根据足迹计数改进人口密度估计:通过跟踪博茨瓦纳喀拉哈里沙漠的大型食草动物,改善每日旅行距离估计。

IF 3.9 1区 生物学 Q2 ECOLOGY
Marie-Charlotte Gielen, Alessandro Araldi, Marie Jardeaux, Seitshiro Pule, Senxwai Mosololo, Xee Fire Seganaphohu, Duela Seganaphofu, Tebelelo Gabaikanye, Pogiso Ithuteng, Derek Keeping, Nicolas Schtickzelle
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引用次数: 0

摘要

背景:动物轨迹调查可以根据合适的基质和高技能的追踪者,快速监测种群的保护情况。Formozov-Malyshev-Pereleshin (FMP)公式将沿样带的轨迹计数转换为绝对种群密度估计,使用物种的平均每日旅行距离估计(M ^)。它的主要局限性在于不能准确地估计与调查的具体时间和地点有关的M ^。如果没有来自研究区域的经验M ^,则可以通过体重- M ^缩放规则异速估计M ^,但精度较低。本研究旨在通过改进经验和异速M ^估计来提高fmp衍生密度估计的准确性。方法:在博茨瓦纳的Khutse野生动物保护区和Kalahari中部野生动物保护区,我们测试了一种具有成本效益的正向跟踪技术,利用当地认证的跟踪器收集大型食草动物物种的高质量经验M ^。由于异速生长M ^值在喀拉哈里沙漠被低估,我们使用本研究和文献中的经验M ^来校准它们。最后,利用追踪调查和FMP公式对11种草食动物的密度进行了综合估算。结果:通过追踪,我们获得了5种草食动物的经验M ^,证实了研究季节内日移动距离值的时间稳定性。我们推导了两个单独的系数来直接校正卡拉哈里物种的异速生长M ^。基于我们对通过FPM获得的动物密度估计值的解释,我们讨论了M ^的准确性、样带设计和调查工作对种群监测的重要性。结论:本研究证明了前向跟踪技术对沙地大型草食动物M ^的准确估计是有效的。它还提供了直接校正卡拉哈里物种异速生长M ^的系数,并提供了2800平方公里保护区内多种食草动物物种的密度估计。这些新元素加强了在低密度环境中监测野生动物轨迹数据的使用,尽管我们鼓励进一步研究以评估特定时间M ^的必要性。我们还强调在研究中将土著知识与现代技术结合起来的机会,促进与当地社区的互利合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Refining population density estimation from track counts: improving daily travel distance estimates through trailing of large herbivores in the Kalahari, Botswana.

Refining population density estimation from track counts: improving daily travel distance estimates through trailing of large herbivores in the Kalahari, Botswana.

Refining population density estimation from track counts: improving daily travel distance estimates through trailing of large herbivores in the Kalahari, Botswana.

Refining population density estimation from track counts: improving daily travel distance estimates through trailing of large herbivores in the Kalahari, Botswana.

Background: Animal track surveys can enable rapid population monitoring for conservation, contingent on a suitable substrate and highly skilled trackers. The Formozov-Malyshev-Pereleshin (FMP) formula converts track counts along transects into absolute population density estimates, using the species' average daily travel distance estimate ( M ^ ). Its main limitation lies in accurately estimating M ^ relevant to the survey's specific time period and location. If empirical M ^ from the study region is not available, M ^ can be estimated allometrically, but less accurately, through body mass- M ^ scaling rules. This study aims to improve the accuracy of FMP-derived density estimates by refining both empirical and allometric M ^ estimations.

Methods: We tested a cost-effective forward trailing technique to collect high-quality empirical M ^ for large herbivore species with local certified trackers, in Khutse Game Reserve and Central Kalahari Game Reserve, Botswana. Since allometric M ^ values are underestimated in the Kalahari, we calibrated them using empirical M ^ from this study and the literature. Finally, we integrated our findings to estimate densities of 11 herbivore species using track surveys and the FMP formula.

Results: Through trailing, we provided empirical M ^ for five herbivore species, which previously lacked data for the area, and confirmed the temporal stability of daily travel distance values within the study season. We derived two separate coefficients to directly correct allometric M ^ for Kalahari species based on their foraging strategies. Based on our interpretation of the animal density estimates obtained via the FPM, we discuss the importance of the accuracy of M ^ , transect design, and survey effort for population monitoring.

Conclusion: Our research demonstrates the effectiveness of the forward trailing technique for accurately estimating M ^ of large herbivores in sandy substrates. It also provides coefficients to directly correct allometric M ^ for Kalahari species and delivers density estimates for multiple herbivores species across 2800 km2 of protected areas. These new elements strengthen the use of track data for wildlife monitoring in low-density environments, although we encourage further research to assess the need of time-specific M ^ . We also highlight opportunities to integrate Indigenous knowledge with modern technology in research, fostering collaboration with local communities for mutual benefit.

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来源期刊
Movement Ecology
Movement Ecology Agricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics
CiteScore
6.60
自引率
4.90%
发文量
47
审稿时长
23 weeks
期刊介绍: Movement Ecology is an open-access interdisciplinary journal publishing novel insights from empirical and theoretical approaches into the ecology of movement of the whole organism - either animals, plants or microorganisms - as the central theme. We welcome manuscripts on any taxa and any movement phenomena (e.g. foraging, dispersal and seasonal migration) addressing important research questions on the patterns, mechanisms, causes and consequences of organismal movement. Manuscripts will be rigorously peer-reviewed to ensure novelty and high quality.
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