Inland navigation and land use interact to impact European freshwater biodiversity.

Inland navigation in Europe is proposed to increase in the coming years, being promoted as a low-carbon form of transport. However, we currently lack knowledge on how this would impact biodiversity at large scales and interact with existing stressors. Here we addressed this knowledge gap by analysing fish and macroinvertebrate community time series across large European rivers comprising 19,592 observations from 4,049 sampling sites spanning the past 32 years. We found ship traffic to be associated with biodiversity declines, that is, loss of fish and macroinvertebrate taxonomic richness, diversity and trait richness. Ship traffic was also associated with increases in taxonomic evenness, which, in concert with richness decreases, was attributed to losses in rare taxa. Ship traffic was especially harmful for benthic taxa and those preferring slow flows. These effects often depended on local land use and riparian degradation. In fish, negative impacts of shipping were highest in urban and agricultural landscapes. Regarding navigation infrastructure, the negative impact of channelization on macroinvertebrates was evident only when riparian degradation was also high. Our results demonstrate the risk of increasing inland navigation on freshwater biodiversity. Integrative waterway management accounting for riparian habitats and landscape characteristics could help to mitigate these impacts.

When Do Traits Tell More Than Species about a Metacommunity? A Synthesis across Ecosystems and Scales.

AbstractLinking species traits with the variation in species assemblages across habitats has often proved useful for developing a more mechanistic understanding of species distributions in metacommunities. However, summarizing the rich tapestry of a species in all of its nuance with a few key ecological traits can also lead to an abstraction that provides less predictability than when using taxonomy alone. As a further complication, taxonomic and functional diversities can be inequitably compared, either by integrating taxonomic-level information into the calculation of how functional aspects of communities vary or by detecting spurious trait-environment relationships. To remedy this, we here synthesize analyses of 80 datasets on different taxa, ecosystems, and spatial scales that include information on abundance or presence/absence of species across sites with variable environmental conditions and the species' traits. By developing analyses that treat functional and taxonomic diversity equitably, we ask when functional diversity helps to explain metacommunity structure. We found that patterns of functional diversity explained metacommunity structure and response to environmental variation in only 25% of the datasets using a multitrait approach but up to 59% using a single-trait approach. Nevertheless, an average of only 19% (interquartile range = 0%-29%) of the traits showed a significant signal across environmental gradients. Species-level traits, as typically collected and analyzed through functional diversity patterns, often do not bring predictive advantages over what the taxonomic information already holds. While our assessment of a limited advantage of using traits to explain variation in species assemblages was largely true across ecosystems, traits played a more useful role in explaining variation when many traits were used and when trait constructs were more related to species' status, life history, and mobility. We propose future research directions to make trait-based approaches and data more helpful for inference in metacommunity ecology.

Accounting for temporal change in multiple biodiversity patterns improves the inference of metacommunity processes.

In metacommunity ecology, a major focus has been on combining observational and analytical approaches to identify the role of critical assembly processes, such as dispersal limitation and environmental filtering, but this work has largely ignored temporal community dynamics. Here, we develop a "virtual ecologist" approach to evaluate assembly processes by simulating metacommunities varying in three main processes: density-independent responses to abiotic conditions, density-dependent biotic interactions, and dispersal. We then calculate a number of commonly used summary statistics of community structure in space and time and use random forests to evaluate their utility for inferring the strength of these three processes. We find that (i) both spatial and temporal data are necessary to disentangle metacommunity processes based on the summary statistics we test, and including statistics that are measured through time increases the explanatory power of random forests by up to 59% compared to cases where only spatial variation is considered; (ii) the three studied processes can be distinguished with different descriptors; and (iii) each summary statistic is differently sensitive to temporal and spatial sampling effort. Including repeated observations of metacommunities over time was essential for inferring the metacommunity processes, particularly dispersal. Some of the most useful statistics include the coefficient of variation of species abundances through time and metrics that incorporate variation in the relative abundances (evenness) of species. We conclude that a combination of methods and summary statistics is probably necessary to understand the processes that underlie metacommunity assembly through space and time, but we recognize that these results will be modified when other processes or summary statistics are used.

Sampling and modelling rare species: Conceptual guidelines for the neglected majority.

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

Biodiversity conservation through the lens of metacommunity ecology.

Metacommunity ecology combines local (e.g., environmental filtering and biotic interactions) and regional (e.g., dispersal and heterogeneity) processes to understand patterns of species abundance, occurrence, composition, and diversity across scales of space and time. As such, it has a great potential to generalize and synthesize our understanding of many ecological problems. Here, we give an overview of how a metacommunity perspective can provide useful insights for conservation biology, which aims to understand and mitigate the effects of anthropogenic drivers that decrease population sizes, increase extinction probabilities, and threaten biodiversity. We review four general metacommunity processes-environmental filtering, biotic interactions, dispersal, and ecological drift-and discuss how key anthropogenic drivers (e.g., habitat loss and fragmentation, and nonnative species) can alter these processes. We next describe how the patterns of interest in metacommunities (abundance, occupancy, and diversity) map onto issues at the heart of conservation biology, and describe cases where conservation biology benefits by taking a scale-explicit metacommunity perspective. We conclude with some ways forward for including metacommunity perspectives into ideas of ecosystem functioning and services, as well as approaches to habitat management, preservation, and restoration.

The worldwide impact of urbanisation on avian functional diversity.

Urbanisation is driving rapid declines in species richness and abundance worldwide, but the general implications for ecosystem function and services remain poorly understood. Here, we integrate global data on bird communities with comprehensive information on traits associated with ecological processes to show that assemblages in highly urbanised environments have substantially different functional composition and 20% less functional diversity on average than surrounding natural habitats. These changes occur without significant decreases in functional dissimilarity between species; instead, they are caused by a decrease in species richness and abundance evenness, leading to declines in functional redundancy. The reconfiguration and decline of native functional diversity in cities are not compensated by the presence of exotic species but are less severe under moderate levels of urbanisation. Thus, urbanisation has substantial negative impacts on functional diversity, potentially resulting in impaired provision of ecosystem services, but these impacts can be reduced by less intensive urbanisation practices.

Author Correction: A global database for metacommunity ecology, integrating species, traits, environment and space.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A global database for metacommunity ecology, integrating species, traits, environment and space.

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; "CESTES". Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.