arXiv subjects

Josep Alós

Publications and source records attributed to Josep Alós.

2 recordsLinked to original sources

arXiv2020

MPA network design based on graph network theory and emergent properties of larval dispersal

Despite the recognised effectiveness of networks of Marine Protected Areas (MPAs) as a biodiversity conservation instrument, nowadays MPA network design frequently disregards the importance of connectivity patterns. In the case of sedentary marine populations, connectivity stems not only from the stochastic nature of the physical environment that affects early-life stages dispersal, but also from the spawning stock attributes that affect the reproductive output (e.g., passive eggs and larvae) and its survivorship. Early-life stages are virtually impossible to track in the ocean. Therefore, numerical ocean current simulations coupled to egg and larval Lagrangian transport models remain the most common approach for the assessment of marine larval connectivity. Inferred larval connectivity may be different depending on the type of connectivity considered; consequently, the prioritisation of sites for marine populations' conservation might also differ. Here, we introduce a framework for evaluating and designing MPA networks based on the identification of connectivity hotspots using graph theoretic analysis. We use as a case of study a network of open-access areas and MPAs, off Mallorca Island (Spain), and test its effectiveness for the protection of the painted comber Serranus scriba. Outputs from network analysis are used to: (1) identify critical areas for improving overall larval connectivity; (2) assess the impact of species' biological parameters in network connectivity; and (3) explore alternative MPA configurations to improve average network connectivity. Results demonstrate the potential of graph theory to identify non-trivial egg/larval dispersal patterns and emerging collective properties of the MPA network which are relevant for increasing protection efficiency.

q-bio.PE↗

arXiv2019

Estimating the density of resident coastal fish using underwater cameras: accounting for individual detectability

Technological advances in underwater video recording are opening novel opportunities for monitoring wild fish. However, extracting data from videos is often challenging. Nevertheless, it has been recently demonstrated that accurate and precise estimates of density for animals (whose normal activities are restricted to a bounded area or home range) can be obtained from counts averaged across a relatively low number of video frames. The method, however, requires that individual detectability (PID, the probability of detecting a given animal provided that it is actually within the area surveyed by a camera) has to be known. Here we propose a Bayesian implementation for estimating PID after combining counts from cameras with counts from any reference method. The proposed framework was demonstrated using Serranus scriba as a case-study, a widely distributed and resident coastal fish. Density and PID were calculated after combining fish counts from unbaited remote underwater video (RUV) and underwater visual censuses (UVC) as reference method. The relevance of the proposed framework is that after estimating PID, fish density can be estimated accurately and precisely at the UVC scale (or at the scale of the preferred reference method) using RUV only. This key statement has been extensively demonstrated using computer simulations yielded by real empirical data. Finally, we provide a simulation tool-kit for comparing the expected precision attainable for different sampling effort and for species with different levels of PID. Overall, the proposed method may contribute to substantially enlarge the spatio-temporal scope of density monitoring programs for many resident fish.

q-bio.QM↗