Habitat Suitability of the Sand Lizard (Lacerta agilis) at Its Distribution Limit—An Analysis Based on Citizen Science Data and Machine Learning

IF 3.4 2区 环境科学与生态学 Q2 ECOLOGY
Alina Krämer, Hanna Meyer, Sascha Buchholz
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引用次数: 0

Abstract

Aim

To inform evidence-based conversation strategies this study aims to assess habitat suitability and connectivity for the Sand Lizard (Lacerta agilis) at its northwestern distribution limit by integrating remote sensing data, machine learning techniques, and citizen science contributions. Comprehending the population dynamics of the Sand Lizard Lacerta agilis is imperative for ensuring the preservation of metapopulations of this matrix-sensitive species.

Location

NW-Germany, Netherlands.

Methods

We integrated citizen science data from observation.org with multispectral Sentinel-2 imagery and auxiliary spatial datasets, including soil types, vegetation indices, topographic features, and proximity to various habitat types. We trained Random Forests which were employed to predict habitat suitability across a region encompassing North Rhine-Westphalia and Lower Saxony in Germany, as well as the Netherlands, at a 10-m spatial resolution. Interpretable machine learning techniques were applied to identify key environmental drivers and corridor analysis was conducted to identify potential barriers to habitat colonisation.

Results

The ability of the model to predict habitat suitability was high (Area under the Curve = 0.935 + − 0.05). Thirty-three parameters were identified as relevant habitat determinants, where the most important group of variables were associated with topography, solar irradiation and soil types. Urban structures, however, further emerged as relevant habitat parameters influencing habitat suitability. Connectivity was mainly provided by linear structures such as railway lines and roadsides.

Main Conclusion

Understanding habitat suitability and connectivity is critical for the effective preservation of metapopulations and the development of robust conservation strategies. Our study demonstrates how integrating remote sensing data with citizen science contributions can effectively be applied for habitat modelling, particularly over large geographical areas. Contrary to previous assumptions that peripheral populations, such as those at the northwestern limit of the Sand Lizard's distribution, may be more specialised, our findings reveal that these lizards exhibit considerable adaptability to a range of environmental conditions, including human-altered landscapes. This adaptability challenges conventional views and underscores the importance of considering anthropogenic environments in conservation planning. By incorporating novel ecosystems and urban areas into species conservation plans, our study contributes to a more inclusive and effective framework for biodiversity conservation.

Abstract Image

沙蜥分布极限的生境适宜性——基于公民科学数据和机器学习的分析
本研究旨在通过整合遥感数据、机器学习技术和公民科学贡献,评估沙蜥(Lacerta agilis)西北分布极限的栖息地适宜性和连通性,为基于证据的对话策略提供信息。了解沙蜥的种群动态是确保这一基质敏感物种的元种群保存的必要条件。位置:德国西北部,荷兰。方法将来自observation.org的公民科学数据与Sentinel-2多光谱影像和辅助空间数据集进行整合,包括土壤类型、植被指数、地形特征和与各种栖息地类型的接近度。我们对随机森林进行了训练,这些随机森林被用来预测包括德国北莱茵-威斯特伐利亚州和下萨克森州以及荷兰在内的一个地区的栖息地适宜性,空间分辨率为10米。应用可解释的机器学习技术来确定关键的环境驱动因素,并进行走廊分析以确定栖息地殖民化的潜在障碍。结果模型对生境适宜性的预测能力较高(曲线下面积= 0.935 +−0.05)。确定了33个参数作为相关的生境决定因素,其中最重要的一组变量与地形、太阳辐照和土壤类型有关。然而,城市结构进一步成为影响生境适宜性的相关生境参数。连通性主要由铁路线和路边等线性结构提供。了解生境适宜性和连通性对于有效保护元种群和制定强有力的保护策略至关重要。我们的研究展示了如何将遥感数据与公民科学贡献相结合,有效地应用于栖息地建模,特别是在大的地理区域。与之前的假设相反,外围种群,如沙蜥分布的西北边界,可能更加专业化,我们的研究结果表明,这些蜥蜴对一系列环境条件表现出相当大的适应性,包括人类改变的景观。这种适应性挑战了传统观点,并强调了在保护规划中考虑人为环境的重要性。通过将新的生态系统和城市纳入物种保护规划,我们的研究有助于建立一个更具包容性和有效性的生物多样性保护框架。
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来源期刊
Journal of Biogeography
Journal of Biogeography 环境科学-生态学
CiteScore
7.70
自引率
5.10%
发文量
203
审稿时长
2.2 months
期刊介绍: Papers dealing with all aspects of spatial, ecological and historical biogeography are considered for publication in Journal of Biogeography. The mission of the journal is to contribute to the growth and societal relevance of the discipline of biogeography through its role in the dissemination of biogeographical research.
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