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Effective management of social-ecological systems (SESs) requires an understanding of human behavior. In many SESs, there are hundreds of agents or more interacting with governance and regulatory institutions, driving management outcomes through collective behavior. Agents in these systems often display consistent behavioral characteristics over time that can help reduce the dimensionality of SES data by enabling the assignment of types. Typologies of resource-user behavior both enrich our knowledge of user cultures and provide critical information for management. Here, we develop a data-driven framework to identify resource-user typologies in SESs with high-dimensional data. To demonstrate policy applications, we apply the framework to a tightly coupled SES, commercial fishing. We leverage large fisheries-dependent datasets that include mandatory vessel logbooks, observer datasets, and high-resolution geospatial vessel tracking technologies. We first quantify vessel and behavioral characteristics using data that encode fishers' spatial decisions and behaviors. We then use clustering to classify these characteristics into discrete fishing behavioral types (FBTs), determining that 3 types emerge in our case study. Finally, we investigate how a series of disturbances applied selection pressure on these FBTs, causing the disproportionate loss of one group. Our framework not only provides an efficient and unbiased method for identifying FBTs in near real time, but it can also improve management outcomes by enabling ex ante investigation of the consequences of disturbances such as policy actions.

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To support fishing communities, reserves should ensure the persistence of meta-populations while boosting fisheries yield. However, so far their design from the onset has rarely considered both objectives simultaneously. Here we overcome this barrier in designing a network of reserves for the Caribbean spiny lobster, a species with long larval duration for which local management is considered pointless because the benefits of protection are believed to be accrued elsewhere. Our reserve design approach uses spatially explicit population models and considers ontogenetic migration, larval and adult movement. We show that yield and persistence are negatively related, but that both objectives can be maximized simultaneously during planning. Importantly, we also show that local efforts to manage spiny lobster, the most economically valuable marine resource in the Caribbean, can result in locally accrued benefits, overcoming a major barrier to investing effort in the appropriate management of this species. [ABSTRACT FROM AUTHOR]

Big data, such as vessel monitoring system (VMS) data, can provide valuable information on fishing behaviours. However, conventional methods of detecting behaviours in movement data are challenged when behaviours are briefer than signal resolution. We investigate options for improving detection accuracy for short-set fisheries using 581 648 position records from 181 vessels in the Gulf of Mexico bandit-reel fishery. We first investigate the effects of increasing VMS temporal resolution and find that detection accuracy improves with fishing-set duration. We then assess whether a feature engineering approach—in our case, changing the way pings are labelled when training a classifier—could improve detection accuracy. From a dataset of 12 184 observed sets, we find that the conventional point-labelling method results in only 49% of pings being correctly labelled as ‘fishing’, whereas a novel window-labelling method results in 88% of records being labelled as ‘fishing’. When the labelled data are used to train classifiers, point labelling attains true-positive/balanced-accuracy rates of only 37%/66%, whereas window labelling achieves 68%/83%. Finally, we map fishing distribution using the two methods, and show that point labelling underestimates the extent of fishing grounds by ~33%, highlighting the benefits of window labelling in particular, and feature engineering approaches in general. [ABSTRACT FROM AUTHOR]

Ecosystem management frequently aims to manage resilience yet measuring resilience has proven difficult. Here, we quantify the ecological resilience of the largest reef in the Caribbean and map potential benefits of marine reserves under two scenarios of greenhouse gas emissions. Resilience is calculated using spatial ecological models and defined as the probability of a reef remaining in its coral-dominated basin of attraction such that it does not flip into an alternate, algal-dominated attractor. In practice, resilience is the probability that coral populations will maintain the ability to exhibit a recovery trend after acute disturbances such as hurricanes. The inputs required to estimate resilience are a reef's initial state, physical environment, and disturbance regime. One major driver of reef resilience is herbivory by parrotfish and recent action to protect parrotfish in Belize was found to have increased resilience 6-fold. However, the expected benefits of parrotfish protection to future coral cover were relatively modest with only a 2- to 2.6-fold improvement over a business-as-usual scenario, demonstrating how resilience and ecosystem states are decoupled. Global action to reduce greenhouse gas emissions had little impact on average coral state unless it was accompanied by local controls of fishing. However, combined global and local action reduced the rate of reef degradation threefold. Operationalizing resilience explicitly integrates available biophysical data and accommodates the complex interactions among ecological processes and multiple types of disturbance. [ABSTRACT FROM AUTHOR]

Nearshore marine populations are structured in metapopulations that are connected through larval dispersal across national boundaries. One of the main challenges for effective management of these metapopulations is the need for partnerships between nations that share the same resource. By coupling large‐scale connectivity information to a dynamic population model, we analyzed the patterns of connectivity and population persistence for the Caribbean spiny lobster (Panulirus argus) metapopulation both within and across national boundaries. Although spiny lobster subpopulations are highly connected at the basin scale, several nations located in the northern Caribbean and ecoregional networks could persist independently of the larger basin‐wide metapopulation. Based on these results, we propose transnational neighborhoods for spiny lobster management. Our analysis suggests that the dynamics and management of those subpopulations neighborhoods are not intrinsically dependent on "upstream" connectivity even though current rates of upstream larval supply are very high. [ABSTRACT FROM AUTHOR]