Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection

Clarifying species-environment relationships is crucial for the development of efficient conservation and restoration strategies. However, this work is often complicated by a lack of detailed information on species distribution and habitat features and tends to ignore the impact of scale and landscape features. Here, we tracked 11 Oriental White Storks (Ciconia boyciana) with GPS loggers during their wintering period at Poyang Lake and divided the tracking data into two parts (foraging and roosting states) according to the distribution of activity over the course of a day. Then, a three-step multiscale and multistate approach was employed to model habitat selection characteristics: (1) first, we minimized the search range of the scale for these two states based on daily movement characteristics; (2) second, we identified the optimized scale of each candidate variable; and (3) third, we fit a multiscale, multivariable habitat selection model in relation to natural features, human disturbance and especially landscape composition and configuration. Our findings reveal that habitat selection of the storks varied with spatial scale and that these scaling relationships were not consistent across different habitat requirements (foraging or roosting) and environmental features. Landscape configuration was a more powerful predictor for storks’ foraging habitat selection, while roosting was more sensitive to landscape composition. Incorporating high-precision spatiotemporal satellite tracking data and landscape features derived from satellite images from the same periods into a multiscale habitat selection model can greatly improve the understanding of species-environmental relationships and guide efficient recovery planning and legislation.

阐明物种与环境的关系对于制定有效的保护和恢复策略至关重要。然而，由于缺乏有关物种分布和栖息地特征的详细信息，这项工作往往变得复杂，并且往往忽略了尺度和景观特征的影响。在此，我们在鄱阳湖越冬期间使用GPS追踪器对11只东方白鹳（Ciconia boyciana）进行了追踪，并根据一天内活动的分布情况将追踪数据分为两部分（觅食和栖息状态）。然后，采用三步多尺度和多状态方法对栖息地选择特征进行建模：（1）首先，我们根据每日活动特征缩小这两种状态的尺度搜索范围；（2）其次，我们确定每个候选变量的优化尺度；（3）第三，我们构建了一个与自然特征、人类干扰，特别是景观组成和配置相关的多尺度、多变量栖息地选择模型。我们的研究结果表明，东方白鹳的栖息地选择随空间尺度而变化，并且这些尺度关系在不同的栖息地需求（觅食或栖息）和环境特征之间并不一致。景观配置是东方白鹳觅食栖息地选择的一个更有力的预测因子，而栖息对景观组成更为敏感。将高精度时空卫星追踪数据以及同期卫星图像所衍生的景观特征纳入多尺度栖息地选择模型，可以极大地提高对物种 - 环境关系的理解，并指导有效的恢复规划和立法。