Integrated assessment of metal contamination in sediments from two tropical estuaries.

In order to evaluate if sediment metal contamination is responsible for benthic degradation and identify possible reference sites in Todos os Santos Bay (TSB), comparisons between a highly impacted (Subaé) and less impacted (Jaguaripe) estuarine systems were made based on (i) field assessment of macrobenthic assemblage, (ii) sediment metal concentrations and (iii) chronic toxicity test with the tropical copepod Nitokra sp. Data were integrated by multivariate analysis (BIOENV and PCA) and the ratio-to-mean (RTMe) approach. Estuaries were divided into four different salinity zones to avoid misclassification of benthic conditions. Salinity was the main variable correlated to the benthic distribution in both estuaries, indicating that categories based on salinity features seem to be suitable in TSB. Correspondence among lines of evidence differed in low and high metal contaminated systems. Chronic toxicity was found along both the entire systems, being considerably higher in Jaguaripe. However, there was no clear evidence of metal contamination and benthic alteration in most stations of Jaguaripe. Although the concentrations of Sr and Cu were correlated to the benthic assemblage in Jaguaripe, it is unlikely that toxicity has been caused by these elements. The benthic assemblage distribution of Jaguaripe seems to be rather related to natural stressful conditions of transitional waters. Even though the Jaguaripe estuary might not be pristine, it can be used as a reference estuary for benthic assessment in TSB. Regarding the Subaé estuary, toxicity and Zn were also correlated to the benthic assemblage and most stations showed signs of benthic alteration and metal contamination. All lines of evidence were in agreement providing evidences that metal contamination might be responsible for benthic degradation in Subaé.

Mercury Exposure and Habitat Fragmentation Affect the Movement, Foraging Behavior, and Search Efficiency of the Marsh Periwinkle (Littorina irrorata).

The interactions between habitat fragmentation and other stressors are considered a key knowledge gap. The present study tested the hypotheses that mercury enhances the effects of fragmentation by (1) reducing the cumulative daily movement of organisms, (2) shifting their foraging behavior, and (3) altering the vertical movement of the marsh periwinkle (Littoraria irrorata) in a field experiment. Random walk simulations were used to access how changes in movement affect the search efficiency of organisms in the long term. Eighteen 1.5 m2 plots were constructed in a salt marsh where landscapes characteristics were manipulated to reach three different levels of habitat cover. Daily movement of 12 marked control and mercury-exposed snails were measured in each plot. Bayesian models were used to analyze the data and evidence ratios were used to test the hypotheses. The results showed that the effects of fragmentation were consistent in both control and exposed treatments, with an increase in the cumulative displacement of organisms. However, mercury significantly reduced the movement of organisms in all levels of fragmentation, shifting their foraging behavior (evidence ratio > 1000). Exposed snails were more likely to be found inactive in comparison with the control treatment (evidence ratio > 1000). Fragmentation also reduced the vertical movement of organisms in both treatments. In contrast, mercury increased the vertical movement of organisms (evidence ratio > 1000). The search efficiency of organisms also increased in a highly fragmentated landscape, suggesting that changes in foraging behavior are likely due to reduced resources and consequently increase in foraging effort. The present study shows that mercury exposure can enhance the effects of habitat fragmentation by changing organisms' movement, foraging behavior, and search efficiency. Environ Toxicol Chem 2023;42:1971-1981. © 2022 SETAC.

Mangrove microbial community recovery and their role in early stages of forest recolonization within shrimp ponds.

Shrimp farming is blooming worldwide, posing a severe threat to mangroves and its multiple goods and ecosystem services. Several studies reported the impacts of aquaculture on mangrove biotic communities, including microbiomes. However, little is known about how mangrove soil microbiomes would change in response to mangrove forest recolonization. Using genome-resolved metagenomics, we compared the soil microbiome of mangrove forests (both with and without the direct influence of shrimp farming effluents) with active shrimp farms and mangroves under a recolonization process. We found that the structure and composition of active shrimp farms microbial communities differ from the control mangrove forests, mangroves under the impact of the shrimp farming effluents, and mangroves under recolonization. Shrimp farming ponds microbiomes have lower microbial diversity and are dominated by halophilic microorganisms, presenting high abundance of multiple antibiotic resistance genes. On the other hand, control mangrove forests, impacted mangroves (exposed to the shrimp farming effluents), and recolonization ponds were more diverse, with a higher abundance of genes related to carbon mobilization. Our data also indicated that the microbiome is recovering in the mangrove recolonization ponds, performing vital metabolic functions and functionally resembling microbiomes found in those soils of neighboring control mangrove forests. Despite highlighting the damage caused by the habitat changes in mangrove soil microbiome community and functioning, our study sheds light on these systems incredible recovery capacity. Our study shows the importance of natural mangrove forest recovery, enhancing ecosystem services by the soil microbial communities even in a very early development stage of mangrove forest, thus encouraging mangrove conservation and restoration efforts worldwide.

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems.

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.

Joint Effects of Fragmentation and Mercury Contamination on Marsh Periwinkle (Littoraria irrorata) Movement.

There are different ways contaminants can interact and enhance the effects of habitat fragmentation, such as modifying the movement of organisms. The present study tested the hypothesis that mercury exacerbates the effects of fragmentation by affecting the movement of the marsh periwinkle Littoraria irrorata and reducing the probability of snails crossing fragmented microlandscape experimental systems. How these changes could affect the search efficiency of organisms in the long term was assessed using hidden Markov models and random walks simulations. Bayesian nonlinear models were used to analyze the effects of fragmentation and contamination on the mean speed and mean directional change of organisms. Snail movement for control and two mercury-exposure treatments were recorded in microlandscapes with six different levels of habitat cover and three landscape replicates. The results indicated that exposed organisms had lower probabilities of crossing the landscape, reduced speed, and shifts in step length distributions. Both mercury exposure and habitat fragmentation affected the movement of the marsh periwinkle. Mercury exacerbated the effects of habitat fragmentation by affecting the cognition (e.g., route planning, orientation, and spatial learning) and movement of L. irrorata. Hence, the interaction of these stressors could further reduce the functional connectivity of landscapes and reduce the search efficiency of organisms. Environ Toxicol Chem 2022;41:1742-1753. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Comparing statistical analyses to estimate thresholds in ecotoxicology.

Different methods are used in ecotoxicology to estimate thresholds in survival data. This paper uses Monte Carlo simulations to evaluate the accuracy of three methods (maximum likelihood (MLE) and Markov Chain Monte Carlo estimates (Bayesian) of the no-effect concentration (NEC) model and Piecewise regression) in estimating true and apparent thresholds in survival experiments with datasets having different slopes, background mortalities, and experimental designs. Datasets were generated with models that include a threshold parameter (NEC) or not (log-logistic). Accuracy was estimated using root-mean square errors (RMSEs), and RMSE ratios were used to estimate the relative improvement in accuracy by each design and method. All methods had poor performances in shallow and intermediate curves, and accuracy increased with the slope of the curve. The EC5 was generally the most accurate method to estimate true and apparent thresholds, except for steep curves with a true threshold. In that case, the EC5 underestimated the threshold, and MLE and Bayesian estimates were more accurate. In most cases, information criteria weights did not provide strong evidence in support of the true model, suggesting that identifying the true model is a difficult task. Piecewise regression was the only method where the information criteria weights had high support for the threshold model; however, the rate of spurious threshold model selection was also high. Even though thresholds are an attractive concept from a regulatory and practical point of view, threshold estimates, under the experimental conditions evaluated in this work, should be carefully used in survival analysis or when there are any biological reasons to support the existence of a threshold.