Disentangling tropicalization and deborealization in marine ecosystems under climate change.

As climate change accelerates, species are shifting poleward and subtropical and tropical species are colonizing temperate environments.1-3 A popular approach for characterizing such responses is the community temperature index (CTI), which tracks the mean thermal affinity of a community. Studies in marine,4 freshwater,5 and terrestrial6 ecosystems have documented increasing CTI under global warming. However, most studies have only linked increasing CTI to increases in warm-affinity species. Here, using long-term monitoring of marine fishes across the Northern Hemisphere, we decomposed CTI changes into four underlying processes-tropicalization (increasing warm-affinity), deborealization (decreasing cold-affinity), borealization (increasing cold-affinity), and detropicalization (decreasing warm-affinity)-for which we examined spatial variability and drivers. CTI closely tracked changes in sea surface temperature, increasing in 72% of locations. However, 31% of these increases were primarily due to decreases in cold-affinity species, i.e., deborealization. Thus, increases in warm-affinity species were prevalent, but not ubiquitous. Tropicalization was stronger in areas that were initially warmer, experienced greater warming, or were deeper, while deborealization was stronger in areas that were closer to human population centers or that had higher community thermal diversity. When CTI (and temperature) increased, species that decreased were more likely to be living closer to their upper thermal limits or to be commercially fished. Additionally, warm-affinity species that increased had smaller body sizes than those that decreased. Our results show that CTI changes arise from a variety of underlying community responses that are linked to environmental conditions, human impacts, community structure, and species characteristics.

Sharks surf the slope: Current updrafts reduce energy expenditure for aggregating marine predators.

An animal's energy landscape considers the power requirements associated with residing in or moving through habitats. Within marine environments, these landscapes can be dynamic as water currents will influence animal power requirements and can change rapidly over diel and tidal cycles. In channels and along slopes with strong currents, updraft zones may reduce energy expenditure of negatively buoyant fishes that are also obligate swimmers. Despite marine predators often residing within high-current area, no study has investigated the potential role of the energetic landscape in driving such habitat selectivity. Over 500 grey reef sharks Carcharhinus amblyrhynchos reside in the southern channel of Fakarava Atoll, French Polynesia. We used diver observations, acoustic telemetry and biologging to show that sharks use regions of predicted updrafts and switch their core area of space use based on tidal state (incoming versus outgoing). During incoming tides, sharks form tight groups and display shuttling behaviour (moving to the front of the group and letting the current move them to the back) to maintain themselves in these potential updraft zones. During outgoing tides, group dispersion increases, swimming depths decrease and shuttling behaviours cease. These changes are likely due to shifts in the nature and location of the updraft zones, as well as turbulence during outgoing tides. Using a biomechanical model, we estimate that routine metabolic rates for sharks may be reduced by 10%-15% when in updraft zones. Grey reef sharks save energy using predicted updraft zones in channels and 'surfing the slope'. Analogous to birds using wind-driven updraft zones, negatively buoyant marine animals may use current-induced updraft zones to reduce energy expenditure. Updrafts should be incorporated into dynamic energy landscapes and may partially explain the distribution, behaviour and potentially abundance of marine predators.

Are we ready to track climate-driven shifts in marine species across international boundaries? - A global survey of scientific bottom trawl data.

Marine biota are redistributing at a rapid pace in response to climate change and shifting seascapes. While changes in fish populations and community structure threaten the sustainability of fisheries, our capacity to adapt by tracking and projecting marine species remains a challenge due to data discontinuities in biological observations, lack of data availability, and mismatch between data and real species distributions. To assess the extent of this challenge, we review the global status and accessibility of ongoing scientific bottom trawl surveys. In total, we gathered metadata for 283,925 samples from 95 surveys conducted regularly from 2001 to 2019. We identified that 59% of the metadata collected are not publicly available, highlighting that the availability of data is the most important challenge to assess species redistributions under global climate change. Given that the primary purpose of surveys is to provide independent data to inform stock assessment of commercially important populations, we further highlight that single surveys do not cover the full range of the main commercial demersal fish species. An average of 18 surveys is needed to cover at least 50% of species ranges, demonstrating the importance of combining multiple surveys to evaluate species range shifts. We assess the potential for combining surveys to track transboundary species redistributions and show that differences in sampling schemes and inconsistency in sampling can be overcome with spatio-temporal modeling to follow species density redistributions. In light of our global assessment, we establish a framework for improving the management and conservation of transboundary and migrating marine demersal species. We provide directions to improve data availability and encourage countries to share survey data, to assess species vulnerabilities, and to support management adaptation in a time of climate-driven ocean changes.

Species better track climate warming in the oceans than on land.

There is mounting evidence of species redistribution as climate warms. Yet, our knowledge of the coupling between species range shifts and isotherm shifts remains limited. Here, we introduce BioShifts-a global geo-database of 30,534 range shifts. Despite a spatial imbalance towards the most developed regions of the Northern Hemisphere and a taxonomic bias towards the most charismatic animals and plants of the planet, data show that marine species are better at tracking isotherm shifts, and move towards the pole six times faster than terrestrial species. More specifically, we find that marine species closely track shifting isotherms in warm and relatively undisturbed waters (for example, the Central Pacific Basin) or in cold waters subject to high human pressures (for example, the North Sea). On land, human activities impede the capacity of terrestrial species to track isotherm shifts in latitude, with some species shifting in the opposite direction to isotherms. Along elevational gradients, species follow the direction of isotherm shifts but at a pace that is much slower than expected, especially in areas with warm climates. Our results suggest that terrestrial species are lagging behind shifting isotherms more than marine species, which is probably related to the interplay between the wider thermal safety margin of terrestrial versus marine species and the more constrained physical environment for dispersal in terrestrial versus marine habitats.

Global trait-environment relationships of plant communities.

Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

A landscape genetic analysis of important agricultural pest species in Tunisia: The whitefly Bemisia tabaci.

Combining landscape ecology and genetics provides an excellent framework to appreciate pest population dynamics and dispersal. The genetic architectures of many species are always shaped by environmental constraints. Because little is known about the ecological and genetic traits of Tunisian whitefly populations, the main objective of this work is to highlight patterns of biodiversity, genetic structure and migration routes of this pest. We used nuclear microsatellite loci to analyze B. tabaci populations collected from various agricultural areas across the country and we determine their biotype status. Molecular data were subsequently interpreted in an ecological context supplied from a species distribution model to infer habitat suitability and hereafter the potential connection paths between sampling localities. An analysis of landscape resistance to B. tabaci genetic flow was thus applied to take into account habitat suitability, genetic relatedness and functional connectivity of habitats within a varied landscape matrix. We shed light on the occurrence of three geographically delineated genetic groups with high levels of genetic differentiation within each of them. Potential migration corridors of this pest were then established providing significant advances toward the understanding of genetic features and the dynamic dispersal of this pest. This study supports the hypothesis of a long-distance dispersal of B. tabaci followed by infrequent long-term isolations. The Inference of population sources and colonization routes is critical for the design and implementation of accurate management strategies against this pest.

Invasion by the Alien Tree Prunus serotina Alters Ecosystem Functions in a Temperate Deciduous Forest.

Alien invasive species can affect large areas, often with wide-ranging impacts on ecosystem structure, function, and services. Prunus serotina is a widespread invader of European temperate forests, where it tends to form homogeneous stands and limits recruitment of indigenous trees. We hypotesized that invasion by P. serotina would be reflected in the nutrient contents of the native species' leaves and in the respiration of invaded plots as efficient resource uptake and changes in nutrient cycling by P. serotina probably underly its aggressive invasiveness. We combined data from 48 field plots in the forest of Compiègne, France, and data from an experiment using 96 microcosms derived from those field plots. We used general linear models to separate effects of invasion by P. serotina on heterotrophic soil and litter respiration rates and on canopy foliar nutrient content from effects of soil chemical properties, litter quantity, litter species composition, and tree species composition. In invaded stands, average respiration rates were 5.6% higher for soil (without litter) and 32% higher for soil and litter combined. Compared to indigenous tree species, P. serotina exhibited higher foliar N (+24.0%), foliar P (+50.7%), and lower foliar C:N (-22.4%) and N:P (-10.1%) ratios. P. serotina affected foliar nutrient contents of co-occuring indigenous tree species leading to decreased foliar N (-8.7 %) and increased C:N ratio (+9.5%) in Fagus sylvatica, decreased foliar N:P ratio in Carpinus betulus (-13.5%) and F. sylvatica (-11.8%), and increased foliar P in Pinus sylvestris (+12.3%) in invaded vs. uninvaded stands. Our results suggest that P. serotina is changing nitrogen, phosphorus, and carbon cycles to its own advantage, hereby increasing carbon turnover via labile litter, affecting the relative nutrient contents in the overstory leaves, and potentially altering the photosynthetic capacity of the long-lived indigenous broadleaved species. Uncontrolled invasion of European temperate forests by P. serotina may affect the climate change mitigation potential of these forests in the long term, through additive effects on local nutrient cycles.

Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering.

Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the spatial patterns of beta diversity for commercially exploited, demersal marine species assemblages along the Tunisian coasts. For this study, we used a presence/absence dataset which included information on 174 species (invertebrates and fishes) and 9 environmental variables. We first performed the modeling analyses and assessed beta diversity using the turnover component of the Jaccard's dissimilarity index. We then performed nonmetric multidimensional scaling to map predicted beta diversity. To delineate the biogeographical regions, we used fuzzy cluster analysis. Finally, we also identified a set of indicator species which characterized the species assemblages in each identified biogeographical region. The predicted beta diversity map revealed two patterns: an inshore-offshore gradient and a south-north latitudinal gradient. Three biogeographical regions were identified and 14 indicator species. These results constitute a first contribution of the bioregionalisation of the Tunisian waters and highlight the issues associated with current fisheries management zones and conservation strategies. Results could be useful to follow an Ecosystem Based Management approach by proposing an objective spatial partitioning of the Tunisian waters. This partitioning could be used to prioritize the adjustment of the actual fisheries management entities, identify current data gaps, inform future scientific surveys and improve current MPA network.

The use of a predictive habitat model and a fuzzy logic approach for marine management and planning.

Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as 'high'. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study.