This study uses dual-labelled (13C and 15N) stable isotope applications to examine uptake and short-term processing of carbon (C) and nitrogen (N) by microbial communities in intertidal sediment from three subtropical estuarine sites. We examine differences in microbial uptake and retention that arise due to domination of microbial processing by either microphytobenthos or heterotrophic bacteria. We compare amino acids and algal dissolved organic matter (Algal DOM) and glucose and NH4+ versus newly fixed microphytobenthos C (MPB-C) and NH4+ using in situ applications across 24 h to identify uptake into the microbial community and sediment OM. Algal DOM had preferential C uptake and more retention across 24 h indicating precursors incorporated into biosynthetic pathways for biomass. Conversely, amino acid C was not incorporated or rapidly respired to DIC but displayed clear preferential uptake and retention of 15N. Short-term (24 h) retention of glucose was higher than MPB-C, while uptake of 15N from NH4+ was similar between treatments, potentially indicating glucose-stimulated export of 15N via coupled nitrification-dentrification. Despite careful selection of similar sites and sediment types, we found substantial variability between replicates and sites in the uptake and processing of labeled substrate that challenged traditional statistical analysis due to non-homogenous variance. Uptake variability across orders of magnitude is likely due to disproportionate processing of substrates occurring in hotspots of microbial processing within sediment. Development of analytical techniques to provide robust strategies to handle variability caused by abiotic and biotic factors will allow greater clarity surrounding in situ biogeochemical processing in intertidal environments. less

The effects of climate change are now more pervasive than ever. Marine ecosystems have been particularly impacted by climate change, with Marine Heat Waves (MHWs) being a strong driver of mass mortality events. Even in the most optimistic greenhouse gas emission scenarios, MHWs will continue to increase in frequency, intensity, and duration. For this reason, understanding the resilience of marine species to the increase of MHWs is crucial to predicting their viability under future climatic conditions. In this study, we explored the consequences of Marine Heatwaves (MHWs) on the resilience of a Mediterranean key octocoral species, Paramuricea clavata, to further disturbances to their population structure. To quantify P. clavata\'s capacity to resist and recover from future disturbances, we used demographic information collected from 1999 to 2022, from two different sites in the NW Mediterranean Sea. Our results showed that the differences in the dynamics of populations exposed and those not exposed to MHWs were driven mostly by differences in mean survivorship and growth. We also showed that after MHWs P. clavata populations had slower rates of recovery but did not experience changes in resistance. Populations exposed to MHWs had lower resistance elasticity to progression but higher stasis compared to unexposed populations. In contrast, the only demographic process showing some differences when comparing the speed of recovery elasticity values between populations exposed and unexposed to MHWs was stasis. Finally, under scenarios of increasing frequency of MHWs, the extinction of P. clavata populations will accelerate and their capacity to recover after further disturbances will be hampered. Overall, these findings confirm that future climatic conditions will make octocoral populations even more vulnerable to further disturbances. These results highlight the importance of limiting local impacts on marine ecosystems to dampen the consequences of climate change. less

Increasing interest in seabed resource use in the ocean is introducing new pressures on deep-sea environments, the ecological impacts of which need to be evaluated carefully. The complexity of these ecosystems and the dearth of comprehensive data pose significant challenges to predicting potential impacts. In this study, we demonstrate the use of Bayesian Networks (BNs) as a modelling framework to address these challenges and enhance the development of robust quantitative predictions concerning the effects of human activities on deep-seafloor ecosystems. The approach consists of iterative model building with experts, and quantitative probability estimates of the relative decrease in abundance of different functional groups of benthos following seabed mining. The model is then used to evaluate two alternative seabed mining scenarios to identify the major sources of uncertainty associated with the mining impacts. By establishing causal connections between the pressures associated with potential mining activities and various components of the benthic ecosystem, our model offers an improved comprehension of potential impacts on the seafloor environment. We illustrate this approach using the example of potential phosphorite nodule mining on the Chatham Rise, offshore Aotearoa/New Zealand, SW Pacific Ocean, and examine ways to incorporate knowledge from both empirical data and expert assessments into quantitative risk assessments. We further discuss how ecological risk assessments can be constructed to better inform decision-making, using metrics relevant to both ecology and policy. The findings from this study highlight the valuable insights that BNs can provide in evaluating the potential impacts of human activities. However, continued research and data collection are crucial for refining and ground truthing these models and improving our understanding of the long-term consequences of deep-sea mining and other anthropogenic activities on marine ecosystems. By leveraging such tools, policymakers, researchers, and stakeholders can work together towards human activities in the deep sea that minimise ecological harm and ensure the conservation of these environments. less

There are two complementary approaches to thermodynamics: an empirical, phenomenological representation of macroscopic states and a model-based, statistical-mechanical representation of microscopic states. If only a few energy transformation steps are involved, macroscopic quantities such as energy and entropy can be estimated without ambiguity, and often the associated microscopic states are well characterised. Both approaches have been used to develop and guide many key early ecological ideas. However, most ecosystems are characterized by uncountably many transformations that operate on a wide range of space and time scales. This renders the bounds of such systems become ambiguous making both the macroscopic and microscopic approaches a challenge. As such, the implementation of both approaches remain areas ripe for further investigation. In particular, the Onsager reciprocal relations permit simplification of expectations that are yet to be fully understood in an ecological context. Here we begin on taking a few first steps in trying understand the far-reaching ramifications of these thermodynamic relations. less

Accurate biological models are critical to reliably predict vulnerability of marine organisms and ecosystems to rapid environmental changes. Current predictions on the biological impacts of climate change and human-caused disturbances primarily stem from controlled experiments but lack assessments of the mechanisms underlying biotic variations in natural systems. Such information is key to translating experimental models to natural populations, especially for habitat-forming, climate sensitive species with key ecological roles. This study aimed to characterize and quantify spatial patterns of shell biomineralization and biomechanical properties in a key reef-building oyster, Crassostrea virginica, collected from restored reefs along natural estuarine gradients in the Hudson River Estuary (NY, U.S.). We characterized patterns of oyster shell production (i.e., shape and thickness), structure (i.e., abundance of foliated and chalky calcite), mineralogy (i.e., crystal size and density), composition (i.e., organic matrix and Mg/Ca ratios), and mechanical performance (i.e., elastic modulus and hardness) at the macro and micro scale. Our results demonstrate a strong protective capacity of C. virginica for compensatory adjustments in shell biomineralization and biomechanics to maintain shell production and protective functions as a response to biotic and abiotic stressors. We reveal salinity as a key predictor of oyster shell structure, mechanical integrity, and resistance to dissolution, and describe the functional role of chalky calcite in shaping shell mechanical performance. Compensatory adjustments along salinity gradients indicate that oysters produce shells with i) high mechanical resistance but increased vulnerability to dissolution under marine conditions, and ii) lower structural integrity but higher protection from dissolution under brackish conditions. Our work illustrates that biomineralization and biomechanical adjustments may act as compensatory mechanisms in eastern oysters to maintain overall performance under heterogeneous estuarine environments, and could represent a cornerstone for calcifying organisms to acclimate and maintain their ecological functions in a rapidly changing climate. less

Coevolution can occur as a result of species interactions. However, it remains poorly understood how coevolution shapes the accumulation of species richness over macroevolutionary timescales. Assuming speciation occurs in a metacommunity as a result of genetic differentiation across communities due to dispersal limitation, we examine the effects of coevolution-induced stabilizing and destabilizing selection of a single quantitative trait on species diversification. We propose and test two hypotheses. (1) Stabilizing selection within communities enhances species diversification through strengthened dispersal limitation. (2) Destabilizing selection within communities impedes species diversification through weakened dispersal limitation. Here, we simulate clade co-diversification using an individual-based model, considering scenarios where phenotypic evolution is shaped by neutral dynamics, mutualistic coevolution, or antagonistic coevolution, where coevolution operates through trait matching or trait difference, and where the strength of coevolutionary selection is symmetrical or asymmetrical. Our assumption that interactions occur between an independent party (whose individuals can establish or persist in a community independently, e.g. hosts) and a dependent party (whose individuals cannot establish or persist in a community without the independent party, e.g. parasites or obligate mutualists) yields two contrasting results. Stabilizing selection within communities enhances species diversification in the dependent clade but not in the independent clade. Conversely, destabilizing selection within communities impedes species diversification in the independent clade but not in the dependent clade. These results are partially corroborated by empirical dispersal data, suggesting that these mechanisms might explain the diversification of some of the most species-rich clades in the Tree of Life. less

The outcomes of species introductions depend on both propagule size and resource competition, but the effects of these factors are inconsistent across community contexts. Here, we investigate how propagule size and resource competition interact to shape colonization during community coalescence by mixing pairs of in vitro gut microbial communities at ratios that vary over seven orders of magnitude. Each resulting co-culture contained species whose relative abundance depended on inoculation dose, causing the composition of some co-cultures to vary substantially across mixture ratios, even after >30 generations of growth. Using a consumer-resource model, we show that dose-dependent colonization can arise when niche overlap is high and species compete near-neutrally for shared resources. This model successfully predicts the outcomes of mixtures of strain isolates, in which propagule size has larger, longer-lasting effects in more diverse communities. Our study establishes a framework for predicting the context-dependent impacts of propagule size, providing principles for the design of microbiome therapeutics. less

Understanding how competition varies with environmental stress is critical to anticipating species and community responses to rapid environmental change. While the stress-gradient hypothesis predicts the strength of competition to decrease with increasing stress, our understanding of how competition varies with stress is limited by a lack of mechanistic understanding of how resource-use traits underlying competitive dynamics respond to stress. Here, we use duckweeds in the Lemna species complex to measure how phenotypic and genetic variation in R* (a resource acquisition trait representing the minimum resource requirement for positive population growth) varies with high-temperature stress to better understand how stress alters competitive ability for essential resources. We found that heat stress increased the R* of Lemna plants for nitrogen acquisition. Because lower R* values predict dominance in competitive dynamics where resources are limiting, this indicates that under stressful, high temperatures, plants could experience increased sensitivity to competition due to the higher resources required to sustain positive population growth rates. We found minimal genetic variation in R* across 11 local genotypes within the Lemna species complex, indicating that selection on resource acquisition strategies for essential resources such as nitrogen may be constrained in nature. The expression of genetic variation in R* for nitrogen was further reduced under heat stress, suggesting that the response to selection for R* could be particularly constrained under high-temperature stress. Contrary to predictions drawn from the gleaner-opportunist trade-off, we did not find evidence for a trade-off in resource acquisition strategies under benign conditions or high-temperature stress. Plants with lower R* (i.e., higher growth rates under lower nitrogen levels) were not constrained to have lower growth rates under higher nitrogen levels, possibly because the chosen genotypes have not diverged across resource acquisition strategies or because Lemna spp. has escaped this constraint. Importantly, our work outlines that high-temperature stress could increase sensitivity to competition through increased requirement for resources while reducing the evolutionary potential for Lemna species to respond to selection for resource traits. This study acts as a key step to understanding the mechanistic traits behind competitive dynamics in resource-limited and stressful environments. less

Stormwater ponds frequently receive urban runoff, increasing the likelihood of pesticide contamination. Biofilms growing in surface waters of these ponds are known to accumulate a range of aquatic contaminants, paradoxically providing both water purification services and potentially posing a threat to urban wildlife. Thus, sampling biofilms in stormwater ponds may be a critical and biologically relevant tool for characterizing pesticide contamination and toxicity in urban environments. Here, we aimed to investigate pesticide occurrences at 21 stormwater ponds in Brampton, ON, one of Canada\'s fastest growing municipalities, and quantify their accumulation in biofilm. Over nine weeks, we collected time-integrated composite water and biofilm samples for analysis of ~500 current-use and legacy pesticides. Thirty-two pesticide compounds were detected across both matrices, with 2,4-D, MCPA, MCPP, azoxystrobin, bentazon, triclopyr, and diuron having near-ubiquitous occurrences. Several compounds not typically monitored in pesticide suites (e.g., melamine and nicotine) were also detected, but only in biofilms. Overall, 56% of analytes detected in biofilms were not found in water samples, indicating traditional pesticide monitoring practices fail to capture all exposure routes, as even when pesticides are below detection levels in water, organisms may still be exposed via dietary pathways. Calculated bioconcentration factors ranged from 4.2 - 1275 and were not predicted by standard pesticide physicochemical properties. Monitoring biofilms provides a sensitive and comprehensive supplement to water sampling for pesticide quantification in urban areas, and identifying pesticide occurrences in stormwater could improve source-tracking efforts in the future. Further research is needed to understand the mechanisms driving pesticide accumulation, to investigate toxicity risks associated with pesticide-contaminated biofilm, and to evaluate whether pesticide accumulation in stormwater pond biofilms represents a route through which contaminants are mobilized into the surrounding terrestrial and downstream aquatic environments. less

Ehrlichia chaffeensis is a tick-borne infectious disease transmitted by amblyomma americanum tick. This infectious disease was discovered in the 1970s when military dogs were returning from the Vietnam war. The disease was found to be extremely severe in German Shepards, Doberman Pinschers, Belgium Malinois, and Siberian Huskies. In this study, we developed a mathematical model for dogs and ticks infected with ehrlichia chaffeensis with the aim of understanding the impact of movement on dogs as they move from one location to another. This could be a dog taken on a walk in an urban area or on a hike in the mountains. We carried out a global sensitivity analysis with and without movement between three locations using as response functions the sum of acutely and chronically infected and the sum of infected ticks in all life stages. The parameters with the most significant impact on the response functions are dogs disease progression rate, dogs chronic infection progression rate, dogs recovery rate, dogs natural death rate, acutely and chronically infected dogs disease induced death rate, dogs birth rate, eggs maturation rates, tick biting rate, dogs and ticks transmission probabilities, ticks death rate, and the location carrying capacity. Our simulation results show that infection in dogs and ticks are localized in the absence of movement and spreads between locations with highest infection in locations with the highest rate movement. Also, the effect of the control measures which reduces infection trickles to other locations (trickling effect) when control are implemented in a single location. The trickling effect is strongest when control is implemented in a location with the highest movement rate into it. less