Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity
Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity
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DOI：
10.1007/s10980-018-0637-9
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发表时间：
2018-04
影响因子：
5.2
通讯作者：
Mariëlle L. van Toor;B. Kranstauber;S. Newman;D. Prosser;J. Takekawa;G. Technitis;R. Weibel;M. Wikelski;K. Safi
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文献类型：
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作者：
Mariëlle L. van Toor;B. Kranstauber;S. Newman;D. Prosser;J. Takekawa;G. Technitis;R. Weibel;M. Wikelski;K. Safi
高分辨率的动物运动数据变得越来越可用，但仅凭大量的经验轨迹并不能让我们轻松预测动物运动。为了回答生态和进化问题，在人口水平上，一个物种的潜力，连接补丁或populationis of importance.ObjectivesWe引入一种方法，结合运动知情的模拟轨迹与环境知情的估计的轨迹的可扩展性，以获得连接。以斑头雁为例，我们估计在整个年度周期在其native range.MethodsWe的跟踪数据斑头雁的景观水平迁移连接开发一个多状态运动模型，并估计时间明确的栖息地适合在物种的范围内。我们模拟了山脉碎片之间的迁徙运动，并计算了一个我们称之为路线可行性的指标。结果进行比较，从已发表的literature.ResultsSimulated迁移匹配的经验轨迹的关键特征，如中途停留时间。模拟轨迹的可行性与经验轨迹的可行性相似。我们发现，总体而言，迁徙的连通性是更高的繁殖比在越冬地区，证实了以前的研究结果，为这个物种.ConclusionsWe显示如何实证跟踪数据和环境信息可以融合有意义的预测动物运动全年，甚至以外的空间范围内的可用数据。除了预测迁移的连通性，我们的框架将被证明是有用的动物运动，如种子传播或疾病生态学促进生态过程的建模。
ContextHigh-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.ObjectivesWe introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.MethodsWe used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.ResultsSimulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species.ConclusionsWe show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.