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Dynamic multistate occupancy modeling to evaluate population dynamics under a scenario of preferential sampling
Ecosphere ( IF 2.7 ) Pub Date : 2021-04-23 , DOI: 10.1002/ecs2.3469
Guillermo Fandos 1, 2, 3 , Marc Kéry 4 , Luis Santiago Cano‐Alonso 3, 5 , Isidoro Carbonell 6 , José Luis Tellería 3
Affiliation  

Effective conservation of animal populations depends on the availability of reliable data derived from rigorous monitoring protocols, which allows us to assess trends and understand the processes they are governed by. Nevertheless, population monitoring schemes are hampered by multiple sources of errors resulting from specific logistical and survey constraints. Two common complications are the non‐visitation of some sites in certain years and preferential sampling (PS), that is, the tendency to survey “better” sites disproportionately more often. Both factors can lead to serious biases unless accommodated into models. We used 22 yr of nest‐monitoring data to develop a dynamic multistate occupancy model, including a PS component to investigate occupancy and reproduction dynamics in a peripheral Black Stork (Ciconia nigra) population in Spain. We analyzed the effects of climate and nesting substrate (tree vs. cliff) on population dynamics and accounted for PS and non‐visitation biases using a model that distinguished three territorial states: unoccupied, occupied without, or occupied with successful reproduction. We found strong evidence for positive PS, and when accounting for this bias, lower population size estimates were generated. Black stork nests had a high probability of remaining in the same state from one year to the next, with successful nests more likely to be occupied again and to be successful the following year than occupied but unsuccessful or unoccupied nests. Nesting substrate and spring precipitation did not influence state transition probabilities or the probability of reproductive success; nevertheless, cliff nest occupancy was overall higher than tree nest occupancy. Our results highlight the importance of correcting for non‐visitation and PS in habitat occupancy models. If these potential biasing effects are not accounted for, inferences of population size may be overestimate. Multistate occupancy models with correction for PS offer a powerful analytical framework for data collected as part of population studies of unmarked animals. These models compensate for common methodological biases in biological surveys and can help implement efficient conservation strategies based on robust population dynamics estimates.

中文翻译:

在优先抽样情况下评估人口动态的动态多状态占用模型

对动物种群的有效保护取决于从严格的监测规程获得的可靠数据的可用性,这使我们能够评估趋势并了解它们所遵循的过程。然而,由于特定的后勤和调查限制,人口监测计划受到多种错误来源的阻碍。两种常见的复杂性是在某些年份中某些站点的未访问以及优先采样(PS),即倾向于更频繁地调查“更好”的站点。除非纳入模型,否则这两个因素都可能导致严重的偏差。我们使用22年的巢穴监测数据来开发动态多状态居住模型,其中包括PS组件,以研究外围黑鹳(Ciconia nigra)的居住和繁殖动态)西班牙人口。我们分析了气候和筑巢基质(树木与悬崖)对种群动态的影响,并使用可区分三种领土状态的模型解释了PS和非参观偏见:未占领,未占领或成功繁殖。我们找到了有力的证据证明PS阳性,并且当考虑到这种偏见时,得出的人口规模估算值较低。黑鹳的巢穴从一年到下一年保持在相同状态的可能性很高,成功的巢穴比被占领但没有成功或空置的巢穴更有可能再次被占用,并在第二年获得成功。巢状基质和春季降水不会影响状态转变的可能性或繁殖成功的可能性。尽管如此,悬崖巢的占用总体上高于树巢的占用。我们的结果强调了在栖息地占用模型中校正非访问和PS的重要性。如果不考虑这些潜在的偏见效应,则可能会高估人口规模的推论。修正PS的多州占用模型为无标记动物种群研究的一部分提供了强大的分析框架。这些模型弥补了生物学调查中常见的方法学偏见,并且可以基于可靠的人口动态估计值来帮助实施有效的保护策略。人口规模的推论可能被高估了。修正PS的多州占用模型为无标记动物种群研究的一部分提供了强大的分析框架。这些模型弥补了生物学调查中常见的方法学偏见,并且可以基于可靠的人口动态估计值来帮助实施有效的保护策略。人口规模的推论可能被高估了。修正PS的多州占用模型为无标记动物种群研究的一部分提供了强大的分析框架。这些模型弥补了生物学调查中常见的方法学偏见,并且可以基于可靠的人口动态估计值来帮助实施有效的保护策略。
更新日期:2021-04-23
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