The biogeography of the Peruvian Eastern Pacific coast has been described based on oceanographic parameters and qualitative species occurrence data. This has generated disagreement about the limits and existence of different biogeographic units. In this study, the distribution of rocky-shore macrobenthic communities were recorded over 41 sites along the Peruvian coastline (3.5°S-13.5°S) and analyzed together with historic abiotic data in order to quantitatively evaluate the biogeographic zonation of rocky intertidal communities throughout the region and its relationship with environmental variables to propose an update bioregionalization. Clusters and non-metric multidimensional scaling were performed using Bray-Curtis dissimilarity matrices from abundance data to evaluate biogeographic patterns of dissimilarities of rocky-shore communities. Significant turnover of taxa among defined biogeographical units was tested using permutational multivariate dispersion. Relationships between of the biogeographical community’s structure and environmental factors were examined using Random Forest analysis on datasets available at Bio-Oracle and Jet Propulsion Laboratory—California Institute of Technology. Variation of community structure of 239 taxa depicted three biogeographical units along the region matching Panamic, transitional and Humboldt provinces. Beta diversity analysis indicated a significant turnover of taxa within the transitional unit. Random forest analysis showed a strong correlation between biogeographic units with phosphate, sea surface temperature, nitrate, dissolved oxygen, cloud fraction, and silicates. Our results set the putative limits of three biogeographic units for rocky-shore communities along the coast of Peru, providing base-line information for understanding further biogeographic changes on communities associated with the ongoing regional coastal cooling and impacts of El Niño events.

Early naturalists suggested that predation intensity increases toward the tropics, affecting fundamental ecological and evolutionary processes by latitude, but empirical support is still limited. Several studies have measured consumption rates across latitude at large scales, with variable results. Moreover, how predation affects prey community composition at such geographic scales remains unknown. Using standardized experiments that spanned 115° of latitude, at 36 nearshore sites along both coasts of the Americas, we found that marine predators have both higher consumption rates and consistently stronger impacts on biomass and species composition of marine invertebrate communities in warmer tropical waters, likely owing to fish predators. Our results provide robust support for a temperature-dependent gradient in interaction strength and have potential implications for how marine ecosystems will respond to ocean warming.

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We compare judgments of green turtle (Chelonia mydas) captures elicited from local gillnet skippers and not-for-profit conservation organization employees operating in a small-scale fishery in Peru, to capture rates calculated from a voluntary at-sea observer program operating out of the same fishery. To reduce cognitive biases and more accurately quantify uncertainty in our experts' judgments, we followed the IDEA ("Investigate," "Discuss," "Estimate," and "Aggregate") structured elicitation protocol. The elicited mean monthly estimates of green turtle gillnet captures within summer and winter fishing seasons were higher than the equivalent green turtle capture rates calculated from the fisheries observer data; however, no statistically significant differences were identified when comparing the means of the datasets using bootstrap hypothesis tests (winter observed difference-in-means: 83.15, adj mean ± SD = 42.39 ± 32.59; summer observed difference-in-means: 68.58, adj mean ± SD = 54.06 ± 41.22). We investigated respondent performance in relation to the observer data capture rates. The not-for-profit employees scored high on accuracy and calibration performance metrics. The gillnet skippers' judgments ranked higher on informativeness yet lower on accuracy and calibration, potentially reflective of overconfident judgments. This research presents a new context for using the IDEA protocol, which may prove helpful for rapid, exploratory evaluations of capture and bycatch impact in data-limited small-scale fishery management scenarios.

The effectiveness of behavioural interventions in conservation often depends on local resource users' underlying social interactions. However, it remains unclear to what extent differences in related topics of information shared between resource users can alter network structure—holding implications for information flows and the spread of behaviours. Here, we explore the differences in nine subtopics of fishing information related to the planned expansion of a community co-management scheme aiming to reduce sea turtle bycatch at a small-scale fishery in Peru. We show that the general network structure detailing information sharing about sea turtle bycatch is dissimilar from other fishing information sharing. Specifically, no significant degree assortativity (degree homophily) was identified, and the variance in node eccentricity was lower than expected under our null models. We also demonstrate that patterns of information sharing between fishers related to sea turtle bycatch are more similar to information sharing about fishing regulations, and vessel technology and maintenance, than to information sharing about weather, fishing activity, finances and crew management. Our findings highlight the importance of assessing information-sharing networks in contexts directly relevant to the desired intervention and demonstrate the identification of social contexts that might be more or less appropriate for information sharing related to planned conservation actions.

The effectiveness of biodiversity conservation interventions is often dependent on local resource users' underlying social interactions. However, it remains unclear how fine-scale differences in information shared between resource users can influence network structure and the success of behavior-change interventions. Using network null models that incorporate a pre-network data permutation procedure, we compare information-sharing networks in a Peruvian fishing community where a trial conservation intervention is underway to reduce the incidental capture of sea turtles (bycatch). We show that the general network structure detailing information sharing about sea turtle bycatch differs from other fishing-related information sharing, specifically in degree assortativity and eccentricity. This finding highlights the importance of assessing social networks in contexts directly relevant to the desired intervention and that fine-scale differences in the information shared between resource users may influence network structure. Our findings also demonstrate how null model approaches developed in the ecological sciences can elucidate important differences between human networks and identify the social contexts which might be more or less appropriate for information-sharing related to conservation interventions.

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The effectiveness of biodiversity conservation interventions is often dependent on local resource users' underlying social interactions. However, it remains unclear how fine-scale differences in information shared between resource users can influence network structure and the success of behaviour-change interventions. We investigate this knowledge gap by comparing information-sharing networks in a fishing community in Peru where a trial conservation intervention is underway to reduce the incidental capture of sea turtles (bycatch). We show that the general network structure detailing information sharing about sea turtle bycatch differs from other fishing-related information sharing, specifically in degree assortativity (homophily) and eccentricity. This finding highlights that fine-scale differences in the information shared between resource users may influence network structure.