Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences

Abstract: Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs

Continental-scale acoustic telemetry and network analysis reveal new insights into stock structure

Delineation of population structure (i.e. stocks) is crucial to successfully manage exploited species and to address conservation concerns for threatened species. Fish migration and associated movements are key mechanisms through which discrete populations mix and are thus important determinants of population structure. Detailed information on fish migration and movements is becoming more accessible through advances in telemetry and analysis methods however such information is not yet used systematically in stock structure assessment. Here, we described how detections of acoustically tagged fish across a continental-scale array of underwater acoustic receivers were used to assess stock structure and connectivity in seven teleost and seven shark species and compared to findings from genetic and conventional tagging. Network analysis revealed previously unknown population connections in some species, and in others bolstered support for existing stock discrimination by identifying nodes and routes important for connectivity. Species with less variability in their movements required smaller sample sizes (45–50 individuals) to reveal useful stock structure information. Our study shows the power of continental-scale acoustic telemetry networks to detect movements among fishery jurisdictions. We highlight methodological issues that need to be considered in the design of acoustic telemetry studies for investigating stock structure and the interpretation of the resulting data. The advent of broad-scale acoustic telemetry networks across the globe provides new avenues to understand how movement informs population structure and can lead to improved management

Scaling of Activity Space in Marine Organisms across Latitudinal Gradients

Unifying models have shown that the amount of spaceused by animals (e.g., activity space, home range) scales allometricallywith body mass for terrestrial taxa; however, such relationships arefar less clear for marine species. We compiled movement data from1,596 individuals across 79 taxa collected using a continental passiveacoustic telemetry network of acoustic receivers to assess allometric scal-ing of activity space. We found thatectothermic marine taxa do exhibitallometric scaling for activity space, with an overall scaling exponentof 0.64. However, body mass alone explained only 35% of the varia-tion, with the remaining variation best explained by trophic positionfor teleosts and latitude for sharks, rays, and marine reptiles. Taxon-specific allometric relationships highlighted weaker scaling exponentsamong teleostfish species (0.07) than sharks (0.96), rays (0.55), andmarine reptiles (0.57). The allometric scaling relationship and scalingexponents for the marine taxonomic groups examined were lowerthan those reported from studies that had collated both marine andterrestrial species data derived using various tracking methods. Wepropose that these disparities arise because previous work integratedsummarized data across many studies that used differing methods forcollecting and quantifying activity space, introducing considerableuncertainty into slope estimates. Ourfindings highlight the benefitof using large-scale, coordinated animal biotelemetry networks to ad-dress cross-taxa evolutionary and ecological questions