Mapping Potential Population-Level Pesticide Exposures in Ecuador Using a Modular and Scalable Geospatial Strategy.

Human populations and ecosystems are extensively exposed to pesticides. Most nations lack the capacity to control pesticide contamination and have limited availability of pesticide use information. Ecuador is a country with intense pesticide use with high exposure risks to humans and the environment, although relative or combined risks are not well understood. Here, we analyzed the distribution of application rates in Ecuador and identified regions of concern because of high potential exposure. We used a geospatial analysis to identify grid cells (∼8 km × 8 km) where the highest pesticide application rates and density of human populations overlap. Furthermore, we identified other regions of concern based on the number of amphibian species as an indicator of ecosystem integrity and the location of natural protected areas. We found that 28% of Ecuador's population dwelled in areas with high pesticide application rate. We identified an area of ∼512 km2 in the Amazon region where high application rates, large human settlements, and a high number of amphibian species overlapped. Additionally, we distinguished clusters of pesticide application rates and human populations that intersected with natural protected areas. Ecuador exemplifies how pesticides are disproportionately applied in areas with the potential to affect human health and ecosystems' integrity. Global estimates of population dwelling, pesticide application rates, and environmental factors are key in prioritizing locations to conduct further exposure assessments. The modular and scalable nature of the geospatial tools we developed can be expanded and adapted to other regions of the world where data on pesticide use are limited.

Mapping the functional connectivity of ecosystem services supply across a regional landscape.

Sustainably managing multifunctional landscapes for production of multiple ecosystem services (ES) requires thorough understanding of the interactions between ES and the ecological processes that drive them. We build upon landscape connectivity theory to present a spatial approach for assessing functional connections between multiple ES at the landscape scale, and take a closer look at the concept of ES interactions by explicitly representing the mechanisms behind the relationships between ES. We demonstrate application of the approach using existing ES supply mapping data for plant agriculture, waterflow regulation, and landscape aesthetics and map the functional connectivity between them. We find that, when weights of all linkages were amalgamated, areas of high-value connectivity are revealed that are not present on any individual ES supply area or pairwise link maps, which suggests that the spatial focus of planning for optimal service provisioning may shift when functional relationships between several ES are considered. From water flow supply areas, our modeling maps several functional connections that operate over both short and long distances, which highlights the importance of managing ES flows both locally and across jurisdictions. We also found that different land use and land cover types than those associated with ES supply areas may be serving as critical corridors connecting interdependent ES. By providing spatial information on ES connectivity, our approach enables local and regional environmental planning and management to take full consideration of the complex, multi-scale interactions between ecological processes, land use and land cover, and ecosystem service supply on a landscape.

Combining agent-based, trait-based and demographic approaches to model coral-community dynamics.

The complexity of coral-reef ecosystems makes it challenging to predict their dynamics and resilience under future disturbance regimes. Models for coral-reef dynamics do not adequately account for the high functional diversity exhibited by corals. Models that are ecologically and mechanistically detailed are therefore required to simulate the ecological processes driving coral reef dynamics. Here, we describe a novel model that includes processes at different spatial scales, and the contribution of species' functional diversity to benthic-community dynamics. We calibrated and validated the model to reproduce observed dynamics using empirical data from Caribbean reefs. The model exhibits realistic community dynamics, and individual population dynamics are ecologically plausible. A global sensitivity analysis revealed that the number of larvae produced locally, and interaction-induced reductions in growth rate are the parameters with the largest influence on community dynamics. The model provides a platform for virtual experiments to explore diversity-functioning relationships in coral reefs.

A voluntary conservation agreement reduces the risks of lethal collisions between ships and whales in the St. Lawrence Estuary (Québec, Canada): From co-construction to monitoring compliance and assessing effectiveness.

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.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis).

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning.

Uniting statistical and individual-based approaches for animal movement modelling.

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Spatio-temporal dynamics in the response of woodland caribou and moose to the passage of grey wolf.

Predators impact prey populations not only by consuming individuals, but also by altering their behaviours. These nonlethal effects can influence food web properties as much as lethal effects. The mechanisms of nonlethal effects include chronic and temporary anti-predator behaviours, the nature of which depends on the spatial dynamics of predators and the range over which prey perceive risk. The relation between chronic and ephemeral responses to risk determines predator-prey interactions, with consequences that can ripple across the food web. Nonetheless, few studies have quantified the spatio-temporal scales over which prey respond to predation threat, and how this response varies with habitat features. We evaluated the reaction of radio-collared caribou and moose to the passage of radio-collared wolves, by considering changes in movement characteristics during winter and summer. We used an optimization algorithm to identify the rate at which the impact of prior passage of wolves decreases over time and with the predator's distance. The spatial and temporal scales of anti-predator responses varied with prey species and season. Caribou and moose displayed four types of behaviour following the passage of wolves: lack of response, increased selection of safe land cover types, decreased selection of risky cover types and increased selection of food-rich forest stands. For example, moose increased their avoidance of open conifer stands with lichen in summer, which are selected by wolves in this season. Also in winter, caribou increased their selection of conifer stands with lichen for nearly 10 days following a wolf's passage. This stronger selection for food-rich patches could indicate that the recent passage of wolves informs caribou on the current predator distribution and reveals the rate at which this information become less reliable over time. Caribou and moose used anti-predator responses that combine both long- and short-term behavioural adjustments. The spatial game between wolves and their prey involves complex and nonlinear mechanisms that vary between species and seasons. A comprehensive assessment of risk effects on ecosystem dynamics thus requires the characterization of chronic and temporary anti-predator behaviours.

Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing.

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.

"Price-quakes" shaking the world's stock exchanges.

BACKGROUND: Systemic risk has received much more awareness after the excessive risk taking by major financial instituations pushed the world's financial system into what many considered a state of near systemic failure in 2008. The IMF for example in its yearly 2009 Global Financial Stability Report acknowledged the lack of proper tools and research on the topic. Understanding how disruptions can propagate across financial markets is therefore of utmost importance. METHODOLOGY/PRINCIPAL FINDINGS: Here, we use empirical data to show that the world's markets have a non-linear threshold response to events, consistent with the hypothesis that traders exhibit change blindness. Change blindness is the tendency of humans to ignore small changes and to react disproportionately to large events. As we show, this may be responsible for generating cascading events--pricequakes--in the world's markets. We propose a network model of the world's stock exchanges that predicts how an individual stock exchange should be priced in terms of the performance of the global market of exchanges, but with change blindness included in the pricing. The model has a direct correspondence to models of earth tectonic plate movements developed in physics to describe the slip-stick movement of blocks linked via spring forces. CONCLUSIONS/SIGNIFICANCE: We have shown how the price dynamics of the world's stock exchanges follows a dynamics of build-up and release of stress, similar to earthquakes. The nonlinear response allows us to classify price movements of a given stock index as either being generated internally, due to specific economic news for the country in question, or externally, by the ensemble of the world's stock exchanges reacting together like a complex system. The model may provide new insight into the origins and thereby also prevent systemic risks in the global financial network.

Positive interactions and the emergence of community structure in metacommunities.

The significant role of space in maintaining species coexistence and determining community structure and function is well established. However, community ecology studies have mainly focused on simple competition and predation systems, and the relative impact of positive interspecific interactions in shaping communities in a spatial context is not well understood. Here we employ a spatially explicit metacommunity model to investigate the effect of local dispersal on the structure and function of communities in which species are linked through an interaction web comprising mutualism, competition and exploitation. Our results show that function, diversity and interspecific interactions of locally linked communities undergo a phase transition with changes in the rate of species dispersal. We find that low spatial interconnectedness favors the spontaneous emergence of strongly mutualistic communities which are more stable but less productive and diverse. On the other hand, high spatial interconnectedness promotes local biodiversity at the expense of local stability and supports communities with a wide range of interspecific interactions. We argue that investigations of the relationship between spatial processes and the self-organization of complex interaction webs are critical to understanding the geographic structure of interactions in real landscapes.

Examining the potential effects of species aggregation on the network structure of food webs.

One of the key measures that have been used to describe the topological properties of complex networks is the "degree distribution", which is a measure that describes the frequency distribution of number of links per node. Food webs are complex ecological networks that describe the trophic relationships among species in a community, and the topological properties of empirical food webs, including degree distributions, have been examined previously. Previously, the "niche model" has been shown to accurately predict degree distributions of empirical food webs, however, the niche model-generated food webs were referenced against empirical food webs that had their species grouped together based on their taxonomic and/or trophic relationships (aggregated food webs). Here, we explore the effects of species aggregation on the ability of the niche model to predict the total- (sum of prey and predator links per node), in- (number of predator links per node), and out- (number of prey links per node) degree distributions of empirical food webs by examining two food webs that can be aggregated at different levels of resolution. The results showed that (1) the cumulative total- and out-degree distributions were consistent with the niche model predictions when the species were aggregated, (2) when the species were disaggregated (i.e., higher resolution), there were mixed conclusions with regards to the niche model's ability to predict total- and out-degree distributions, (3) the model's ability to predict the in-degree distributions of the two food webs was generally inadequate. Although it has been argued that universal functional form based on the niche model could describe the degree distribution patterns of empirical food webs, we believe there are some limitations to the model's ability to accurately predict the structural properties of food webs.