Spatially-explicit Individual-based Model Research Articles

Error propagation in an integrated spatially-explicit individual-based model

Error propagation is an important consideration in individual-based modeling, but it has been considered insufficiently studied. We investigated the propagation of error due to uncertainty in initial conditions using a previously published spatially-explicit individual-based model that simulates infestation of sorghum by an invasive pest aphid, Melanaphis sorghi (Theobald) [sorghum aphid; previously published as sugarcane aphid, Melanaphis sacchari (Zehntner)]. We initialized the model with aphids in three alternative initial infestation locations using one of three neighboring cells and analyzed the resulting model outputs in three pairwise scenario comparisons. The spatio-temporal patterns of aphid infestation, as estimated by timing and probability of first infestation, were statistically significantly different between the scenarios, but the differences were locally restricted and scenario-dependent. In particular, the two pairwise differences between scenarios originating from neighboring cells indicated that error propagation through the studied system depends not only on the physical distance between the alternative initialization cells (i.e., the extent of the initial spatial uncertainty), but also on the actual location of the model initialization cells, likely reflecting differences in the environmental characteristics of those locations. Despite the statistical significance, the differences were small from the perspective of practical application with few highly localized exceptions. The spatio-temporal trajectories of the propagating error indicate that, within the examined range, the spatial uncertainty in model initialization has a low effect on the timing and probability of first infestation, and the propagation of the error in the observed variables is limited by the system itself.

Predicting point-source invasion success in the Queensland fruit fly (Bactrocera tryoni): An individual-based modelling approach

Fruit flies are a major pest worldwide for fruit producing industries. Incursions into fly free areas usually occurs via infested fruit; however, little is reported about the size of a propagule to start a new establishment. Propagule pressure is an important predictor of the probability that an invasive species will establish a breeding population. Recently, individual-based model (IBM) became a valuable modelling tool for exploring invasive species. Here, we developed a spatially-explicit individual-based model (IBM) specifically parameterized for the Queensland fruit fly (Qfly) (Bactrocera tryoni Froggatt), a major horticultural pest species in Australia and a major quarantine concern worldwide. Usually, new establishments or incursions originate from the introduction of infested fruit and larvae must progress through several stages to become sexually mature adults. For a Qfly incursion to establish a breeding population, flies must avoid predators and survive long enough to become reproductively mature, find a mate, and find ripening fruit. Additionally, their offspring must survive and successfully reproduce. The IBM model simulated release of a fixed number of flies into a heterogeneous environment of varying suitability. We conducted simulations to delineate the contributions of demographic stochasticity and Allee effects (finding a mate in a spatial environment) on establishment probability. Our model delineated several key influential factors, especially tree density, extrinsic mortality and mating range. We performed sensitivity analyses to identity which biological and ecological mechanisms strongly affect establishment probability. Integrating the model's findings with information on transport of infested fruit helps explain why Qfly incursions are common, but yet most fail to establish. Our model predicted that circa 16 and 50 flies were required for a 50% and 99% chance of establishment respectively. Additionally, our model predicted the mating distance for Qfly was 16.1 m. The mean daily dispersal distance was 30 m. We discuss how this knowledge might be used to better manage Qfly by alterations in surveillance and male annihilation technique.

Evaluation of Areawide Forecasts of Wind-borne Crop Pests: Sugarcane Aphid (Hemiptera: Aphididae) Infestations of Sorghum in the Great Plains of North America.

Airborne pests pose a major challenge in agriculture. Integrated pest management programs have been considered a viable response to this challenge, and pest forecasting can aid in strategic management decisions. Annually recurrent areawide sugarcane aphid [Melanaphis sacchari (Zehntner) (Hemiptera: Aphididae)] infestations of sorghum [Sorghum bicolor (L.) Moench (Poales: Poaceae)] in the Great Plains of North America is one of such challenges. As part of the response, a spatially-explicit individual-based model was developed that simulates sugarcane aphid infestations over the southern-to-central part of the region. In this work, we evaluated model forecasts using 2015-2018 field data. The ranges of forecasted days of first infestation significantly overlapped with those observed in the field. The average days of first infestation observed in the field were approximated by the model with differences of less than 28 days in Texas and southern Oklahoma (2015-2018), and in northern Oklahoma (2016-2017). In half of these cases the difference was less than 14 days. In general, the modeled average day of first infestation was earlier than the observed one. As conceptual modeling decisions may impact model forecasts and as various socio-environmental factors may impact spatio-temporal patterns of field data collection, agreement between the forecasts and the observed estimates may vary between locations and seasons. Predictive modeling has the potential to occupy a central position within areawide integrated pest management programs. More detailed consideration of local agricultural practices and local environmental conditions could improve forecasting accuracy, as could broader participation of producers in field monitoring efforts.

Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass✰

The northern stock of European sea bass (Dicentrarchus labrax) is a large, high value, slow growing and late maturing fish that is an important target species for both commercial and recreational fisheries. Around the UK, scientific assessments have shown a rapid eight-year decline in spawning stock biomass since 2010 attributed to poor recruitment; this was likely driven by environmental factors and high fishing mortality. Management of the stock is informed by scientific assessments in which a population model is fitted to the available data and used to forecast the possible consequences of various catch options. However, the model currently used cannot represent the spatial distribution of the stock or any effects of environmental variability. One approach that may be used to represent the effects of spatial and temporal variation in environmental drivers is with Individual based models (IBMs). In IBMs populations are represented by their constituent individuals that interact with their environment and each other. The mechanistic nature of IBMs is often advantageous as a management tool for complex systems including fisheries. Here we add to an existing IBM to produce a spatio-temporally explicit IBM of the northern stock of sea bass in which individual fish respond to local food supply and sea surface temperature. All life stages (i.e., pelagic stages, juvenile and mature fish) are modelled and individual fish have their own realistic energy budgets driven by observed dynamic maps of phytoplankton density and sea surface temperature. The model is calibrated using Approximate Bayesian Computation (ABC). After calibration by ABC the model gives good fits to key population parameters including spawning stock biomass. The model provides a mechanistic link between observed local food supplies and sea surface temperatures and overall population dynamics. Plots of spatial biomass distribution show how the model uses the energy budget to predict spatial and temporal change in sea bass biomass distribution in response to environmental variability. Our results indicate that the IBM is a promising approach that could be used to support stock assessment with scope for testing a range of spatially and temporally explicit management scenarios in addition to testing stock responses to novel environmental change.

The influence of shark behavior and environmental conditions on baited remote underwater video survey results

Baited remote underwater video systems (BRUVS) have become an important and frequently used tool by resource managers to monitor relative abundances for a variety of marine species. As with any abundance survey method, fundamental assumptions of the technique are that counts derived from videos accurately reflect true changes to abundances, while being robust to changes in density-independent factors. We tested these assumptions using a newly developed spatially-explicit individual-based simulation model for two of the most commonly used video survey metrics of relative abundance; MaxN and MeanCount. Simulating a 1-km2 area over a 60-min BRUV deployment targeting elasmobranch species, we evaluated how resulting estimates of each metric were influenced by swimming speed, relative directness of movement patterns, relative attraction strength to bait, bait plume size, and camera visibility range while shark density was held constant. By simulating both standard (120°) and full-spherical (FS; 360°) fields of view (FOV), we were also able to explore if newly developed FS cameras could help reduce the impact of these density-independent factors. Results from both generalized linear models and visual inspection of simulations indicated that density as well as non-density-related factors were highly significant in predicting camera counts, regardless of the camera's FOV or count metric used. Collectively, these findings illustrate that video survey metrics are sensitive to factors unrelated to changes in density, and researchers should carefully consider their potential influence on survey results as well as potential management decisions based on these data.

Modelling the contribution of ephemeral wetlands to landscape connectivity

Habitat loss and fragmentation continue to drive declines of amphibian populations. Maintaining connectivity between aquatic and terrestrial habitats and across wetlands is critical to amphibian conservation, particularly in regions where climate change may exacerbate habitat loss. Our objective was to study the impact of climate- and human-driven losses in ephemeral wetlands on functional connectivity for amphibians, using the endangered western tiger salamander (Ambystoma mavortium) in British Columbia, Canada as a case study. Land use data and dispersal characteristics for the western tiger salamander were used to develop a spatially-explicit individual-based model of amphibian movement. The model was configured to explore connectivity under three climate scenarios (a wet, average, and dry year), and a land management scenario in which only known breeding sites are conserved. We used a spatial network analysis to identify key ephemeral wetlands that connect otherwise isolated sub-networks across the landscape and probable movement paths between wetlands and the upland terrestrial habitat. Our results illustrate the importance of conserving ephemeral wetlands as stepping stones. We argue that a landscape approach to wetland conservation, rather than just conserving known breeding sites, is essential for retaining viable amphibian populations in a context of human induced habitat loss and climate change.

Comparing the plant virus spread patterns of non-persistently transmitted virus and persistently transmitted virus using an individual-based model

Abstract To compare the spread patterns between two types of plant viruses, non-persistent virus (NPV) and persistent virus (PV), we developed a spatially-explicit individual-based model. Our probability-based model is driven by the actions of insect vectors that are affected by interactions with host plants and plant viruses, considering both biological and behavioral components of their relationship. As a model system, we used potato virus y and potato leafroll virus, respectively for NPV and PV, potato for host plant, and Myzus persicae for the insect vector; empirical results from previous studies were acquired and adjusted to be used as our parameter values. Our simulation results showed that initial infection of PV in the field resulted in over 1.3 times greater number of insect vectors while causing approximately 7 times greater number of virus-infected plants compared to NPV by the end of simulation. Furthermore, spatial analysis showed that PV-infected plants showed greater aggregation in the field, forming larger patches compared to NPV-infected plants. Our results demonstrated the importance of host plant and insect vector manipulation by plant viruses as well as biological properties such as infectious period in the insect on the difference in overall spread pattern.

SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics

In 2018 we published a spatially-explicit individual-based model (IBM) that uses satellite-derived maps of food availability and temperature to predict Northeast Atlantic mackerel (Scomber scombrus, NEAM) population dynamics. Since then, to address various ecological questions, we have extended the IBM to include additional processes and data. Throughout its development, technical documents have been provided in the form of e.g. supplementary information to published articles. However, we acknowledge that it would be difficult for potential users to collate information from separate supplementary documents and gain a full understanding of the current state of the IBM. Here, we provide a full technical specification of the latest version of our IBM. The technical specification is provided in the standard ODD (Overview, Design concepts and Details) format, and supplemented by a TRACE (TRAnsparent and Comprehensive model Evaludation) document. For the first time, we give our model the acronym SEASIM-NEAM: a Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics. This article supersedes previous documentation. Going forward we hope that this article will stimulate development of similar models.•This article collates improvements that have been made to SEASIM-NEAM over time.

A spatially-explicit, individual-based demogenetic simulation framework for evaluating hybridization dynamics

Spatially-explicit individual-based simulation models provide a valuable tool for exploring complex ecological and evolutionary processes that are not easily empirically measured. Here, we present modifications of a spatially-explicit individual-based simulation model (CDMetaPOP) to accommodate a two-species system and simulations involving interspecific hybridization. We first describe how a hybrid (H) index is used to distinguish individuals of interspecific descent from those of either parental species. User-defined thresholds provide flexibility in the degree of admixture tolerated for classifying ‘pure’ individuals. We then detail relationships further informed by the H index, including individual growth, temperature-based fitness and selection, and mate preference behavior. Empirically derived species- and system-specific information can be incorporated into these relationships, for example, to produce differential growth among hybrids and parental species. Lastly, we demonstrate an application of this simulation framework by exploring the relative effects of temperature-based selection, mate preference behavior, and hybrid fitness on the rate and spatial extent of sympatric hybridization between two native riverine fish species, bull trout (Salvelinus confluentus) and Dolly Varden (Salvelinus malma), in the upper Skagit River system (United States and Canada). Results from this demonstration provide guidance for future empirical studies of bull trout, a federally threatened species. Understanding factors that contribute to the initiation and maintenance of hybridization, as well as the ecological and evolutionary consequences of this phenomenon, is of increasing importance given shifting species ranges due to large-scale landscape modification and a changing global climate. Our framework can be used to study a wide range of hybridization dynamics in any terrestrial or aquatic system, including comparisons of distinct environmental conditions or potential management responses.

Conservation planning for species recovery under the Endangered Species Act: A case study with the Northern Spotted Owl.

The northern spotted owl (Strix occidentalis caurina) was listed as threatened under the U.S. Endangered Species Act (ESA) in 1990. We applied modern spatial conservation theory and models to evaluate several candidate critical habitat networks, and sought an efficient conservation solution that encompassed the highest value lands for spotted owl recovery rather than maximizing the total area of potential critical habitat. We created a map of relative habitat suitability, which served as input to the spatial conservation prioritization program Zonation. We used the spatially-explicit individual-based population model HexSim to estimate and compare simulated spotted owl population outcomes among a suite of candidate critical habitat networks that varied in size and spatial arrangement under alternative scenarios of future habitat suitability and barred owl (S. varia) effects. We evaluated simulated spotted owl population outcomes, including total population size, and extinction and quasi-extinction likelihoods for 108 combinations of candidate critical habitat networks by habitat change by barred owl scenarios, both range-wide and within 11 distinct portions of the owl’s range. Barred owl encounter rates and the amount and suitability of habitat had substantial effects on simulated spotted owl populations. When barred owl encounter rates were high, changes in the amount and suitability of habitat had minimal impacts on population performance. Under lowered barred owl encounter rates, candidate critical habitat networks that included most existing high suitability habitat supported a high likelihood of long-term population persistence. Barred owls are currently the primary driving force behind poor population performance of NSOs; however, our models demonstrated that a sufficient area of high suitability habitat remains essential for recovery when effects of barred owls can be reduced. The modeling approach we employed is sufficiently flexible to incorporate new information about spotted owls as it becomes available and could likely be applied to conservation planning for other species.

When managers forage for pests: Implementing the functional response in pest management

In this study, we explore how the functional response framework can be implemented in pest management. Here, managers take the role of predators foraging on pests and facing monetary costs for survey and control in a spatial domain where the pest distribution and control strategy do not have to be random. To investigate this framework quantitatively, we simulated various management processes on different pest spatial distributions using a spatially-explicit individual-based model and Monte-Carlo simulations, and also confirmed some of the results analytically. By graphing the number of pests controlled versus pest density, we obtained management functional response curves. Whether the management functional response was shaped like a type I, type II or type III functional response depended on the management costs and the search area. However, the management spatial strategy and the pest spatial distribution had little effect on the functional response. We applied our model to the management of mountain pine beetle epidemic in Cypress Hills, Saskatchewan, Canada, with simulations matching the real number of attacked trees controlled by managers. We showed how to make an analogy between functional responses in predator–prey interactions and in human–pest interactions and thereby, apply insights from the functional response framework to pest management.

Individual‐based models forecast the spread and inform the management of an emerging riverine invader

AbstractAimMounting ecological impacts of invasive species on freshwater ecosystems are among the greatest challenges confronting ecologists and decision‐makers in conserving biodiversity and ecosystem function. Tools to slow the proliferation of aquatic invasive species are still needed to guide the allocation of limited resources more effectively and efficiently once a species is already established. Here we develop mechanistic models to recreate the invasion history of the rusty crayfish Faxonius rusticus in the John Day River (JDR) basin, forecast its future distribution, and evaluate the management efficiency of, and trade‐offs among, population control actions.LocationJohn Day River Basin, Oregon.MethodsThe spread and control of rusty crayfish in the JDR was simulated with a spatially explicit individual‐based model (SEIBM) whereby the life history of each crayfish in the population is modelled in response to environmental conditions that vary across space and time. The model was calibrated by comparing modelled rusty crayfish spread throughout the JDR to known occurrences according to three comprehensive surveys.ResultsOur model accurately reproduced historical rusty crayfish distribution data for 2005, 2010, and 2016 with a specificity and sensitivity of ~80%. Leveraging this realistic model of the spread of rusty crayfish, we show that rapid management actions to the initial invasion would have resulted in an opportunity to slow the spread of rusty crayfish. We instead predict that rusty crayfish will reach the mainstem of the Columbia River by 2025, at which our model predicts that the crayfish population will number on the order of 108 individuals over more than 1100 km of river throughout the watershed and progress into critical salmon spawning habitat.Main conclusionThis study demonstrates that SEIBMs can provide unique insight into the future distribution of aquatic invasive species and concretely support decision‐makers in choosing an optimal control strategy.

A spatial simulation model to explore the long-term dynamics of podocarp-tawa forest fragments, northern New Zealand

Abstract Understanding the interactive effects of fragmentation and invasive species on forest dynamics requires a long-term perspective because they are difficult to assess in the medium- to long-term using observational or experimental data alone. In such settings ecological models have an important role to play. Here we describe the implementation of a spatially explicit individual-based model (SEIBM) representing the dynamics of small forest fragments in northern New Zealand based on empirical data collected in the region. In addition, we performed a baseline analysis to determine how well the model captured podocarp-tawa forest dynamics, and compared its performance with stand structure data obtained from an unfragmented forest in northern New Zealand. We used sensitivity analysis to determine how sensitive the model was to changes in the input parameters. In addition, we simulated different scenarios under diverse management conditions to explore the model’s potential as a management tool. The model captures the stand structural characteristics of the fragments reasonably well but under-predicts stand basal area, suggesting that it does not represent the long-term suppression of some canopy tree species adequately. Although some refinement is needed to improve its performance, we believe that the model presented here is a useful tool for management purposes and for the assessment of the long term viability of forest fragments. The model can help inform managers and decision-makers regarding the long-term persistence of podocarp-tawa forest patches.

Model sensitivity to spatial resolution and explicit light representation for simulation of boreal forests in complex terrain

A model is a simplification of our understanding of reality, but how much simplification is too much? We assessed model sensitivity for a new spatially-explicit individual-based gap model (IBM) SIBBORK to determine how spatial resolution (i.e., plot size) and explicit representation of light and space affect the simulated vegetation characteristics (e.g., structure and composition). The 3-dimensional (3-D) representation of light is the most computationally-expensive part of the simulation, so it is worthwhile to evaluate whether the time, resource and effort of spatial explicity improve predictive capabilities. In the simulation, gap dynamics occur at the plot-level, wherein a certain level of spatial homogeneity is assumed. Therefore, for the simulation of each ecosystem it is imperative to select the appropriate scale at which gap dynamics are simulated, i.e. the plot size. We conducted these sensitivity analyses and qualitatively compared model output to the descriptions of forest structure and composition at two different sites in central and southern Siberia. We systematically varied the plot size (100–900m2) and found that a 100m2 plot is most appropriate for the simulation of the central Siberian boreal forest ecosystem. Moreover, we found that the forest structure and composition simulated under the light environment generated using a 3-dimensional light ray tracing subroutine more closely resembled local and regional forest characteristics at both sites, whereas the growth and stand processes computed based on the simplified (1-D) light conditions approximated only large-scale (continental) average forest structure and biomass for the Eurasian boreal forest.

An adaptable toolkit to assess commercial fishery costs and benefits related to marine protected area network design

Around the world, governments are establishing Marine Protected Area (MPA) networks to meet their commitments to the United Nations Convention on Biological Diversity. MPAs are often used in an effort to conserve biodiversity and manage fisheries stocks. However, their efficacy and effect on fisheries yields remain unclear. We conducted a case-study on the economic impact of different MPA network design strategies on the Atlantic cod ( Gadus morhua) fisheries in Canada. The open-source R package that we developed to analyze this case study can be customized to conduct similar analyses for other systems. We used a spatially-explicit individual-based model of population growth and dispersal coupled with a fisheries management and harvesting component. We found that MPA networks that both protect the target species’ habitat and were spatially optimized to improve population connectivity had the highest net present value (i.e., were most profitable for the fishing industry). These higher profits were achieved primarily by reducing the distance travelled for fishing and reducing the probability of a moratorium event. These findings add to a growing body of knowledge demonstrating the importance of incorporating population connectivity in the MPA planning process, as well as the ability of this R package to explore ecological and economic consequences of alternative MPA network designs.

An adaptable toolkit to assess commercial fishery costs and benefits related to marine protected area network design

Around the world, governments are establishing Marine Protected Area (MPA) networks to meet their commitments to the United Nations Convention on Biological Diversity. MPAs are often used in an effort to conserve biodiversity and manage fisheries stocks. However, their efficacy and effect on fisheries yields remain unclear. We conducted a case-study on the economic impact of different MPA network design strategies on the Atlantic cod (Gadus morhua) fisheries in Canada. The open-source R package that we developed to analyze this case study can be customized to conduct similar analyses for other systems. We used a spatially-explicit individual-based model of population growth and dispersal coupled with a fisheries management and harvesting component. We found that MPA networks that both protect the target species’ habitat and were spatially optimized to improve population connectivity had the highest net present value (i.e., were most profitable for the fishing industry). These higher profits were achieved primarily by reducing the distance travelled for fishing and reducing the probability of a moratorium event. These findings add to a growing body of knowledge demonstrating the importance of incorporating population connectivity in the MPA planning process, as well as the ability of this R package to explore ecological and economic consequences of alternative MPA network designs.

Fish behaviour effects on the accuracy and precision of underwater visual census surveys. A virtual ecologist approach using an individual-based model

Underwater visual census (UVC) methods are used worldwide to monitor shallow marine and freshwater habitats and support management and conservation decisions. However, several sources of bias still undermine the ability of these methods to accurately estimate abundances of some species.The present study introduces FishCensus, a spatially-explicit individual-based model that simulates underwater visual census of fish populations. The model features small temporal and spatial scales and uses a movement algorithm which can be shaped to reflect complex behaviours and effects of diver presence. Four different types of fish were used in the model, featuring typically problematic behavioural traits, namely schooling behaviour, cryptic habits, shyness and boldness. Corresponding control types were also modelled, lacking only the key behavioural traits. Sampling was conducted by a virtual diver using four true fish densities and employing two distinct methods: strip transects and stationary point counts.Comparisons with control fish have shown that schooling and bold behaviours induce positive bias and reduce precision, while cryptic and shy behaviours induce negative bias and increase precision, although shy behaviour did not have a significant effect on precision in transects. By looking at deviations from true density, however, schooling, shy and bold fish densities were strongly overestimated by both methods, while cryptic fish were slightly underestimated. Schooling and bold fish had the lowest precision overall, followed by shy fish. Fish rarity decreased precision, but had no effect on bias. Stationary points had less precision than transects for all fish types, and led to much higher counts, resulting in greater overestimation of density overall.By modelling complex behaviour, it was possible to separate the contributions of detectability and non-instantaneous sampling on bias, and gain a deeper understanding of the effect of behavioural traits on UVC estimates. The model can be used as a tool for planning and optimization of monitoring programs or to calculate conversion factors for past or ongoing surveys, assuming behavioural patterns are well replicated.

Modeling connectivity of walleye pollock in the Gulf of Alaska: Are there any linkages to the Bering Sea and Aleutian Islands?

We investigated the connectivity of walleye pollock in the Gulf of Alaska (GOA) and linkages to the Bering Sea (BS) and Aleutian Island (AL) regions. We used a spatially-explicit Individual-based model (IBM) coupled to 6 years of a hydrodynamic model that simulates the early life history of walleye pollock in the GOA (eggs to age-0 juveniles). The processes modeled included growth, movement, mortality, feeding and the bioenergetics component for larvae and juveniles. Simulations were set to release particles on the 1st of the month (February to May) in fourteen historical spawning areas in the GOA up to the 1st of September each year. Model results reproduced the link between the Shelikof Strait spawning area and the Shumagin nursery region for March and April spawners, besides other Potential Nursery Areas (PNAs) found in the GOA. A prominent finding of this study was the appearance of the BS as important PNAs for several GOA spawning grounds, which is supported by a consistent flow into the BS through Unimak Pass. The simulations showed the highest density of simulated surviving pollock in the western Bering Sea (WBS) region with the lowest coefficients of variation of the whole domain. Three spawning sectors were defined, which aggregate multiple spawning areas in the eastern (EGOA), central (CGOA) and western Gulf of Alaska (WGOA). A connectivity matrix showed strong retention within the CGOA (25.9%) and EGOA (23.8%), but not in the WGOA (7.2%). Within the GOA, the highest connectivity is observed from EGOA to CGOA (57.8%) followed by the connection from CGOA to WGOA (24.3%). Overall, one of the most prominent connections was from WGOA to WBS (62.8%), followed by a connection from CGOA to WBS (29.2%). In addition, scenarios of shifting spawning locations and nursery sectors of GOA, BS and AL are explored and implications for walleye pollock stock structure hypotheses are discussed.

An adaptable toolkit to assess commercial fishery costs and benefits related to marine protected area network design.

Around the world, governments are establishing Marine Protected Area (MPA) networks to meet their commitments to the United Nations Convention on Biological Diversity. MPAs are often used in an effort to conserve biodiversity and manage fisheries stocks. However, their efficacy and effect on fisheries yields remain unclear. We conducted a case-study on the economic impact of different MPA network design strategies on the Atlantic cod ( Gadus morhua) fisheries in Canada. The open-source R toolbox that we developed to analyze this case study can be customized to conduct similar analyses for other systems. We used a spatially-explicit individual-based model of population growth and dispersal coupled with a fisheries management and harvesting component. We found that MPA networks that both protect the target species' habitat (particularly the spawning grounds), and were spatially optimized to improve population connectivity had the highest net present value (i.e., were most profitable for the fishing industry). These higher profits were achieved primarily by reducing the distance travelled for fishing and reducing the probability of a moratorium event. These findings add to a growing body of knowledge demonstrating the importance of incorporating population connectivity in the MPA planning process, as well as the ability of this R toolbox to explore ecological and economic consequences of alternative MPA network designs.

Modeling Behavior by Coastal River Otter (Lontra Canadensis) in Response to Prey Availability in Prince William Sound, Alaska: A Spatially-Explicit Individual-Based Approach.

Effects of climate change on animal behavior and cascading ecosystem responses are rarely evaluated. In coastal Alaska, social river otters (Lontra Canadensis), largely males, cooperatively forage on schooling fish and use latrine sites to communicate group associations and dominance. Conversely, solitary otters, mainly females, feed on intertidal-demersal fish and display mutual avoidance via scent marking. This behavioral variability creates “hotspots” of nutrient deposition and affects plant productivity and diversity on the terrestrial landscape. Because the abundance of schooling pelagic fish is predicted to decline with climate change, we developed a spatially-explicit individual-based model (IBM) of otter behavior and tested six scenarios based on potential shifts to distribution patterns of schooling fish. Emergent patterns from the IBM closely mimicked observed otter behavior and landscape use in the absence of explicit rules of intraspecific attraction or repulsion. Model results were most sensitive to rules regarding spatial memory and activity state following an encounter with a fish school. With declining availability of schooling fish, the number of social groups and the time simulated otters spent in the company of conspecifics declined. Concurrently, model results suggested an elevation of defecation rate, a 25% increase in nitrogen transport to the terrestrial landscape, and significant changes to the spatial distribution of “hotspots” with declines in schooling fish availability. However, reductions in availability of schooling fish could lead to declines in otter density over time.