A social-ecological approach to estimate fisher resilience: a case study from Brazil

Social-ecological systems (SESs), such as fishing communities, are human and biophysical subsystems that are intrinsically connected to one another and strongly depend on natural resources. That is why these human groups are usually the first to feel the effects of policies concerning fisheries and ocean governance and the most affected by them. These policies can potentially build or erode social-ecological resilience (SER), especially if they are coupled with environmental changes. SER assessments offer a valuable tool to identify human-nature linkages, and the implications and feedbacks in SESs when facing human-induced or natural changes. We created a SER index by combining interviews with fishers with environmental datasets on a fine scale that has never been presented for the Brazilian coast. This scale was then tested in marine protected areas that allow sustainable use. Our approach estimated SER from information on fisheries ecosystem services and adaptive capacity at the local scale, considering the individual and community levels. We synthesized blocks of critical indicators of an individual or community’s ability to build and maintain resilience in SESs, such as flexibility, ability to learn, ability to organize, assets, social capital, and ecological characteristics. We identified that fishers’ ability to learn and to organize, as well as the biological sensitivity of an ecosystem are determinant to enhancing SER in the studied coastal communities. A Bayesian model also showed that the fishers’ SER was related to socioeconomic factors, thereby indicating that older fishers, fishers who consistently catch more fish, and fishers with a higher reliance on fishing for their income presented lower index values. By knowing the variables that influence the ability of fishers to cope with changes to their SESs, we can devise smarter management approaches that may include compensatory mechanisms for more fragile fishers. Our findings can also inform decision making about where fisheries management strategies are likely to be more participative and effective in order to minimize the social impacts of policy decisions and increase SER in coastal communities.Postprint2,51

Coral distribution and bleaching vulnerability areas in Southwestern Atlantic under ocean warming

Global climate change is a major threat to reefs by increasing the frequency and severity of coral bleaching events over time, reducing coral cover and diversity. Ocean warming may cause shifts in coral communities by increasing temperatures above coral’s upper thermal limits in tropical regions, and by making extratropical regions (marginal reefs) more suitable and potential refugia. We used Bayesian models to project coral occurrence, cover and bleaching probabilities in Southwestern Atlantic and predicted how these probabilities will change under a high-emission scenario (RCP8.5). By overlapping these projections, we categorized areas that combine high probabilities of coral occurrence, cover and bleaching as vulnerability-hotspots. Current coral occurrence and cover probabilities were higher in the tropics (1°S–20°S) but both will decrease and shift to new suitable extratropical reefs (20°S–27°S; tropicalization) with ocean warming. Over 90% of the area present low and mild vulnerability, while the vulnerability-hotspots represent ~ 3% under current and future scenarios, but include the most biodiverse reef complex in South Atlantic (13°S–18°S; Abrolhos Bank). As bleaching probabilities increase with warming, the least vulnerable areas that could act as potential refugia are predicted to reduce by 50%. Predicting potential refugia and highly vulnerable areas can inform conservation actions to face climate change.Postprint2,92

Social-ecological trends: managing the vulnerability of coastal fishing communities

The loss of biodiversity, including the collapse of fish stocks, affects the vulnerability of social-ecological systems (SESs) and threatens local livelihoods. Incorporating community-centered indicators and SES drivers and exposures of change into coastal management can help anticipate and mitigate human and/or coastal vulnerability. We have proposed a new index to measure the social-ecological vulnerability of coastal fishing communities (Index of Coastal Vulnerability [ICV]) based on species, ecosystem, and social indicators. The ICV varies from 0 (no vulnerability) to 1 (very high vulnerability) and is composed of 3 components: species vulnerability, i.e., fish biological traits; ecosystem vulnerability, i.e., environmental indicators of ecosystem health; and adaptive capacity, i.e., human ability to cope with changes. We tested the ICV of Brazil’s 17 coastal states. The average ICV for the Brazilian coast was 0.77, and variation was low among states. More than half of the coastal states revealed very high vulnerability (> 0.8). The ecosystem vulnerability values were worse than the adaptive capacity and species vulnerability values, and the North and Northeast regions were revealed to be vulnerable hot spots. Additionally, we investigated how the ICV related to specific anthropogenic risks, i.e., fish landing richness, fishery instability, market, coastal extension, and coastal population, and found that states with fewer species landings and higher coastal populations presented higher ICVs. At a time when human impacts are overtaking natural processes, understanding how these impacts lead to coastal vulnerability can help improve conservation policies. For this case study, we suggest both fisheries management measures and restoration of sensitive habitats to protect species and decrease vulnerability. The integrated evaluation developed here could be used as a baseline for coastal monitoring and conservation planning and be applied to coastal regions in which governments evaluate both social and biological aspects.Postprint2,51

Supporting Spatial Management of Data-Poor, Small-Scale Fisheries With a Bayesian Approach

Marine conservation areas are an important tool for the sustainable management of multispecies, small-scale fisheries. Effective spatial management requires a proper understanding of the spatial distribution of target species and the identification of its environmental drivers. Small-scale fisheries, however, often face scarcity and low-quality of data. In these situations, approaches for the prioritization of conservation areas need to deal with scattered, biased, and short-term information and ideally should quantify data- and model-specific uncertainties for a better understanding of the risks related to management interventions. We used a Bayesian hierarchical species distribution modeling approach on annual landing data of the heavily exploited, small-scale, and data-poor fishery of Chwaka Bay (Zanzibar) in the Western Indian Ocean to understand the distribution of the key target species and identify potential areas for conservation. Few commonalities were found in the set of important habitat and environmental drivers among species, but temperature, depth, and seagrass cover affected the spatial distribution of three of the six analyzed species. A comparison of our results with information from ecological studies suggests that our approach predicts the distribution of the analyzed species reasonably well. Furthermore, the two main common areas of high relative abundance identified in our study have been previously suggested by the local fisher as important areas for spatial conservation. By using short-term, catch per unit of effort data in a Bayesian hierarchical framework, we quantify the associated uncertainties while accounting for spatial dependencies. More importantly, the use of accessible and interpretable tools, such as the here created spatial maps, can frame a better understanding of spatio-temporal management for local fishers. Our approach, thus, supports the operability of spatial management in small-scale fisheries suffering from a general lack of long-term fisheries information and fisheries independent data.En prens

Modelling the effect of environmental variables on the reproductive success of Griffon Vulture (Gyps fulvus) in Sardinia, Italy

Old World vultures are experiencing dramatic population declines and now are among the species most threatened with extinction. Understanding the environmental variables that can influence the reproductive indexes of vulture populations can facilitate both habitat and species management. The aim of this study was to identify which environmental variables primarily affect the breeding successes of the Griffon Vulture Gyps fulvus in northern Sardinia by applying a Bayesian hierarchical model. A unique dataset of reproductive records (197 nests monitored over 39 years for a total of 992 breeding records) was used. Eight environmental and topographical variables describing the habitat at the nesting sites were considered as potential predictors of breeding success. These included mean annual temperature, mean annual precipitation, isothermality, elevation, the normalized difference vegetation index, wind speed, and the aspect and slope of the land surface. In addition, we also considered the effect of human disturbance and the type of nest. According to our best model, the probability of successfully raising a chick in Griffon Vultures was higher in nests exposed to a high wind speed, not covered by natural shelters, where the vegetation was mostly represented by shrub and pastures, with low human disturbance and in years with low rainfall. This model will be useful for management of the breeding habitat and to identify the area most suitable for Griffon Vulture reproduction. This information is crucial for programming conservation measures aimed at enlarging the area of occupancy of the species.Postprin

Using a Bayesian modelling approach (INLA‑SPDE) to predict the occurrence of the Spinetail Devil Ray (Mobular mobular)

To protect the most vulnerable marine species it is essential to have an understanding of their spatiotemporal distributions. In recent decades, Bayesian statistics have been successfully used to quantify uncertainty surrounding identified areas of interest for bycatch species. However, conventional simulation-based approaches are often computationally intensive. To address this issue, in this study, an alternative Bayesian approach (Integrated Nested Laplace Approximation with Stochastic Partial Differential Equation, INLA-SPDE) is used to predict the occurrence of Mobula mobular species in the eastern Pacific Ocean (EPO). Specifically, a Generalized Additive Model is implemented to analyze data from the Inter-American Tropical Tuna Commission’s (IATTC) tropical tuna purse-seine fishery observer bycatch database (2005–2015). The INLA-SPDE approach had the potential to predict both the areas of importance in the EPO, that are already known for this species, and the more marginal hotspots, such as the Gulf of California and the Equatorial area which are not identified using other habitat models. Some drawbacks were identified with the INLA-SPDE database, including the difficulties of dealing with categorical variables and triangulating effectively to analyze spatial data. Despite these challenges, we conclude that INLA approach method is an useful complementary and/or alternative approach to traditional ones when modeling bycatch data to inform accurately management decisions.En prensa2,92

The missing whales: relevance of “struck and lost” rates for the impact assessment of historical whaling in the southwestern Atlantic Ocean

The massive impact that open-boat historical whaling (18th to 20th centuries) had on whale populations has been traditionally estimated from records of oil and baleen plate production. However, an unknown proportion of hunted whales were struck, wounded, eventually killed, but lost, and not included in these records, suggesting that whaling impact may be critically underestimated. Whaling logbooks provide a key source for assessing past catches and losses. Here, we extract detailed records of 19875 days of activity in the southwestern Atlantic Ocean from 255 logbooks of offshore whaling voyages. During the period considered (1776–1923), whalers first targeted southern right whales (Eubalaena australis, 2497 sightings and 658 catches), gradually substituted by sperm whales (Physeter macrocephalus, 1157 sightings and 843 catches) after 1840. Loss rate factors, calculated to account for the number of “struck and lost” whales, decreased across time for both species, and were particularly high (ranging 1.09–1.6) for the southern right whale, whose population was drastically reduced by whaling, as compared to previous estimates based on rough catch records. Accurate accounting for these “lost” individuals is essential for reconstructing the impact of whaling on cetacean populations and for a proper assessment of their initial population size and demographic trends.Postprint2,27

Evaluación de los cambios en la talla de madurez de la merluza europea (Merluccius merluccius) en las aguas atlánticas ibéricas

European hake (Merluccius merluccius) is a commercially important resource in Iberian Atlantic waters. Despite the recovery plan implemented in 2006 and the multiannual management plan for western waters, fishing mortality is still higher than that corresponding to the maximum sustainable yield for the southern European hake stock. The biological processes underlying the dynamics of this stock and its life history traits are essential for assessing population productivity and resilience, making them basic information for management. We analysed the temporal variability of size at maturity (L50) of this species and the main factors influencing it in Atlantic Iberian waters from 1982 to 2019. The annual variability of L50 for each sex was modelled with generalized additive models, considering explanatory environmental variables (Atlantic Multidecadal Oscillation, North Atlantic Oscillation and sea surface temperature) and biological variables (biomass, spawning biomass at length and relative condition factor). The results showed that the L50 of males decreased by a total of 12.9 cm and L50 of females decreased by a total of 10.9 cm from 1982 to 2019. For females the significant explanatory variables were year, spawning biomass at length, biomass and the North Atlantic Oscillation, while for males only year was an explanatory variable. These results are important for understanding the status of the European hake population, signalling that L50 is a good indicator for predicting future population dynamics.La merluza europea (Merluccius merluccius) es un recurso comercialmente importante en aguas Atlánticas Ibéricas. A pesar del plan de recuperación puesto en marcha en 2006 y del plan de gestión plurianual de las aguas occidentales, la mortalidad por pesca sigue siendo superior a la correspondiente al rendimiento máximo sostenible de la población de merluza del sur de Europa. Comprender los procesos biológicos que subyacen a la dinámica de este stock y proporcionar información sobre los rasgos de la historia de vida es fundamental para evaluar la productividad y la resiliencia de la población, convirtiéndolos en información básica para la gestión. Analizamos la variabilidad temporal de la talla de madurez (L50) y los principales factores que influyen en ella, desde 1982 hasta 2019 en aguas Atlánticas Ibéricas. La variabilidad anual de L50 para cada sexo se modeló con Modelos Aditivos Generalizados considerando variables ambientales explicativas (Oscilación Multidecadal del Atlántico, Oscilación del Atlántico Norte y Temperatura Superficial del Mar), y variables biológicas (biomasa, biomasa reproductora por talla y factor de condición relativo). Los resultados mostraron que la de los machos disminuyó en un total de 12,9 cm y la L50 de las hembras disminuyó en un total de 10,9 cm de 1982 a 2019. Para las hembras las variables explicativas significativas fueron año, biomasa de desove por talla, biomasa y NAO, mientras que para los machos solo el año. Estos resultados son importantes para comprender el estado de la población de merluza europea, lo que destaca que la L50 es un buen indicador para predecir la dinámica futura de la población

Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach

In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model. Inference and prediction is performed using the integrated nested Laplace approximation methodology to reduce the computational burden. We illustrate the performance of the coregionalized model in species interaction scenarios using both simulated and real data. The simulation demonstrates the better predictive performance of the coregionalized model with respect to the univariate models. The case study focus on the spatial distribution of a prey species, the European anchovy (Engraulis encrasicolus), and one of its predator species, the European hake (Merluccius merluccius), in the Mediterranean sea. The results indicate that European hake and anchovy are positively associated, resulting in improved model predictions using the coregionalized model.Postprin

On the Role of Perception: Understanding Stakeholders’ Collaboration in Natural Resources Management through the Evolutionary Theory of Innovation

Natural resources management deals with highly complex socioecological systems. This complexity raises a conundrum, since wide-ranging knowledge from different sources and types is needed, but at the same time none of these types of knowledge is able by itself to provide the basis for a viable productive system, and mismatches between the two of them are common. Therefore, a growing body of literature has examined the integration of different types of knowledge in fisheries management. In this paper, we aim to contribute to this ongoing debate by integrating the evolutionary theory of innovation—and specifically the concept of proximity—and the theory of perception. We set up a theoretical framework that is able to explain not only why the different types of knowledge differ, but also why they should differ and why this divergence is useful to develop fisheries management. This framework is illustrated through a well-known complex scenario, as was the implementation of the Landing Obligation (LO) in Europe. We conclude that diversity (distance) between types of knowledge is essential for interactive learning, innovation, the incorporation of new ideas or to avoid lock-in, etc. At the same time, cognitive, institutional, geographical, etc. proximity is needed for effective communication, participation and dialoguePostprin