Cosentino Francesca, Seamark Ernest Charles James, Van Cakenberghe Victor, Maiorano Luigi
Department of Biology and Biotechnologies "Charles Darwin" Sapienza University of Rome Italy.
AfricanBats NPC Centurion Republic of South Africa.
Ecol Evol. 2023 Mar 20;13(3):e9855. doi: 10.1002/ece3.9855. eCollection 2023 Mar.
Abiotic factors are usually considered key drivers of species distribution at macro scales, while biotic interactions are mostly used at local scales. A few studies have explored the role of biotic interactions at macro scales, but all considered a limited number of species and obligate interactions. We examine the role of biotic interactions in large-scale SDMs by testing two main hypotheses: (1) biotic factors in SDMs can have an important role at continental scale; (2) the inclusion of biotic factors in large-scale SDMs is important also for generalist species. We used a maximum entropy algorithm to model the distribution of 177 bat species in Africa calibrating two SDMs for each species: one considering only abiotic variables (noBIO-SDMs) and the other (BIO-SDMs) including also biotic variables (trophic resource richness). We focused the interpretation of our results on variable importance and response curves. For each species, we also compared the potential distribution measuring the percentage of change between the two models in each pixel of the study area. All models gave AUC >0.7, with values on average higher in BIO-SDMs compared to noBIO-SDMs. Trophic resources showed an importance overall higher level than all abiotic predictors in most of the species (~68%), including generalist species. Response curves were highly interpretable in all models, confirming the ecological reliability of our models. Model comparison between the two models showed a change in potential distribution for more than 80% of the species, particularly in tropical forests and shrublands. Our results highlight the importance of considering biotic interactions in SDMs at macro scales. We demonstrated that a generic biotic proxy can be important for modeling species distribution when species-specific data are not available, but we envision that a multi-scale analysis combined with a better knowledge of the species might provide a better understanding of the role of biotic interactions.
非生物因素通常被认为是宏观尺度上物种分布的关键驱动因素,而生物相互作用大多用于局部尺度。一些研究探讨了生物相互作用在宏观尺度上的作用,但都只考虑了有限数量的物种和专性相互作用。我们通过检验两个主要假设来研究生物相互作用在大规模物种分布模型(SDMs)中的作用:(1)物种分布模型中的生物因素在大陆尺度上可能具有重要作用;(2)在大规模物种分布模型中纳入生物因素对广适性物种也很重要。我们使用最大熵算法对非洲177种蝙蝠的分布进行建模,为每个物种校准两个物种分布模型:一个仅考虑非生物变量(无生物因素物种分布模型),另一个(生物因素物种分布模型)还包括生物变量(营养资源丰富度)。我们将结果的解释重点放在变量重要性和响应曲线上。对于每个物种,我们还比较了潜在分布,测量研究区域每个像素中两个模型之间的变化百分比。所有模型的AUC均>0.7,生物因素物种分布模型的值平均比无生物因素物种分布模型更高。在大多数物种(约68%)中,包括广适性物种,营养资源显示出总体上比所有非生物预测因子更高的重要性水平。所有模型中的响应曲线都具有很高的可解释性,证实了我们模型的生态可靠性。两个模型之间的模型比较显示,超过80%的物种潜在分布发生了变化,特别是在热带森林和灌木丛中。我们的结果强调了在宏观尺度的物种分布模型中考虑生物相互作用的重要性。我们证明,当没有物种特异性数据时,一个通用的生物代理对于建模物种分布可能很重要,但我们设想多尺度分析结合对物种的更好了解可能会更好地理解生物相互作用的作用。