• Energy Research

Loss in intraspecific diversity can alter ecosystem functions, but the underlying mechanisms are still elusive, and intraspecific biodiversity–ecosystem function (iBEF) relationships have been restrained to primary producers. Here, we manipulated genetic and functional richness of a fish consumer (Phoxinus phoxinus) to test whether iBEF relationships exist in consumer species and whether they are more likely sustained by genetic or functional richness. We found that both genotypic and functional richness affected ecosystem functioning, either independently or interactively. Loss in genotypic richness reduced benthic invertebrate diversity consistently across functional richness treatments, whereas it reduced zooplankton diversity only when functional richness was high. Finally, losses in genotypic and functional richness altered functions (decomposition) through trophic cascades. We concluded that iBEF relationships lead to substantial top-down effects on entire food chains. The loss of genotypic richness impacted ecological properties as much as the loss of functional richness, probably because it sustains “cryptic” functional diversity.

Understanding ecosystem responses to global change have long challenged scientists due to notoriously complex properties arising from the interplay between biological and environmental factors. We propose the concept of ecosystem synchrony - that is, similarity in the temporal fluctuations of an ecosystem function between multiple ecosystems - to overcome this challenge. Ecosystem synchrony can manifest due to spatially correlated environmental fluctuations (Moran effect), exchange of energy, nutrients, and organic matter and similarity in biotic characteristics across ecosystems. By taking advantage of long-term surveys, remote sensing and the increased use of high-frequency sensors to assess ecosystem functions, ecosystem synchrony can foster our understanding of the coordinated ecosystem responses at unexplored spatiotemporal scales, identify emerging portfolio effects among ecosystems, and deliver signals of ecosystem perturbations.

AbstractPredicting fish responses to modified flow regimes is becoming central to fisheries management. In this study we present an agent-based model (ABM) to predict the growth and distribution of young-of-the-year (YOY) and one-year-old (1+) Atlantic salmon and brown trout in response to flow change during summer. A field study of a real population during both natural and low flow conditions provided the simulation environment and validation patterns. Virtual fish were realistic both in terms of bioenergetics and feeding. We tested alternative movement rules to replicate observed patterns of body mass, growth rates, stretch distribution and patch occupancy patterns. Notably, there was no calibration of the model. Virtual fish prioritising consumption rates before predator avoidance replicated observed growth and distribution patterns better than a purely maximising consumption rule. Stream conditions of low predation and harsh winters provide ecological justification for the selection of this behaviour during summer months. Overall, the model was able to predict distribution and growth patterns well across both natural and low flow regimes. The model can be used to support management of salmonids by predicting population responses to predicted flow impacts and associated habitat change.

Raw data for the article: Bestion, E, Soriano-Redondo, A, Cucherousset, J, Jacob, S, White, J, Zinger, L, Fourtune, L, Di Gesu, L, Teyssier, A, Cote, J. Altered trophic interactions in warming climates: consequences for predator diet breadth and fitness. Proceedings of the Royal Society: B. 2019. 286:20192227. https://doi.org/10.1098/rspb.2019.2227 This data should be cited as: Bestion, E, Soriano-Redondo, A, Cucherousset, J, Jacob, S, White, J, Zinger, L, Fourtune, L, Di Gesu, L, Teyssier, A, Cote, J (2019). Raw data for: "Altered trophic interactions in warming climates: consequences for predator diet breadth and fitness", Bestion et al 2019 Proceedings B. (Version 1). Zenodo. https://doi.org/10.5281/zenodo.3475402 This data is composed of one dataset with 21 columns and a README file Composition of the Bestion_2019_isotopy_dataset_for_zenodo.csv dataset - Individual: numerical index corresponding to each of the 327 individuals in the dataset - Age: age class, J = juvenile (<1 year old), A = adult (1 and 2+ year old) - Sex: F (female) or M (male) - Climate: Present-day climate or Warm climate - Enclosure: enclosure number (10 enclosures, 5 per climatic treatment) - delta13C_september: stable isotope values for delta13C in september - delta15N_september: stable isotope values for delta15N in september - delta13C_september_corrected: stable isotope values for delta13C in september corrected for the stable isotope value of the three invertebrate prey categories - delta15N_september_corrected: stable isotope values for delta15N in september corrected for the stable isotope value of the three invertebrate prey categories - Prop_predator_eaten: proportion of predatory invertebrates eaten by each individual derived from the corrected stable isotope values - Prop_phytophagous_eaten: proportion of phytophagous invertebrates eaten by each individual derived from the corrected stable isotope values - Prop_detritivorous_eaten: proportion of detritivorous invertebrates eaten by each individual derived from the corrected stable isotope values - Levins_diet_index: levins' dietary index corresponding to lizard diet specialization (with 3 = completely generalist and 1 = completely specialist lizard) - Body_Size_september: lizard body size (snout-vent length in mm) - Body_Mass_september: lizard body mass (in g) - Body_Condition_september: lizard body condition (residuals of body mass by body size) - Microbiota_shannon_index: shannon index representing gut microbial bacteria community diversity - Survival_winter: survival during the winter (1 = survived, 0 = died) - Abundance_predator_enclosure: abundance of predatory invertebrates within the enclosure - Abundance_phytophagous_enclosure: abundance of phytophagous invertebrates within the enclosure - Abundance_detitivorous_enclosure: abundance of detritivorous invertebrates within the enclosure

The development of novel renewable energy technologies, such as floating photovoltaics (FPVs), is expanding, but their environmental consequences remain understudied. FPVs physically alter freshwater ecosystems by limiting light and wind penetration at the lake surface, while providing new substrates for biofilm development, including diatoms. Diatoms are essential to primary production and carbon cycling in aquatic systems, however, the composition of diatom assemblages on FPV structures remains unexplored. This study aimed to characterise the diatom assemblages colonising FPV floaters and compare them with those in the pelagic and benthic compartments of gravel pit lakes. Results showed significantly lower taxonomic richness and diversity on FPV floaters, followed by pelagic assemblages, with the highest values observed in benthic habitats. Community composition also differed significantly between the three compartments. Community composition also differed significantly across all habitats, but its dominance was particularly pronounced on FPV floaters (72%), compared to 54% and 32% in the benthic and pelagic compartments, respectively. As a low-profile, disturbance-tolerant taxon, Achnanthidium may thrive in low-light conditions created by FPV shading. It can also serve as a good water quality indicator, while baseline studies are needed to assess whether its dominance on FPVs reflects positive conditions for gravel pit lakes. By creating novel artificial habitats in the pelagic zone, FPVs can modify the patterns of primary production and pelagic-benthic coupling that remain to be investigated.

Floating Photovoltaic (FPV) deployments are accelerating worldwide and FPV coverage on water surface can strongly influence their ecological impacts. Yet, a global assessment of their characteristics is still lacking. We identified 643 FPV power plants constructed across the globe. We found that FPV power plants currently exist in 28 countries, predominantly concentrated in Asia. FPV coverage was highly variable between lakes, ranging from 0.004% to 89.9% of lake surface area. Overall, FPV coverage averaged 34.2% (± 22 SD, n=494), varying significantly across continents. FPV coverage was significantly driven by lake size and morphological complexity, with smaller lakes and lakes with simplified morphology having higher FPV coverage. The high variability in FPV coverage worldwide suggests a high context-dependency of their ecological impacts that will likely be stronger in small lakes with higher FPV coverage.