Combining a cumulative risk index and species distribution data to identify priority areas for marine biodiversity conservation in the Black Sea

Almpanidou, Vasiliki; Doxa, Aggeliki; Mazaris, Antonios D.

doi:10.1016/j.ocecoaman.2021.105877

Cited by 8 publications

(2 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some examples are the highly commercial Atlantic bluefin tuna Thunnus thynnus , the common dentex Dentex dentex , and the critically endangered common goby Pomatoschistus microps . Therefore, strategic, climate‐smart spatial planning and management is needed to cope with the combined effects of anthropogenic stressors and climate change (Almpanidou et al, 2021; Doxa et al, 2022). The governance of fisheries in the era of climate change should support a flexible, adaptive, and well‐informed ecosystem‐based management aiming to face environmental change and provide long‐term yields with reduced risks of stock collapse (Bastardie et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Are Mediterranean marine threatened species at high risk by climate change?

Chatzimentor

Doxa

Katsanevakis

et al. 2023

Global Change Biology

Self Cite

View full text Add to dashboard Cite

Rapid anthropogenic climate change is driving threatened biodiversity one step closer to extinction. Effects on native biodiversity are determined by an interplay between species' exposure to climate change and their specific ecological and life‐history characteristics that render them even more susceptible. Impacts on biodiversity have already been reported, however, a systematic risk evaluation of threatened marine populations is lacking. Here, we employ a trait‐based approach to assess the risk of 90 threatened marine Mediterranean species to climate change, combining species' exposure to increased sea temperature and intrinsic vulnerability. One‐quarter of the threatened marine biodiversity of the Mediterranean Sea is predicted to be under elevated levels of climate risk, with various traits identified as key vulnerability traits. High‐risk taxa including sea turtles, marine mammals, Anthozoa and Chondrichthyes are highlighted. Climate risk, vulnerability and exposure hotspots are distributed along the Western Mediterranean, Alboran, Aegean, and Adriatic Seas. At each Mediterranean marine ecoregion, 21%–31% of their threatened species have high climate risk. All Mediterranean marine protected areas host threatened species with high risk to climate change, with 90% having a minimum of 4 up to 19 species of high climate risk, making the objective of a climate‐smart conservation strategy a crucial task for immediate planning and action. Our findings aspire to offer new insights for systematic, spatially strategic planning and prioritization of vulnerable marine life in the face of accelerating climate change.

show abstract

Section: Discussionmentioning

confidence: 99%

Are Mediterranean marine threatened species at high risk by climate change?

Chatzimentor

Doxa

Katsanevakis

et al. 2023

Global Change Biology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Spatial indicators can be used to identify priority areas and support the design of PAs (Almpanidou et al, 2021). An intuitive method is to select the k-highest percentiles of the indicator as hotspots.…”

Section: Orchids Conservationmentioning

confidence: 99%

Deep Species Distribution Modeling From Sentinel-2 Image Time-Series: A Global Scale Analysis on the Orchid Family

et al. 2022

View full text Add to dashboard Cite

Species distribution models (SDMs) are widely used numerical tools that rely on correlations between geolocated presences (and possibly absences) and environmental predictors to model the ecological preferences of species. Recently, SDMs exploiting deep learning and remote sensing images have emerged and have demonstrated high predictive performance. In particular, it has been shown that one of the key advantages of these models (called deep-SDMs) is their ability to capture the spatial structure of the landscape, unlike prior models. In this paper, we examine whether the temporal dimension of remote sensing images can also be exploited by deep-SDMs. Indeed, satellites such as Sentinel-2 are now providing data with a high temporal revisit, and it is likely that the resulting time-series of images contain relevant information about the seasonal variations of the environment and vegetation. To confirm this hypothesis, we built a substantial and original dataset (called DeepOrchidSeries) aimed at modeling the distribution of orchids on a global scale based on Sentinel-2 image time series. It includes around 1 million occurrences of orchids worldwide, each being paired with a 12-month-long time series of high-resolution images (640 x 640 m RGB+IR patches centered on the geolocated observations). This ambitious dataset enabled us to train several deep-SDMs based on convolutional neural networks (CNNs) whose input was extended to include the temporal dimension. To quantify the contribution of the temporal dimension, we designed a novel interpretability methodology based on temporal permutation tests, temporal sampling, and temporal averaging. We show that the predictive performance of the model is greatly increased by the seasonality information contained in the temporal series. In particular, occurrence-poor species and diversity-rich regions are the ones that benefit the most from this improvement, revealing the importance of habitat's temporal dynamics to characterize species distribution.

show abstract

Speaking Deads: Sea Turtle Mortality Areas and Fisheries Overlaps Identified Through Backtracking of Stranded Carcasses in the Adriatic Sea

Agabiti,

Zanetti,

Quattrocchi

et al. 2024

Aquatic Conservation

View full text Add to dashboard Cite

Interaction with fishing gears represents the main anthropogenic threat at sea for sea turtles worldwide, and identifying the hotspots of turtle bycatch is a priority knowledge gap. Turtle stranding data represent a source of information about mortality areas at sea that are not fully exploited. This study aims to infer turtle mortality areas of turtles stranded along the Italian Adriatic Coast in the period 2019–2021 (1432 records), through backtrack modelling of carcasses. Specifically, the decomposition process of eight loggerhead carcasses was monitored, and the relationship between floating period (FP), turtle size and sea temperature was modelled through a generalized additive model. Oceanographic information was then used to track the routes of floating carcasses back, knowing their size and decomposition stage, and finally estimate the likely area of mortality. A complementary numerical experiment of connectivity between coastal and offshore areas gave indication that areas of potential mortality are relatively close to the coast, particularly in the northern Adriatic. Stranded turtles probably represent just a small fraction (17%–25%) of total at‐sea mortalities in the study area (Italian Adriatic waters), with decomposition rates, season and distance from shore influencing their stranding likelihood. Hence, strandings can inform only about spatio‐temporal variability of coastal mortality hotspots. Inferred areas of turtle mortality were most likely located in the North and Central Adriatic all over the year and overlap with heatmaps of fishing effort, obtained from vessel monitoring system (VMS) and automatic identification system (AIS) data, in the Gulf of Manfredonia and in the North‐West Adriatic in the cold (September–December) and warm (May–August) periods, respectively.

show abstract

Combining a cumulative risk index and species distribution data to identify priority areas for marine biodiversity conservation in the Black Sea

Cited by 8 publications

References 41 publications

Are Mediterranean marine threatened species at high risk by climate change?

Are Mediterranean marine threatened species at high risk by climate change?

Deep Species Distribution Modeling From Sentinel-2 Image Time-Series: A Global Scale Analysis on the Orchid Family

Speaking Deads: Sea Turtle Mortality Areas and Fisheries Overlaps Identified Through Backtracking of Stranded Carcasses in the Adriatic Sea

Contact Info

Product

Resources

About