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Demographic network and multi-season occupancy modeling of Rana sylvatica reveal spatial and temporal patterns of population connectivity and persistence

机译:林蛙的人口网络和多季节居住模型揭示了人口连通性和持久性的时空格局

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摘要

Many populations are spatially structured with frequent extinction-colonization events. A clear understanding of these processes is necessary for making informed and effective management decisions. Due to the spatially and temporally dynamic nature of many systems, population connectivity and local extinction-colonization processes can be difficult to assess, but graph theoretic and occupancy modeling approaches are increasingly being utilized to answer such vital ecological questions. In our study, we used 6 years of egg mass counts from 34 ponds for Rana sylvatica to parameterize spatially explicit demographic network models. Our models revealed that the studied populations have spatial structure with strong source-sink dynamics. We also assessed the colonization and persistence probability of each pond using multi-season occupancy modeling. We observed extreme fluctuation in reproductive effort among years, resulting in variable levels of connectivity across the landscape. Pond colonization and persistence were most influenced by local population dynamics, but colonization was also affected by precipitation. Our demographic network model had moderate ability to predict reproductive effort, but accuracy was hindered by variation in annual precipitation. Source populations had higher colonization and persistence rates as well as a greater proportion of ravine habitat within 1,000 m than sink populations. By linking a spatially explicit connectivity model with a temporal occupancy/persistence model, we provide a framework for interpreting patterns of occupancy and dispersal that can serve as an initial guide for future habitat management and restoration.
机译:许多种群在空间结构上都有频繁的灭绝-殖民化事件。必须对这些过程有一个清晰的了解,以便做出明智而有效的管理决策。由于许多系统的时空动态特性,可能难以评估人口连通性和局部灭绝殖民化过程,但是越来越多地利用图论和居住建模方法来回答这些至关重要的生态问题。在我们的研究中,我们使用了来自34个池塘的6年生鸡蛋计数来对林蛙进行参数化,以对空间明确的人口统计网络模型进行参数化。我们的模型表明,研究的种群具有强烈的源汇动态的空间结构。我们还使用多季节占用模型评估了每个池塘的定殖和持久性概率。我们观察到多年间生殖力的极大波动,导致整个景观的连接水平各不相同。池塘的定居和持久性受当地人口动态的影响最大,但定居也受到降水的影响。我们的人口网络模型具有适度的预测生殖力的能力,但精度受年降水量变化的影响。源种群比沉种群具有更高的定植和持久化率,以及1000 m以内的峡谷生境比例更高。通过将空间显式连通性模型与时间占用/持久性模型链接在一起,我们提供了一个解释占用和分散模式的框架,可以作为未来栖息地管理和恢复的初步指南。

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