The seafloor is inhabited by a large number of benthic invertebrates, and their importance in mediating carbon mineralization and biogeochemical cycles is recognized. However, the majority of fauna live below the sediment surface, so most means of survey rely on destructive sampling methods that are limited to documenting species presence rather than event driven activity and functionally important aspects of species behaviour. We have developed and tested a laboratory-based three-dimensional acoustic coring system that is capable of non-invasively visualizing the presence and activity of invertebrates within the sediment matrix. Here, we present reconstructed three-dimensional acoustic images of the sediment profile, with strong backscatter revealing the presence and position of individual benthic organisms. These data were used to train a three-dimensional convolutional neural network model and, using a combination of data augmentation and data correction techniques, we were able to identify individual species with an 88% accuracy. Combining three-dimensional acoustic coring with deep learning forms an effective and non-invasive means of providing detailed mechanistic information of in situ species-sediment interactions, opening new opportunities to quantify species-specific contributions to ecosystems.

The invasion of non-native amphipods often leads to severe changes in the composition of aquatic communities and may also result in the local replacement of native species. Particularly, a lower risk of being preyed upon resulting from high swimming velocities can be an advantage in interspecific competition. Furthermore, as swimming velocities are ecologically important, they are often used in ecotoxicological studies to estimate effects of different stressors. However, knowledge on swimming velocities of native and non-native amphipods is still rather limited. We experimentally investigated the maximum swimming velocities of three native and three non-native amphipods via video analyses in the laboratory. Results showed that non-native species reach higher maximum swimming velocities compared to natives probably leading to a higher predation success and reduced risk of being preyed upon. Additionally, body length correlates positively with swimming velocities, except for the invader Dikerogammarus villosus. As D. villosus can be cannibalistic, the high swimming velocities of the small individuals may reduce the intraspecific predation and may increase the survival rates of smaller specimen. Hence, knowledge about the swimming velocities of species contribute to the understanding of interspecific competition among species and might support explanation approaches for the success of invasive species. Furthermore, it provides baselines for ecotoxicological studies of stressor impacts.

Many different factors, such as species traits, socio-economic factors, geographical and environmental factors, can lead to specimen collection preference. This study aims to determine whether grassland specimen collection in China is preferred by species traits (i.e., plant height, flowering and fruiting period), environmental range (i.e., the temperature and precipitation range) and geographical range (i.e., distribution range and altitudinal range). Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables. Random Forest models were then used to find the most parsimonious multivariate model. The results showed that interannual variation in specimen number between 1900 and 2020 was considerable. Specimen number of these species in southeast China was notably lower than that in northwest China. Environmental range and geographical range of species had significant positive correlations with specimen number. In addition, there were relatively weak but significant associations between specimen number and species trait (i.e., plant height and flowering and fruiting period). Random Forest models indicated that distribution range was the most important variable, followed by flowering and fruiting period, and altitudinal range. These findings suggest that future floristic surveys should pay more attention to species with small geographical range, narrow environmental range, short plant height, and short flowering and fruiting period. The correction of specimen collection preference will also make the results of species distribution model, species evolution and other works based on specimen data more accurate.

Patterns of abundance across space and time, and intraspecific variation in body size, are two species attributes known to influence diet breadth and the structure of interaction networks. Yet, the relative influence of these attributes on diet breadth is often assumed to be equal among taxonomic groups, and the relationship between intraspecific variation in body size on interaction patterns is frequently neglected. We observed bee-flower interactions in multiple locations across Montana, USA, for two growing seasons and measured spatial and temporal patterns of abundance, along with interspecific and intraspecific variation in body size for prevalent species. We predicted that the association between spatial and temporal patterns of abundance and intraspecific variation in body size, and diet breadth, would be stronger for bumble bee compared to non-bumble bee species, because species with flexible diets and long activity periods can interact with more food items. Bumble bees had higher local abundance, occurred in many local communities, more intraspecific variation in body size, and longer phenophases compared to non-bumble bee species, but only local abundance and phenophase duration had a stronger positive association with the diet breadth of bumble bee compared to non-bumble bee species. Communities with a higher proportion of bumble bees also had higher intraspecific variation in body size at the network-level, and network-level intraspecific variation in body size was positively correlated with diet generalization. Our findings highlight that the association between species attributes and diet breadth changes depending on the taxonomic group, with implications for the structure of interaction networks.

A strong need exists for broadly applicable nano-QSARs, capable of predicting toxicological outcomes towards untested species and nanomaterials, under different environmental conditions. Existing nano-QSARs are generally limited to only a few species but the inclusion of species characteristics into models can aid in making them applicable to multiple species, even when toxicity data is not available for biological species. Species traits were used to create classification- and regression machine learning models to predict acute toxicity towards aquatic species for metallic nanomaterials. Afterwards, the individual classification- and regression models were stacked into a meta-model to improve performance. Additionally, the uncertainty and limitations of the models were assessed in detail (beyond the OECD principles) and it was investigated whether models would benefit from the addition of more data. Results showed a significant improvement in model performance following model stacking. Investigation of model uncertainties and limitations highlighted the discrepancy between the applicability domain and accuracy of predictions. Data points outside of the assessed chemical space did not have higher likelihoods of generating inadequate predictions or vice versa. It is therefore concluded that the applicability domain does not give complete insight into the uncertainty of predictions and instead the generation of prediction intervals can help in this regard. Furthermore, results indicated that an increase of the dataset size did not improve model performance. This implies that larger dataset sizes may not necessarily improve model performance while in turn also meaning that large datasets are not necessarily required for prediction of acute toxicity with nano-QSARs.

Warming temperatures are altering communities and trophic networks across Earth\'s ecosystems. While the overall influence of warming on food webs is often context-dependent, increasing temperatures are predicted to change communities in two fundamental ways: (1) by reducing average body size and (2) by increasing individual metabolic rates. These warming-induced changes have the potential to influence the distribution of food web fluxes, food web stability, and the relative importance of deterministic and stochastic ecological processes shaping community assembly. Here, we quantified patterns and the relative distribution of organic matter fluxes through stream food webs spanning a broad natural temperature gradient (5-27°C). We then related these patterns to species and community trait distributions of mean body size and population biomass turnover (P:B) within and across streams. We predicted that (1) communities in warmer streams would exhibit smaller body size and higher P:B and (2) organic matter fluxes within warmer communities would increasingly skew toward smaller, higher P:B populations. Across the temperature gradient, warmer communities were characterized by smaller body size (~9% per °C) and higher P:B (~7% faster turnover per °C) populations on average. Additionally, organic matter fluxes within warmer streams were increasingly skewed toward higher P:B populations, demonstrating that warming can restructure organic matter fluxes in both an absolute and relative sense. With warming, the relative distribution of organic matter fluxes was decreasingly likely to arise through the random sorting of species, suggesting stronger selection for traits driving high turnover with increasing temperature. Our study suggests that a warming world will favor energy fluxes through \"smaller and faster\" populations, and that these changes may be more predictable than previously thought.

Insectivorous bats are generalist predators and can flexibly respond to fluctuations in the distribution and abundance of insect prey. To better understand the effects of bats on arthropod pests, the types of pests eaten by bats and the response of bats to insect prey need to be determined. In this study, we performed DNA metabarcoding to examine prey composition and pest diversity in the diets of four insectivorous species of bats (Hipposideros armiger, Taphozous melanopogon, Aselliscus stoliczkanus, and Miniopterus fuliginosus). We evaluated the correlation between bat activity and insect resources and assessed dietary niche similarity and niche breadth among species and factors that influence prey consumption in bats. We found that the diets of these bats included arthropods from 23 orders and 200 families, dominated by Lepidoptera, Coleoptera, and Diptera. The proportion of agricultural pests in the diet of each of the four species of bats exceeded 40% and comprised 713 agricultural pests, including those that caused severe economic losses. Bats responded to the availability of insects. For example, a higher abundance of insects, especially Lepidoptera, and a higher insect diversity led to an increase in the duration of bat activity. In areas with more abundant insects, the number of bat passes also increased. The dietary composition, diversity, and niches differed among species and were particularly significant between H. armiger and T. melanopogon; the dietary niche width was the greatest in A. stoliczkanus and the narrowest in H. armiger. The diet of bats was correlated with their morphological and echolocation traits. Larger bats preyed more on insects in the order Coleoptera, whereas the proportion of bats consuming insects in the order Lepidoptera increased as the body size decreased. Bats that emitted echolocation calls with a high peak frequency and duration preyed more on insects in the order Mantodea. Our results suggest that dietary niche differentiation promotes the coexistence of different bat species and increases the ability of bats to consume insect prey and agricultural pests. Our findings provide greater insights into the role of bats that prey on agricultural pests and highlight the importance of combining bat conservation with integrated pest management.

Climate change is pushing species towards and potentially beyond their critical thermal limits. The extent to which species can cope with temperatures exceeding their critical thermal limits is still uncertain. To better assess species\' responses to warming, we compute the warming tolerance (ΔTniche ) as a thermal vulnerability index, using species\' upper thermal limits (the temperature at the warm limit of their distribution range) minus the local habitat temperature actually experienced at a given location. This metric is useful to predict how much more warming species can tolerate before negative impacts are expected to occur. Here we set up a cross-continental transplant experiment involving five regions distributed along a latitudinal gradient across Europe (43° N-61° N). Transplant sites were located in dense and open forests stands, and at forest edges and in interiors. We estimated the warming tolerance for 12 understory plant species common in European temperate forests. During 3 years, we examined the effects of the warming tolerance of each species across all transplanted locations on local plant performance, in terms of survival, height, ground cover, flowering probabilities and flower number. We found that the warming tolerance (ΔTniche ) of the 12 studied understory species was significantly different across Europe and varied by up to 8°C. In general, ΔTniche were smaller (less positive) towards the forest edge and in open stands. Plant performance (growth and reproduction) increased with increasing ΔTniche across all 12 species. Our study demonstrated that ΔTniche of understory plant species varied with macroclimatic differences among regions across Europe, as well as in response to forest microclimates, albeit to a lesser extent. Our findings support the hypothesis that plant performance across species decreases in terms of growth and reproduction as local temperature conditions reach or exceed the warm limit of the focal species.

While spatial distribution shifts have been documented in many marine fishes under global change, the responses of elasmobranchs have rarely been studied, which may have led to an underestimation of their potential additional threats. Given their irreplaceable role in ecosystems and their high extinction risk, we used a 24-year time series (1997-2020) of scientific bottom trawl surveys to examine the effects of climate change on the spatial distribution of nine elasmobranch species within Northeast Atlantic waters. Using a hierarchical modeling of species communities, belonging to the joint species distribution models, we found that suitable habitats for four species increased on average by a factor of 1.6 and, for six species, shifted north-eastwards and/or to deeper waters over the past two decades. By integrating species traits, we showed changes in habitat suitability led to changes in the elasmobranchs trait composition. Moreover, communities shifted to deeper waters and their mean trophic level decreased. We also note an increase in the mean community size at maturity concurrent with a decrease in fecundity. Because skates and sharks are functionally unique and dangerously vulnerable to both climate change and fishing, we advocate for urgent considerations of species traits in management measures. Their use would make it better to identify species whose loss could have irreversible impacts in face of the myriad of anthropogenic threats.

The first arrival dates of 31 species of migrant birds in the Tatarstan Republic of Russia were monitored for the 34-year period from 1989-2022. Trends in first arrival date were evaluated using regression against the year value. Patterns in arrival data with respect to species traits (habitat, migration distance, body weight, etc.) were evaluated using redundancy analysis. Relationships between first arrival dates and Tatarstan temperatures were also evaluated using regression methods of first-arrival date on monthly mean temperatures. Almost all (28 of 31) species revealed a significantly earlier migration arrival date; however, associations between arrival patterns and species traits were equivocal. Warmer temperatures were significantly associated with earlier arrival in 26 of the 31 species, but the relationship was insufficient to explain the average 11-day advance in species. For these species and in this location only the timing and location of arrival are well recorded; the exact wintering areas and migration routes, and the timing of these phases are less well understood. When these become better known, an investigation of the influence of environmental conditions (including temperature) on departure timing and passage timing and speed is recommended.