Human pressures modulate climate-warming-induced changes in size spectra of stream fish communities.

Climate warming can negatively affect the body size of ectothermic organisms and, based on known temperature-size rules, tends to benefit small-bodied organisms. Our understanding of the interactive effects of climate warming and other environmental factors on the temporal changes of body size structure is limited. We quantified the annual trends in size spectra of 583 stream fish communities sampled for more than 20 years across France. The results show that climate warming steepened the slope of the community size spectrum in streams with limited impacts from other human pressures. These changes were caused by increasing abundance of small-bodied individuals and decreasing abundance of large-bodied individuals. However, opposite effects of climate warming on the size spectrum slopes were observed in streams facing high levels of other human pressures. This demonstrates that the effects of temperature on body size structure can depend on other human pressures, disrupting the natural patterns of size spectra in wild communities with potentially strong implications for the fluxes of energy and nutrients in ecosystems.

Maximum entropy models reveal spatial variation of metabolic scaling in stream fish communities.

Metabolic scaling provides valuable information about the physiological and ecological functions of organisms, although few studies have quantified the metabolic scaling exponent (b) of communities under natural conditions. Maximum entropy theory of ecology (METE) is a constraint-based unified theory with the potential to empirically assess the spatial variation of the metabolic scaling. Our main goal is to develop a novel method of estimating b within a community by integrating metabolic scaling and METE. We also aim to study the relationships between the estimated b and environmental variables across communities. We developed a new METE framework to estimate b in 118 stream fish communities in the north-eastern Iberian Peninsula. We first extended the original maximum entropy model by parameterizing b in the model prediction of the community-level individual size distributions and compared our results with empirical and theoretical predictions. We then tested the effects of abiotic conditions, species composition and human disturbance on the spatial variation of community-level b. We found that community-level b of the best maximum entropy models showed great spatial variability, ranging from 0.25 to 2.38. The mean exponent (b = 0.93) resembled the community-aggregated mean values from three previous metabolic scaling meta-analyses, all of which were greater than the theoretical predictions of 0.67 and 0.75. Furthermore, the generalized additive model showed that b reached maximum at the intermediate mean annual precipitation level and declined significantly as human disturbance intensified. The parameterized METE is proposed here as a novel framework for estimating the metabolic pace of life of stream fish communities. The large spatial variation of b may reflect the combined effects of environmental constraints and species interactions, which likely have important feedback on the structure and function of natural communities. Our newly developed framework can also be applied to study the impact of global environmental pressures on metabolic scaling and energy use in other ecosystems.

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates.

Body size is an important functional trait that can be used as a bioindicator to assess the impacts of perturbations in natural communities. Community size structure responds to biotic and abiotic gradients, including anthropogenic perturbations across taxa and ecosystems. However, the manual measurement of small-bodied organisms such as benthic macroinvertebrates (e.g., >500 µm to a few centimeters long) is time-consuming. To expedite the estimation of community size structure, here, we developed a protocol to semi-automatically measure the individual body size of preserved river macroinvertebrates, which are one of the most commonly used bioindicators for assessing the ecological status of freshwater ecosystems. This protocol is adapted from an existing methodology developed to scan marine mesozooplankton with a scanning system designed for water samples. The protocol consists of three main steps: (1) scanning subsamples (fine and coarse sample size fractions) of river macroinvertebrates and processing the digitized images to individualize each detected object in each image; (2) creating, evaluating, and validating a learning set through artificial intelligence to semi-automatically separate the individual images of macroinvertebrates from detritus and artifacts in the scanned samples; and (3) depicting the size structure of the macroinvertebrate communities. In addition to the protocol, this work includes the calibration results and enumerates several challenges and recommendations to adapt the procedure to macroinvertebrate samples and to consider for further improvements. Overall, the results support the use of the presented scanning system for the automatic body size measurement of river macroinvertebrates and suggest that the depiction of their size spectrum is a valuable tool for the rapid bioassessment of freshwater ecosystems.

Promoting lab culture to enhance academic resilience during crises.

The COVID-19 pandemic has heavily impacted academics' professional and personal lives, forcing many research groups (labs) to shift from an academic system primarily based on in-person work to an almost full-time remote workforce during lockdowns. Labs are generally characterized by a strong lab culture that underpins all research and social activities of its members. Lab culture traditionally builds on the pillars of in-person communication, knowledge sharing, and all social and professional activities that promote collaboration, team building, scientific productivity, and well-being. Here, we use the experience of our research group facing the COVID-19 pandemic to illustrate how proactively reinforcing lab culture and its positive outcomes have been essential to our lab when transitioning from an in-person to a remote lab environment, and through its ongoing evolution toward a hybrid remote/in-person model. We argue that the proactive promotion of lab culture in research groups can foster academic resilience during crises, helping research groups to maintain their capacity to conduct scientific activities while preserving a sustainable life/work balance and a healthy mental condition.

Individual body mass and length dataset for over 12,000 fish from Iberian streams.

We provide a unique fish individual body size dataset collected from our own sampling and public sources in north-eastern Spain. The dataset includes individual body size measures (fork length and mass) of 12,288 individuals of 24 fish species within 10 families collected at 118 locations in large rivers and small streams. Fish were caught by one-pass electrofishing following European standard protocols. The fish dataset has information on the local instream conditions including climatic variables (i.e., temperature and precipitation), topography (i.e., altitude), nutrient concentration (i.e., total phosphorus and nitrates), and the IMPRESS values (a measure of cumulative human impacts in lotic ecosystems). The potential uses of this new fish dataset are manifold, including developing size-based indices to further estimate the ecological status of freshwater ecosystems, allometric models, and analysis of variation in body size structure along environmental gradients.

Species compositions mediate biomass conservation: The case of lake fish communities.

Environmental and geographical factors are known to influence the number, distribution, and combination of species that coexist within ecological communities. This, in turn, should influence ecosystem functions such as biomass conservation, or the ability of a community to sustain biomass from small to large organisms. We tested this hypothesis by assessing the role of environmental factors in determining how biomass is conserved in over 600 limnetic fish communities spread across a broad geographic gradient in Canada. Comprehensive and accurate information on water conditions and community characteristics such as taxonomy, abundance, biomass, and size distributions were used in our assessment. Results showed that species combinations emerge as one of the main predictors of biomass conservation among the effects of individual species and abiotic factors. Our study highlights the strong role that geographic patterns in the distribution of species can play in shaping key ecosystem functions, with consequences for ecosystem services such as the provision of harvestable fish biomass.

Environmental filtering determines metacommunity structure in wetland microcrustaceans.

Metacommunity approaches are becoming popular when analyzing factors driving species distribution at the regional scale. However, until the popularization of the variation partitioning technique it was difficult to assess the main drivers of the observed patterns (spatial or environmental). Here we propose a new framework linking the emergence of different metacommunity structures (e.g., nested, Gleasonian, Clementsian) to spatial and environmental filters. This is a novel approach that provides a more profound analysis of how both drivers could lead to similar metacommunity structures. We tested this framework on 110 sites covering a strong environmental gradient (i.e., microcrustacean assemblages organized along a salinity gradient, from freshwater to brackish water wetlands). First we identified the metacommunity structure that better fitted these microcrustacean assemblages. Then, we used hierarchical variation partitioning to quantify the relative influences of environmental filters and the distance among wetlands on the identified structure. Our results showed that under strong environmental filtering metacommunity structures were non-random. We also noted that even passive dispersers, that are supposed to be poorly spatially filtered, showed spatial signals at a large geographical scale. However, some difficulties arose when inferring biotic interactions at finer-scale spatial signals. Overall, our study shows the potential of elements of metacommunity structure combined with variation partition techniques to detect environmental drivers and broadscale patterns of metacommunity structure, and that some caution is needed when interpreting finer-scale spatial signals.