evaluate how much of a problem these observer effects are for primatology and find that direct observation of habituated subjects is still by far the most common method of data collection. Yet, newer methods involving remote sensing technologies and greater reliance on field experiments are slowly being adopted. These are critical for a better understanding of the basic behavioral ecology of wild primates and for devising effective conservation plans. My empirical chapters also focus on antipredator behavior and for each of these I use data I collected on two habituated groups of samango monkeys found in the western Soutpansberg mountains of South Africa. This study location has a relatively intact predator guild of leopard, brown hyena, several eagle species, mesopredators, and snakes, which is rare for a primatological field site. My data collection for these projects began in May 2017, including a 15-month field season from 2018-2019. Previous studies conducted with these samangos indicated that they tend to perceive themselves to be safer from predators while observed by humans (Nowak et al., 2014), but that risk from aerial predators is an important predictor of their landscape utilization (Coleman & Hill, 2014a). This work on samango "landscapes of fear" led me to question whether these observed patterns of spatial avoidance were the result of aggregating data on eagle encounters which could result in samango groups fleeing a dangerous area or whether these observations indicate that these animals might remember where they had encountered predators in the past. In Chapter 3, I investigate this question using information on group spatial cohesion-a widely studied risk-sensitive behavior-and asked whether groups of samangos become more cohesive during risky times or while in risky places (in the absence of an immediate threat). To do this, I used a combination of direct observations and GPS-recorded predator and intergroup competitor encounters. My results suggested that groups tended to increase cohesion reactively during intergroup conflicts-but not during eagle encounters. This, however, contrasted with findings that my smaller study group tended to be more cohesive in places where eagle risk was high, but not in locations where the risk of encountering another group was high. This should add to our knowledge of animal "landscapes of fear" because most of these studies, thus far, have not looked at behavioral differences across landscapes of relative risk. During data collection for Chapter 3, field assistants and I encountered relatively few terrestrial predators (n = 4 leopard encounters versus n = 74 eagle predation attempts), suggesting that aerial predators are less affected by human presence. To get a better picture of how samangos respond to different predator guilds, I used field experiments with models of three confirmed samango predators (leopard, eagle and python) (Chapter 4). Specifically, I used time-limited experiments with only part of each samango group exposed to each model to gauge whether predator type, group cohesion, scanning behavior, and/or habitat characteristics would best predict how far antipredator responses spread throughout the study groups. Individual samangos responded to each model with alarm calls and other fearful reactions, but information about these potential threats did not always reach the rest of the group. Habitat visibility was a key predictor affecting the extent of collective predator detection, but the importance of antipredator behavior (scanning and spatial cohesion), depended on the predator species they encountered. These results suggest that the effectiveness of purported risk-sensitive strategies varies based on the type of threat samangos encounter. Perhaps most importantly, responses to the leopard model were consistently stronger than responses to the eagle or snake model. This may suggest that perception of risk may not align strongly with actual risk. Alternatively, terrestrial predators pose a greater threat to samangos than we realize based on observations alone. In my final empirical chapter (5), I investigated whether hormonal changes might indicate when samangos experience predator-induced stress and, if so, whether human observers could modulate these responses. Fecal cortisol metabolite concentrations (FCMs) can track environmental challenges and perturbations, with heightened levels often serving as an indicator of physiological stress. Samangos at my study site were followed on a rotated schedule and spent 3-4 days each week unobserved by researchers. Due to a 24hr lag between an event and a resultant change in FCM levels, this meant that I was able to evaluate whether human presence/absence could predict variation in FCMs. Using 192 samples from 13 individuals, I compared support for models incorporating information on researcher presence with models of food availability, thermoregulation, and water stress. Models incorporating information on the three environmental challenges were better supported than those including information on human presence/absence. I then used a subset of data (n = 82) where samangos were observed the previous day to evaluate if, instead, human presence might dampen responses to intergroup competitors or predators. FCM levels appeared to reflect variation in perceived predation risk as levels increased with the number of predator encounters/predator alarms emitted by the group each day. Yet, when three or more observers were present this response was apparently dampened. Despite intergroup competition also being a potentially risky event, I found no evidence that these affected FCM concentrations. These findings suggest that limiting the number of human observers with habituated animal groups might be an effective way of mitigating some observer effects. Chapters 2, 3, and 4 are reprints of previously published journal articles. In each of these studies I conceived of the study design, collected, and analyzed data, and was the primary author of the manuscript.

ISBN: 9798516935084Subjects--Topical Terms:

522710
Biology.
Subjects--Index Terms:

Cortisol

The Ecology of Fear in a Wild Social Primate.
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520 $a Predation is a key species interaction that often has strong direct and indirect effects on ecological communities. These indirect effects are shaped by changes in prey densities and the behavioral tactics that prey consistently use to avoid being detected. Human-induced fear in wildlife similarly has the potential to alter animal behavior, with especially strong effects on non-prey animals like large carnivores (Lindsey et al., 2017; Smith et al., 2017; Wolf & Ripple, 2017). This presents a challenge to researchers used to collecting behavioral data via direct observations of wildlife in natural settings because study subjects purposefully habituated to researcher presence will necessarily be much more tolerant of humans than surrounding wildlife. In Chapter 2, I review methods used for studying antipredator behavior in primates to evaluate how much of a problem these observer effects are for primatology and find that direct observation of habituated subjects is still by far the most common method of data collection. Yet, newer methods involving remote sensing technologies and greater reliance on field experiments are slowly being adopted. These are critical for a better understanding of the basic behavioral ecology of wild primates and for devising effective conservation plans. My empirical chapters also focus on antipredator behavior and for each of these I use data I collected on two habituated groups of samango monkeys found in the western Soutpansberg mountains of South Africa. This study location has a relatively intact predator guild of leopard, brown hyena, several eagle species, mesopredators, and snakes, which is rare for a primatological field site. My data collection for these projects began in May 2017, including a 15-month field season from 2018-2019. Previous studies conducted with these samangos indicated that they tend to perceive themselves to be safer from predators while observed by humans (Nowak et al., 2014), but that risk from aerial predators is an important predictor of their landscape utilization (Coleman & Hill, 2014a). This work on samango "landscapes of fear" led me to question whether these observed patterns of spatial avoidance were the result of aggregating data on eagle encounters which could result in samango groups fleeing a dangerous area or whether these observations indicate that these animals might remember where they had encountered predators in the past. In Chapter 3, I investigate this question using information on group spatial cohesion-a widely studied risk-sensitive behavior-and asked whether groups of samangos become more cohesive during risky times or while in risky places (in the absence of an immediate threat). To do this, I used a combination of direct observations and GPS-recorded predator and intergroup competitor encounters. My results suggested that groups tended to increase cohesion reactively during intergroup conflicts-but not during eagle encounters. This, however, contrasted with findings that my smaller study group tended to be more cohesive in places where eagle risk was high, but not in locations where the risk of encountering another group was high. This should add to our knowledge of animal "landscapes of fear" because most of these studies, thus far, have not looked at behavioral differences across landscapes of relative risk. During data collection for Chapter 3, field assistants and I encountered relatively few terrestrial predators (n = 4 leopard encounters versus n = 74 eagle predation attempts), suggesting that aerial predators are less affected by human presence. To get a better picture of how samangos respond to different predator guilds, I used field experiments with models of three confirmed samango predators (leopard, eagle and python) (Chapter 4). Specifically, I used time-limited experiments with only part of each samango group exposed to each model to gauge whether predator type, group cohesion, scanning behavior, and/or habitat characteristics would best predict how far antipredator responses spread throughout the study groups. Individual samangos responded to each model with alarm calls and other fearful reactions, but information about these potential threats did not always reach the rest of the group. Habitat visibility was a key predictor affecting the extent of collective predator detection, but the importance of antipredator behavior (scanning and spatial cohesion), depended on the predator species they encountered. These results suggest that the effectiveness of purported risk-sensitive strategies varies based on the type of threat samangos encounter. Perhaps most importantly, responses to the leopard model were consistently stronger than responses to the eagle or snake model. This may suggest that perception of risk may not align strongly with actual risk. Alternatively, terrestrial predators pose a greater threat to samangos than we realize based on observations alone. In my final empirical chapter (5), I investigated whether hormonal changes might indicate when samangos experience predator-induced stress and, if so, whether human observers could modulate these responses. Fecal cortisol metabolite concentrations (FCMs) can track environmental challenges and perturbations, with heightened levels often serving as an indicator of physiological stress. Samangos at my study site were followed on a rotated schedule and spent 3-4 days each week unobserved by researchers. Due to a 24hr lag between an event and a resultant change in FCM levels, this meant that I was able to evaluate whether human presence/absence could predict variation in FCMs. Using 192 samples from 13 individuals, I compared support for models incorporating information on researcher presence with models of food availability, thermoregulation, and water stress. Models incorporating information on the three environmental challenges were better supported than those including information on human presence/absence. I then used a subset of data (n = 82) where samangos were observed the previous day to evaluate if, instead, human presence might dampen responses to intergroup competitors or predators. FCM levels appeared to reflect variation in perceived predation risk as levels increased with the number of predator encounters/predator alarms emitted by the group each day. Yet, when three or more observers were present this response was apparently dampened. Despite intergroup competition also being a potentially risky event, I found no evidence that these affected FCM concentrations. These findings suggest that limiting the number of human observers with habituated animal groups might be an effective way of mitigating some observer effects. Chapters 2, 3, and 4 are reprints of previously published journal articles. In each of these studies I conceived of the study design, collected, and analyzed data, and was the primary author of the manuscript.
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