A bird in the hand: Global-scale morphological trait datasets open new frontiers of ecology, evolution and ecosystem science

Functional diversity dynamics of waterbird communities driven by water levels at Shengjin Lake, a small river-connected shallow lake in the middle and lower Yangtze River floodplain

Gate-controlled activities in lakes can directly or indirectly influence the assembly of waterbird communities. Shengjin Lake, a Ramsar site, is a typical river-connected and gate-controlled shallow lake in the lower and middle Yangtze River floodplain in China, comprising three sub-lakes (upper, middle, and lower) based on topographical features. We surveyed wintering waterbirds at Shengjin Lake from October 2022 to March 2023. We divided the winter water level period into nine phases based on the characteristics of water level changes. By measuring functional diversity, we aimed to provide insights into the differences in waterbird communities among the three sub-lakes under different water level conditions. Multiple linear regression was used to analyze the relationship between habitat factors and functional diversity. We further explored the relationship between specific functional traits and habitat factors through a combination of the R-mode linked to the Q-mode and the trait-environment correlation matrix (fourth-corner analyses) to explain the mechanism underlying waterbird community assembly. When the water level fluctuated in the range of 10.43-10.74 m (Huanghai elevation), the three sub-lakes had significant habitat differences and high habitat heterogeneity, increasing functional richness and functional dispersion of the upper and lower lakes, both of which significantly differed from those of the middle lake. Habitat heterogeneity and mudflat habitats have positive effects on functional diversity. The difference in functional diversity was primarily determined based on the foraging traits and strata of waterbirds. Habitat filtering of particular traits is a major driving force underlying the assembly of waterbird communities. Overall, we suggest that the minimum water level in the wintering period at Shengjin Lake should be regulated between 10.43 and 10.74 m. These findings provide reasonable suggestions for water level regulation and a theoretical basis for conserving waterbird diversity at Shengjin Lake.

Assessing the predictive value of morphological traits on primary lifestyle of birds through the extreme gradient boosting algorithm

The relationship between morphological traits and ecological performance in birds is an important area of research, as it can help us to understand how birds are able to adapt and how they are affected by changes in their environment. Many studies have investigated the relationship between morphological traits and certain aspects of the performance and ecological niche of these animals. However, the relationship between morphological traits and the primary lifestyle of birds has not previously been explored. This paper aims to evaluate the predictive potential of morphological data to determine the primary lifestyle of birds through a tree-based machine learning algorithm. By doing this, it is also possible to evaluate these artificial categories that we used to split up birds and know whether they are suitable for dividing them in function of shared morphological characteristics or need a redefinition under more discriminant criteria. Supplementary dataset 1 of the AVONET project was used, which comprises the 11 morphological predictors used in this work and the classification according to the primary lifestyle for more than 95% of the existing bird species. For all morphological traits used, statistically significant univariate differences were found between primary lifestyles. The three fitted machine learning models showed high accuracy, in all cases above 78% and superior to the ones achieved through traditional approaches used as contrasts. The results obtained provide evidence that primary lifestyle can be predicted in birds based on morphological traits, as well as more insights about the relevance of functional traits for ecological modeling. This is another step forward in our mechanistic understanding of bird ecology, while exploring how birds have adapted to their environments and how they interact with their surroundings.

High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles

Climate, topography and the 3D structure of forests are major drivers affecting local species communities. However, little is known about how the specific functional traits of saproxylic (wood-living) beetles, involved in the recycling of wood, might be affected by those environmental characteristics.Here, we combine ecological and morphological traits available for saproxylic beetles and airborne laser scanning (ALS) data in Bayesian trait-based joint species distribution models to study how traits drive the distributions of more than 230 species in temperate forests of Europe.We found that elevation (as a proxy for temperature and precipitation) and the proportion of conifers played important roles in species occurrences while variables related to habitat heterogeneity and forest complexity were less relevant. Furthermore, we showed that local communities were shaped by environmental variation primarily through their ecological traits whereas morphological traits were involved only marginally. As predicted, ecological traits influenced species' responses to forest structure, and to other environmental variation, with canopy niche, wood decay niche and host preference as the most important ecological traits. Conversely, no links between morphological traits and environmental characteristics were observed. Both models, however, revealed strong phylogenetic signal in species' response to environmental characteristics.These findings imply that alterations of climate and tree species composition have the potential to alter saproxylic beetle communities in temperate forests. Additionally, ecological traits help explain species' responses to environmental characteristics and thus should prove useful in predicting their responses to future change. It remains challenging, however, to link simple morphological traits to species' complex ecological niches. Read the free Plain Language Summary for this article on the Journal blog.