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Comparison of landscape graph modelling methods for analysing pond network connectivity
Landscape Ecology ( IF 5.2 ) Pub Date : 2020-11-28 , DOI: 10.1007/s10980-020-01164-9
Claire Godet , Céline Clauzel

Landscape fragmentation negatively impacts species populations by isolating them. Assessing landscape connectivity could help to improve biodiversity conservation. Among various methods available to model and analyse connectivity, graph-theoretic approaches are recognized as powerful tools, even if their ecological significance may be questionable in some cases. Indeed, there are many ways to construct a landscape graph and their impacts on the assessment of connectivity are rarely explored. Our aim was to compare three methods of constructing landscape graphs to identify differences and similarities in the resulting network connectivity. The methods can be distinguished according to the type of data used: expert opinions, field data or a combination of the two. The methodological framework was applied to seven pond-dwelling species (Alytes obstetricans, Bufo bufo, Epidalea calamita, Hyla arborea, Natrix natrix, Rana temporaria, Triturus cristatus) in the Ile-de-France region (France). Three common methods were applied to construct landscape graphs: (1) using a land cover map (LM) and expert opinions to define nodes and links; (2) using a habitat suitability model (HSM) and species occurrence data to define nodes and links; and (3) using a HSM to define nodes and a land cover map to define links (HSM_LM). To carry out our study, we produced a land cover map, collected and prepared input data for HSMs, generated HSMs to map the probability of species occurrence and constructed landscape graphs from the three methods. For each of them, several connectivity metrics were calculated and compared. The results revealed large differences in the statistical distribution of connectivity values, even though the spatial location of the main areas of low and high connectivity was roughly the same. In general, the LM method provided lower values of connectivity and smaller areas of high values than the other two, regardless of species. Conversely, the HSM method had the highest connectivity values, while the combined HSM_LM method appeared to be intermediate. Our study was not intended to conclude whether one method is better than another; only to point out that results vary greatly depending on the graph construction method. To evaluate the predictive performance of each model, a validation process should be conducted with another independent biological dataset, which was not available in our study. The high variability of results argues for taking care to ensure that the construction of models is carefully consistent with ecological assumptions and the objective pursued.

中文翻译:

用于分析池塘网络连通性的景观图建模方法比较

景观破碎化通过隔离物种种群对物种种群产生负面影响。评估景观连通性有助于改善生物多样性保护。在可用于建模和分析连通性的各种方法中,图论方法被认为是强大的工具,即使它们的生态意义在某些情况下可能存在问题。事实上,构建景观图的方法有很多,它们对连通性评估的影响很少被探索。我们的目的是比较构建景观图的三种方法,以识别生成的网络连接的差异和相似之处。这些方法可以根据使用的数据类型进行区分:专家意见、现场数据或两者的组合。该方法框架应用于法兰西岛地区(法国)的七种池塘栖息物种(产科动物、蟾蜍、Epidalea calamita、Hyla arborea、Natrix natrix、Rana temporaria、Triturus cristatus)。三种常用方法用于构建景观图:(1)使用土地覆盖图(LM)和专家意见来定义节点和链接;(2) 使用栖息地适宜性模型(HSM)和物种发生数据来定义节点和链接;(3) 使用 HSM 来定义节点和土地覆盖图来定义链接 (HSM_LM)​​。为了开展我们的研究,我们制作了土地覆盖图,收集并准备了 HSM 的输入数据,生成 HSM 以绘制物种出现的概率,并从三种方法构建景观图。对于它们中的每一个,计算和比较了几个连接性指标。结果表明,连通性值的统计分布存在较大差异,尽管低连通性和高连通性的主要区域的空间位置大致相同。一般而言,LM 方法提供的连通性值较低,而高值区域较小,与其他两种方法相比,无论物种如何。相反,HSM 方法具有最高的连通性值,而组合的 HSM_LM 方法似乎处于中间状态。我们的研究并非旨在得出一种方法是否优于另一种方法的结论;只是要指出,结果因图形构建方法的不同而有很大差异。为了评估每个模型的预测性能,应该使用另一个独立的生物数据集进行验证过程,这在我们的研究中是不可用的。
更新日期:2020-11-28
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