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Estimating the impacts of anthropogenic disturbances requires an understanding of the habitat use patterns of individuals within a population. This is especially the case when disturbances are localized within a population’s spatial range, as variation in habitat-use within a population can drastically alter the distribution of impacts.Here, we illustrate the potential for multilevel multinomial models to generate spatial networks from capture-recapture data, a common data source use in wildlife studies to monitor population dynamics and habitat use. These spatial networks capture which regions of a population’s spatial distribution share similar/dissimilar individual usage patterns, and can be especially useful for detecting structured habitat use within the population’s spatial range.Using simulations and 18 years of capture-recapture data from St. Lawrence Estuary (SLE) beluga, we show that this approach can successfully estimate the magnitude of similarities/dissimilarities in individual usage patterns across sectors, and identify sectors that share similar individual usage patterns that differ from other sectors, i.e., structured habitat use. In the case of SLE beluga, this method identified multiple clusters of individuals, each preferentially using restricted areas within their summer range of the SLE.Synthesis and applications.Multilevel multinomial models can be effective at estimating spatial structure in habitat use within wildlife populations sampled by capture-recapture of individuals. Our finding of a structured habitat use within the SLE beluga summer range has direct implications for estimating individual exposures to localized stressors, such as underwater noise from shipping or other activities.

This article explores the suitability of Ostrom and colleagues' social-ecological systems framework (SESF) for the study of resource-dependent communities in Canada. Through a broad literature abou...

Vessel underwater noise (VUN) is one of the main threats to the recovery of the endangered St. Lawrence Estuary Beluga population (SLEB). The 1% yearly population decline indicates that the cumulative threats are already beyond sustainable limits for the SLEB. However, a potential threefold increase in shipping traffic is expected within its critical habitat in the coming years resulting from proposed port-industrial projects in the Saguenay River. Current data indicate that SLEB typically use multiple sectors within their summer range, likely leading to differential VUN exposure among individuals. The degree of displacement and spatial mixing among habitats are not yet well understood but can be simulated under different assumptions about movement patterns at the individual and population levels. Here, we propose using an agent-based model (ABM) to explore the biases introduced when estimating exposure to stressors such as VUN, where individual-centric movement patterns and habitat use are derived from different spatial behaviour assumptions. Simulations of the ABM revealed that alternative behavioural assumptions for individual belugas can significantly alter the estimation of instantaneous and cumulative exposure of SLEB to VUN. Our simulations also predicted that with the projected traffic increase in the Saguenay River, the characteristics making it a quiet zone for SLEB within its critical habitat would be nullified. Whereas spending more time in the Saguenay than in the Estuary allows belugas to be exposed to less noise under the current traffic regime, this relationship is reversed under the increased traffic scenario. Considering the importance of the Saguenay for SLEB females and calves, our results support the need to understand its role as a possible acoustic refuge for this endangered population. This underlines the need to understand and describe individual and collective beluga behaviours using the best available data to conduct a thorough acoustic impact assessment concerning future increased traffic.

The recovery of whale species at risk requires the implementation of protection measures designed to mitigate the risks posed by various stressors. In the St. Lawrence Estuary (Canada), several whale species are threatened by navigation activities in various ways. Since 2013, seasonal voluntary ship strike mitigation measures, including a speed reduction area (SRA) and a no-go area, were implemented annually and largely adopted by the maritime industry to reduce the risks of lethal collisions with four species of baleen whales. While the endangered St. Lawrence beluga population is unlikely to be subject to collisions with large merchant ships, it is known to be negatively affected by vessel-generated underwater noise. To assess how these protection measures modify the beluga’s soundscape throughout their critical habitat, we implemented an underwater acoustic module within an existing agent-based model (3MTSim) of ship-whale movements and interactions in the St. Lawrence Estuary. We ran multiple simulations for two scenarios 1) without and 2) with the protection measures to compare the level of noise received by belugas before and after 2013. Overall, the simulations showed a statistically-significant 1.6% decrease in the total amount of noise received by belugas in their critical habitat following the implementation of the protection measures. Although slowing down ships reduces instantaneous radiated noise, it also increases the total amount of acoustic energy released in the environment by extending the time spent in the SRA. Accordingly, our simulations showed a 2.4% increase in the cumulative noise from shipping received by beluga in the SRA. Conversely, belugas located in the Upper Estuary, mostly females and calves, i.e., the most valuable individuals experienced a 5.4% reduction in the cumulative received level of shipping noise. Although refinements are required to improve the modelling of noise sources and propagation for finer scale projections in this complex nearshore environment, this agent-based modelling paradigm of 3MTSim proved informative for underwater acoustic impact assessments.

A study on the perception of vulnerability and adaptive capacity to climate change (CC) was realised among 27 small private forest owners (SPFOs) of a region in southern Quebec. In-depth semi-structured interviews were conducted with SPFOs of diverse profiles to better understand their perception of environmental disturbances and their needs to improve forest management in relation to global change and more precisely to CC. The main purpose of the research was to better understand whether perceptions of vulnerability and adaptive capacity to CC can constitute a barrier to proactive actions toward adaptation. Qualitative data shows a spectrum of attitudes and perceptions which highlight how SPFOs identify different potential and actual disturbances and assess the risk they represent for their forest-based activities. It shows how place-based experiences of environmental disturbances shape perceptions of vulnerability and capacity to adapt to disturbances. Factors such as access to financial resources and perceived resilience of forest ecosystem influence perceived adaptive capacity. Most SPFOs who participated in the research do not perceive their forest or forest-based activities to be vulnerable to CC, which may constitute a barrier to proactive adaptation to CC. The awareness of CC as a general phenomenon does necessarily translate into adaptation in forestry practices. Yet, many participants expressed a need for better access to knowledge and financial support to improve adaptive capacities to CC and broader environmental or economic stressors.

Lethal collisions with ships are limiting the recovery of several at-risk whale species worldwide. In the St. Lawrence Estuary (Quebec, Canada), the endangered blue whale and of special concern fin whale are among the migratory species subject to collisions with large ships. In 2011, a working group composed of representatives from the maritime industry, the government, non-governmental organizations, and academia was created to explore solutions to mitigate ship-whale collisions in the St. Lawrence Estuary. Adopting an adaptive risk management framework, the working group took advantage of the best available scientific data and tools to co-construct realistic collision mitigation options and evaluate their likely benefits for whale conservation and costs for the industry. In 2013, the working group recommended the implementation of voluntary measures to mitigate collision risks, consisting of a slow-down area, a no-go area, and a caution area; a recommended route was added in 2014. Along with the voluntary framework, the working group agreed to continuously monitor compliance with and assess effectiveness of these mitigation measures. After the fourth year of implementation, voluntary measures showed encouraging results, with a reduction of up to 40% of lethal collision risks with fin whales in the highest density area. This reduction in risk is mainly related to ship speed reduction in the slow-down area from 14.1 ± 2.6 knots in 2012 to 11.3 ± 1.7 knots since 2014. The presence of a mandatory pilotage area overlapping with the slow-down area was instrumental to facilitate communication about the mitigation measures, with the pilotage corporation sitting as a regular member of the working group. This resulted in significantly slower speeds in the slow-down area for ships with a pilot from the pilotage corporation onboard compared to those without (-0.8 knots, p-value < 0.001). It is also likely to explain the weaker compliance of the maritime industry with the no-go area located outside of the mandatory pilotage area. Other factors of success include: the continuous dedication of the government to a voluntary and transparent participatory process; the use of available data, tools and institutions; the presence of an environmental certification program representative in the working group; and the adoption by consensus of an adaptive risk management approach. The traditional regulatory approach to conservation is often blamed for its focus on deterring negative behaviors, doing nothing to encourage and reward positive ones. In agreement with other case studies, the benefits of the voluntary measures implemented in the St. Lawrence Estuary include the pro-active commitment from the industry (which is likely to reduce conflicts with regulators), the greater flexibility and freedom that allowed to come up with cost-effective and tailored-made mitigation measures, and the fast achievement of conservation gains. More importantly perhaps, the human and working capital built throughout the concertation process have the potential to be a fundamental cornerstone in dealing with more complex issues such as the chronically increasing level of underwater noise in whale habitats.

Introduction to special issue

Integrating humans in our perception of ecosystems is of critical importance to adequately protect natural resources. This poses the challenge of understanding human decision making in the context of decisions potentially threatening nature's integrity. We developed a spatially explicit agent-based model that simulates commercial whale-watching vessel movements based on a representation of the captains’ decision making process when observing marine mammals in and around the Saguenay–St. Lawrence Marine Park in Quebec, Canada. We focus here on the human part of the global model, the submodel of whale movements having been developed and validated independently ( Lamontagne, 2009 ). The objective of this study is to select and validate a model of whale-watching captains’ decision making using the pattern-oriented modelling approach (POM): three models of cognitive heuristics (satisficing, tallying and Take The Best) along with a null model (random choice) were tested. These concurrent decision making models were built upon knowledge extracted from data collected during field investigations, including interviews with whale-watching captains and park wardens, onboard and shore-based observations, and analyses of a multi-year dataset of sampled whale-watching excursions. Model selection is performed by statistically comparing simulated and real patterns of boat trajectories (excursion length), spatial hotspots (kernel home range 50%), and excursion content (species observed, time allocated to different activities). The selection process revealed that the Take The Best heuristic was the best performing model. We used the distribution of the number of whale-watching boats in the vicinity (2000 m) of each vessel as a secondary pattern to validate the ability of each decision making model to reproduce real observations. Given the prevalence of the species attribute in the choice of which whale to observe, the Take The Best heuristic's ability to deal with non-compensatory information partly explains its overall best performance. Moreover, implementation of communication abilities between modelled captains led to the emergence of persistent observation sites in the park, which is a well-known collective spatiotemporal characteristic of the whale-watching industry; thus validating the fundamental assumption that cooperation is an important mechanism behind the pattern of whale-watching boat dynamics. The relatively good performance of the satisficing and tallying heuristics supports both field evidence and literature on bounded rationality in that humans likely use collections of heuristics (adaptive toolbox) to solve decision problems in different contexts. The POM strategy appears suitable to build up an informative ABM regarding the management of human activities in a natural environment so that further developments will be assessed following the same approach.

A new method, called genetic programming-spectral vegetation index (GP-SVI), for the extraction of information from hyperspectral data is presented. This method is introduced in the context of precision farming. GP-SVI derives a regression model describing a specific crop biophysical variable from hyperspectral images (verified with in situ observations). GP-SVI performed better than other methods [multiple regression, tree-based modeling, and genetic algorithm-partial least squares (GA-PLS)] on the task of correlating canopy nitrogen content in a cornfield with pixel reflectance. It is also shown that the band selection performed by GP-SVI is comparable with the selection performed by GA-PLS, a method that is specifically designed to deal with hyperspectral data.

Anticipating the impacts of a new policy before implementation on a complex social–ecological system is a challenging task for managers and policymakers. This paper reports on the development and use of an agent-based model (ABM) dedicated to support marine park managers in their effort to devise policies to sustainably manage whale-watching activities. The ABM, called the Marine Mammal and Maritime Traffic Simulator (3MTSim), represents the spatiotemporal dynamics of marine mammals and navigation activities in and around the Saguenay–St. Lawrence Marine Park in Canada. In the context of updating the current regulations on whale-watching in the Marine Park, 3MTSim was run to evaluate the merits of a proposed set of rules compared to the current regulations. To do so, a set of variables related to policies’ impacts on the three spheres of sustainable development, namely the impact on whales (Environment), on whale-watching companies (Economy), and tourist experience (Society) was analysed. 3MTSim's simulations highlighted that the proposed rules are expected to improve the situation regarding whale conservation and tourist experience with only marginal impact on the whale-watching industry. In the proposed regulations, one rule is expected to be very influential on whale-watching activities. This rule limits to 10 the number of whale-watching boats allowed to stand within 926 m of any boat in observation mode. Assuming efficient law enforcement, 3MTSim predicts a significant decrease in overall boat concentration around whales in the Marine Park, which is one of the management objectives benefiting both whales and tourists. Interestingly, 3MTSim reveals that this rule could indirectly force some boats to observe second-choice whales present in higher abundance rather than some more attractive species scarcer in the region. This highlights the following management tradeoffs: Reducing boat exposure for the humpback whale and endangered blue whale is likely to increase it for the more abundant fin whale listed as of special concern (Canada's Species at Risk Act) and minke whale. This work demonstrates the utility of ABMs to support policy analysis in the context of sustainable management in a Marine Park. ABMs developed in close relationship with end-users are unarguably a tool of choice to manage complex social–ecological systems since they provide insight into phenomena hard or impossible to measure in the real system. Despite the labour intensive nature of their implementation, this investment is worth the effort.

Landscapes are complex systems. Landscape dynamics are the result of multiple interacting biophysical and socioeconomic processes that are linked across a broad range of spatial, temporal, and organizational scales. Understanding and describing landscape dynamics poses enormous challenges and demands the use of new multiscale approaches to modeling. In this synthesis article, we present three regional systems - i.e., a forest system, a marine system, and an agricultural system - and describe how hybrid, bottom-up modeling of these systems can be used to represent linkages across scales and between subsystems. Through the use of these three examples, we describe how modeling can be used to simulate emergent system responses to different conservation policy and management scenarios from the bottom up, thereby increasing our understanding of important drivers and feedback loops within a landscape. The first case study involves the use of an individual-based modeling approach to simulate the effects of forest harvesting on the movement patterns of large mammals in Canada's boreal forest and the resulting emergent population dynamics. This model is being used to inform forest harvesting and management guidelines. The second case study combines individual and agent-based approaches to simulate the dynamics of individual boats and whales in a marine park. This model is being used to inform decision-makers on how to mitigate the impacts of maritime traffic on whales in the Saint Lawrence Estuary in eastern Canada. The third example is a case study of biodiversity conservation efforts on the Eyre Peninsula, South Australia. In this example, the social-ecological system is represented as a complex network of interacting components. Methods of network analysis can be used to explore the emergent responses of the system to changes in the network structure or configuration, thus informing managers about the resilience of the system. These three examples illustrate how bottom-up modeling approaches may contribute to a new landscape science based on scenario building, to find solutions that meet the multiple objectives of integrated resource management in social-ecological systems.

Les diverses conséquences des activités de navigation sur le milieu marin sont maintenant reconnues et de plus en plus documentées, en particulier sur les mammifères marins. Dans les dernières années, les gouvernements se sont engagés à rehausser le niveau de protection du milieu marin, notamment par la création d’aires marines protégées. Le système d’identification automatique (AIS), implémenté à l’origine pour la sécurité maritime et la gestion du trafic, est devenu un outil indispensable pour la gestion des activités de navigation dans un contexte de conservation de l’environnement marin. Afin de présenter différentes applications des données AIS dans la gestion d’une aire marine protégée, nous utilisons comme étude de cas le parc marin du Saguenay–Saint-Laurent, reconnu pour la diversité des espèces de mammifères marins qui le fréquentent et pour l’intensité du trafic maritime. Les exemples portent sur la description de l’utilisation de l’espace maritime par les activités de navigation, sur l’évaluation et la modélisation de leurs effets environnementaux et sur le suivi de la conformité à des mesures de gestion. En plus d’illustrer les différents avantages d’utilisation des données AIS, une revue critique sur les limites de ces données en conservation est également présentée., The diverse impacts of shipping activities on the marine environment are now recognized and increasingly documented, particularly with regards to marine mammals. In recent years, governments have committed to enhancing the protection of the marine environment, notably through the creation of marine protected areas. The Automatic Identification System (AIS), originally introduced for maritime safety and traffic control, has become an essential tool for the management of shipping activities for the conservation of marine environments. The present paper uses the Saguenay–St. Lawrence Marine Park (Québec, Canada), recognized for its high diversity of marine mammals and intensive traffic, to highlight the different potential uses of AIS data in the management of a marine protected area. Examples presented include describing baseline vessel use of a maritime area, assessing and modelling the environmental impacts of the shipping activities, and monitoring compliance to management measures. The different benefits of using AIS data in a conservation context are illustrated, and their limitations are outlined.