five

Data from: Fearlessness towards extirpated large carnivores may exacerbate the impacts of naïve mesocarnivores

收藏
DataONE2016-11-18 更新2024-06-26 收录
下载链接:
https://search.dataone.org/view/null
下载链接
链接失效反馈
资源简介:
By suppressing mesocarnivore foraging, the fear large carnivores inspire can be critical to mitigating mesocarnivore impacts. Where large carnivores have declined, mesocarnivores may quantitatively increase foraging, commensurate with reductions in fear. The extirpation of large carnivores may further exacerbate mesocarnivore impacts by causing qualitative changes in mesocarnivore behavior. Error management theory suggests that, where predators are present, prey should be biased towards over-responsiveness to predator cues, abandoning foraging in response to both predator cues and benign stimuli mistaken for predator cues (false-positives). Where predators are absent, prey may avoid these foraging costs by becoming unresponsive (naïve) to both predator cues and false-positives. If naiveté occurs in mesocarnivores where large carnivores have been extirpated, it could substantively exacerbate their impacts, as ‘fearless’ mesocarnivores may engage in virtually unrestricted foraging. We tested the naiveté of raccoons (Procyon lotor) to extirpated large carnivores in the context of a larger experiment demonstrating that fear of large carnivores can mediate mesocarnivore impacts. Raccoon responsiveness to playbacks of their extirpated large carnivore predators (cougars, Puma conolor; bears, Ursus americanus) was significantly less than to the only extant large carnivore predator (dogs), and was no greater than to non-predators (‘seals’; Phoca vitulina, Eumetopias jubatus). Raccoons failed to recognize their now extirpated predators as threatening, spending as much time foraging as when hearing non-predators, which we estimate has substantive impacts, based on results from the larger experiment. We discuss the potentially powerful role of ‘fearlessness’ in exacerbating mesocarnivore impacts in systems where large carnivores have been lost.
创建时间:
2016-11-18
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4099个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

THCHS-30

“THCHS30是由清华大学语音与语言技术中心(CSLT)发布的开放式汉语语音数据库。原始录音是2002年在清华大学国家重点实验室的朱晓燕教授的指导下,由王东完成的。清华大学计算机科学系智能与系统,原名“TCMSD”,意思是“清华连续普通话语音数据库”,时隔13年出版,由王东博士发起,并得到了教授的支持。朱小燕。我们希望为语音识别领域的新研究人员提供一个玩具数据库。因此,该数据库对学术用户完全免费。整个软件包包含建立中文语音识别所需的全套语音和语言资源系统。”

OpenDataLab 收录

DIOR

“DIOR” 是用于光学遥感图像中对象检测的大规模基准数据集,该数据集由23,463图像和带有水平边界框注释的192,518对象实例组成。

OpenDataLab 收录

LIDC-IDRI

LIDC-IDRI 数据集包含来自四位经验丰富的胸部放射科医师的病变注释。 LIDC-IDRI 包含来自 1010 名肺部患者的 1018 份低剂量肺部 CT。

OpenDataLab 收录

中国农村金融统计数据

该数据集包含了中国农村金融的统计信息,涵盖了农村金融机构的数量、贷款余额、存款余额、金融服务覆盖率等关键指标。数据按年度和地区分类,提供了详细的农村金融发展状况。

www.pbc.gov.cn 收录

ShapeNet

ShapeNet 是由斯坦福大学、普林斯顿大学和美国芝加哥丰田技术研究所的研究人员开发的大型 3D CAD 模型存储库。该存储库包含超过 3 亿个模型,其中 220,000 个模型被分类为使用 WordNet 上位词-下位词关系排列的 3,135 个类。 ShapeNet Parts 子集包含 31,693 个网格,分为 16 个常见对象类(即桌子、椅子、平面等)。每个形状基本事实包含 2-5 个部分(总共 50 个部分类)。

OpenDataLab 收录