Reply to: Caution over the use of ecological big data for conservation

[Extract] Our global analysis1 estimated the overlap and fishing exposure risk (FEI) using the space use of satellite-tracked sharks and longline fishing effort monitored by the automatic identification system (AIS). In the accompanying Comment, Harry and Braccini2 draw attention to two localized shark–longline vessel overlap hotspots in Australian waters, stating that 47 fishing vessels were misclassified as longline and purse seine vessels in the Global Fishing Watch (GFW)3 2012–2016 AIS fishing effort data product that we used. This, they propose2, results in misidentifications that highlight fishing exposure hotspots that are subject to an unexpected level of sensitivity in the analysis and they suggest that misidentifications could broadly affect the calculations of fishing exposure and the central conclusions of our study1. We acknowledged in our previously published paper1 that gear reclassifications were likely to occur for a small percentage of the more than 70,000 vessels studied, however, here we demonstrate that even using much larger numbers of vessel reclassifications than those proposed by Harry and Braccini2, the central results and conclusions of our paper1 do not change

Reply to: Shark mortality cannot be assessed by fishery overlap alone

[Extract] Our previously published paper1 provided global fine-scale spatiotemporal estimates (1° × 1°; monthly) of overlap and fishing exposure risk (FEI) between satellite-tracked shark space use and automatic identification system (AIS) longline fishing effort. We did not assess shark mortality directly, but in addition to replying to the Comment by Murua et al.2, we confirm—using regression analysis of spatially matched data—that fishing-induced pelagic shark mortality (catch per unit effort (CPUE)) is greater where FEI is higher. We focused on assessing shark horizontal spatiotemporal overlap and exposure risk with fisheries because spatial overlap is a major driver of fishing capture susceptibility and previous shark ecological risk assessments (ERAs) assumed a homogenous shark density within species-range distributions3,4,5 or used coarse-scale modelled occurrence data, rather than more ecologically realistic risk estimates in heterogeneous habitats that were selected by sharks over time. Furthermore, our shark spatial exposure risk implicitly accounts for other susceptibility factors with equal or similar probabilities to those commonly used in shark ERAs3,5