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Estimation of breeding probability can make monitoring data more revealing: a case study of amphibians
Ecological Applications ( IF 5 ) Pub Date : 2021-04-18 , DOI: 10.1002/eap.2357
Sam S Cruickshank 1 , Ariel Bergamini 1 , Benedikt R Schmidt 2, 3
Affiliation  

Monitoring programs serve to detect trends in the distribution and abundance of species. To do so, monitoring programs often use static state variables. Dynamic state variables that describe population dynamics might be more valuable because they allow for a mechanistic understanding of the processes that lead to population trends. We fit multistate occupancy models to data from a country-wide multispecies amphibian occupancy monitoring program and estimated occupancy and breeding probabilities. If breeding probabilities are determinants of occupancy dynamics, then they may serve in monitoring programs as state variables that describe dynamic processes. The results showed that breeding probabilities were low and that a large proportion of the populations had to be considered to be non-breeding populations (i.e., populations where adults are present but no breeding occurs). For some species, the majority of populations were non-breeding populations. We found that non-breeding populations have lower persistence probabilities than populations where breeding occurs. Breeding probabilities may thus explain trends in occupancy but they might also explain other ecological phenomena, such as the success of invasive species, which had high breeding probabilities. Signs of breeding, i.e., the presence of eggs and larvae, were often hard to detect. Importantly, non-breeding populations also had low detection probabilities, perhaps because they had lower abundances. We suggest that monitoring programs should invest more in the detection of life history stages indicative of breeding, and also into the detection of non-breeding populations. We conclude that breeding probability should be used as a state variable in monitoring programs because it can lead to deeper insights into the processes driving occupancy dynamics.

中文翻译:

繁殖概率估算可以使监测数据更具启发性:以两栖动物为例

监测计划用于检测物种分布和丰度的趋势。为此,监控程序通常使用静态变量。描述种群动态的动态状态变量可能更有价值,因为它们允许对导致种群趋势的过程进行机械理解。我们将多州占用模型与来自全国多物种两栖动物占用监测计划的数据以及估计的占用和繁殖概率相匹配。如果繁殖概率是占用动态的决定因素,那么它们可以在监测程序中作为描述动态过程的状态变量。结果表明,繁殖概率很低,而且很大一部分种群必须被认为是非繁殖种群(即,成虫存在但没有繁殖的种群)。对于某些物种,大多数种群是非繁殖种群。我们发现非繁殖种群的持续概率低于繁殖发生的种群。因此,繁殖概率可以解释入住率的趋势,但它们也可以解释其他生态现象,例如具有高繁殖概率的入侵物种的成功。繁殖的迹象,即卵和幼虫的存在,通常很难被发现。重要的是,非繁殖种群的检测概率也很低,这可能是因为它们的丰度较低。我们建议监测计划应该更多地投资于检测指示繁殖的生活史阶段,以及检测非繁殖种群。
更新日期:2021-04-18
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