Same species, same habitat preferences? The distribution of aquatic plants is not explained by the same predictors in lakes and streams. (2nd January 2020)

• Record Type: Journal Article
• Authors: Gillard, Morgane B.; Aroviita, Jukka; Alahuhta, Janne
• Is Part Of: Freshwater biology. Volume 65:Number 5(2020)
• Page Start: 878
• Page End: 892
• Publication Date: 2020-01-02
• Subjects: boreal water bodies -- freshwater ecosystems -- macrophytes -- rivers -- species distribution models; Freshwater biology -- Periodicals; Biologie d'eau douce -- Périodiques; 577.605
• DOI: 10.1111/fwb.13470
• Languages: English
• ISSNs: 0046-5070

Abstract

Abstract: Studying the geographical distribution of species can reveal conditions and processes that may drive species presence and abundance. Organism distribution has frequently been explained by climate, but the relative role of local environmental predictors is not fully understood. Moreover, in the freshwater realm, intrinsic differences existing between different categories of water bodies can lead to significant differences in species–environment relationships. Here, we tested the relative importance of broad‐scale climate and local environmental predictors in explaining plant species distributions in freshwater lakes and streams. We built species distribution models to investigate which predictors best explain aquatic plant distribution in two categories of water bodies. We used species inventories and records of three climate and eight local environmental predictors for 150 lakes and 150 streams in Finland. We found that sets of predictors that explain the distribution of macrophyte species are unique depending on if species are in a lake or a stream. Overall, air temperature and ecosystem size were essential to predict aquatic plant species presence in both water body categories. Broad‐scale climate predictors were always very important in explaining species distribution, while local environmental conditions such as water chemistry were of variable influence, depending on species and water body category. These results are probably due to high spatial and temporal variability and range of water physico‐chemical parameters, especially in streams. Nonetheless, despite a lower relative importance than climatic factors, local environmental predictors also strongly affected species distributions. Our findings highlight that incorporating local environmental conditions to species distribution models in addition to climate predictors is necessary to improve predictions, particularly for distribution of stream flora. Considering the species‐specific responses of aquatic plants to their environment, studying species individually with species distribution models represents a useful analysis.