Identifying landscape scale patterns from individual scale processes

Extrapolating across scales is a critical problem in ecology. Explicit mechanistic models of ecological systems provide a bridge from measurements of processes at small and short scales to larger scales; spatial patterns at large scales can be used to test the outcomes of these models. However, it is necessary to identify patterns that are not dependent on initial conditions, because small scale initial conditions will not normally be measured at large scales. We examined one possible pattern that could meet these conditions, the relationship between mean and variance in abundance of a parasitic tick in an individual based model of a lizard tick interaction. We scaled discrepancies between the observed and simulated patterns with a transformation of the variance–covariance matrix of the observed pattern to objectively identify patterns that are “close”.     

Modelling directional spatial processes in ecological data

Distributions of species, animals or plants, terrestrial or aquatic, are influenced by numerous factors such as physical and biogeographical gradients. Dominant wind and current directions cause the appearance of gradients in physical conditions whereas biogeographical gradients can be the result of historical events (e.g. glaciations). No spatial modelling technique has been developed to this day that considers the direction of an asymmetric process controlling species distributions along a gradient or network. This paper presents a new method that can model species spatial distributions generated by a hypothesized asymmetric, directional physical process. This method is an eigenfunction-based spatial filtering technique that offers as much flexibility as the Moran's eigenvector maps (MEM) framework; it is called asymmetric eigenvector maps (AEM) modelling. Information needed to construct eigenfunctions through the AEM framework are the spatial coordinates of the sampling or experimental sites, a connexion diagram linking the sites to one another, prior information about the direction of the hypothesized asymmetric process influencing the response variable(s), and optionally, weights attached to the edges (links). To illustrate how this new method works, AEM is compared to MEM analysis through simulations and in the analysis of an ecological example where a known asymmetric forcing is present. The ecological example reanalyses the dietary habits of brook trout (Salvelinus fontinalis) sampled in 42 lakes of the Mastigouche Reserve, Québec.     

Grassy field margins as potential corridors for butterflies in agricultural landscapes: A simulation study

Over the last decades, agricultural intensification has caused a dramatic reduction of grassy habitats. This habitat loss has had a strong negative effect on many meadow-living insect populations, including butterflies. As a part of the cross-compliance measures of the Common Agricultural Policy of the European Union, subsidies for creation and maintenance of grassy field margins (GFM) have been launched. Among other environmental issues, they may serve as corridors for movement of various meadow-living species between individual meadows. Their role as corridors has, however, not yet been demonstrated at the landscape scale and their characteristics that most significantly increase landscape connectivity are unknown. Empirical data for such studies are missing, as the GFM subsidies were launched only 3 years ago. One possibility to get some predictions of their outcomes is provided by simulation models. Here we present our simulation results, using an extension of the model developed by Kindlmann et al. (2004) for the Meadow Brown butterfly, Maniola jurtina. The extension includes the probability to cross a boundary (Conradt and Roper, 2006) that negatively influences dispersal rates but increases sensitivity to the corridor effect. Our simulations show that GFMs increase the dispersal rates between habitat patches and we predict the optimal combinations of width and number of GFMs in the landscape. This way we provide a decision-making tool for increasing landscape connectivity for M. jurtina and similar species. Although our simulations are based on a particular species, they may be generalized because this species shows dispersal rates that are typical of butterfly metapopulations (Conradt et al., 2000), and a potentially widespread dispersal kernel (i.e. “foray search”) that has been reported in a wide variety of species (see Conradt et al., 2003 for a review).     

GIS-based modeling of the geographic distribution of Quercus emoryi Torr. (Fagaceae) in México and identification of significant environmental factors influencing the species’ distribution

The greatest concentration of oak species in the world is believed to be found in Mexico. These species are potentially useful for reforestation because of their capacity to adapt to diverse environments. Knowledge of their geographic distribution and of species–environment relations is essential for decision-making in the management and conservation of natural resources. The objectives of this study were to develop a model of the distribution of Quercus emoryi Torr. in Mexico, using geographic information systems and data layers of climatic and other variables, and to determine the variables that significantly influence the distribution of the species. The study consisted of the following steps: (A) selection of the target species from a botanical scientific collection, (B) characterization of the collecting sites using images with values or categories of the variables, (C) model building with the overlay of images that meet the habitat conditions determined from the characterization of sites, (D) model validation with independent data in order to determine the precision of the model, (E) model calibration through adjustment of the intervals of some variables, and (F) sensitivity analysis using precision and concordance non-parametric statistics applied to pairs of images. Results show that the intervals of the variables that best describe the species’ habitat are the following: altitude from 1650 to 2750 amsl, slope from 0 to 66°; average minimum temperature of January from −12 to −3 °C; mean temperature of June from 11 to 25 °C; mean annual precipitation from 218 to 1225 mm; soil units: lithosol, eutric cambisol, haplic phaeozem, chromic luvisol, rendzina, luvic xerosol, mollic planosol, pellic vertisol, eutric regosol; type of vegetation: oak forest, oak–pine forest, pine forest, pine–oak forest, juniperus forest, low open forest, natural grassland and chaparral. The resulting model of the geographic distribution of Quercus emoryi in Mexico had the following values for non-parametric statistics of precision and agreement: Kappa index of 0.613 and 0.788, overall accuracy of 0.806 and 0.894, sensitivity of 0.650 and 0.825, specificity of 0.963, positive predictive value of 0.945 and 0.957 and negative predictive value of 0.733 and 0.846. Results indicate that the variable average minimum temperature of January, with a maximum value of −3 °C, is an important factor in limiting the species’ distribution.     

Establishment patterns in a secondary tree line ecotone

On semi-open pre-alpine fen pastures Alder encroachment creates a dynamic mosaic of grassland and woodland, which is rich in ecotones from fen to Carr. The structural diversity in colonisation patterns of Alder on fens suggests a dependency on multiple environmental drivers. Unidirectional progressive ecotone development provides an opportunity to address a current deficit in understanding successional patterns, i.e. process-pattern relationships in a multiple factor regime.We developed an individual-based model of Alder establishment on fen grassland to investigate the dependency of encroachment patterns upon seed production, dispersal distances and safe site availability. The purpose of the model is to provide a causal understanding of establishment patterns of Alder. In the model, all life processes of Alder individuals were parameterised with field data. This allowed us to strictly perform bottom-up simulations and successfully check plausibility by comparing simulated establishment patterns of cohorts with observed ecotone structures.Simulation results show that establishment patterns strongly depend on environmental drivers. Spatial progression of Alder encroachment and width of ecotones, respectively, mainly depend on wind speed during seed dispersal. Dense establishment of Alder leading to community change from fen grassland to Carr, requires windows of opportunity, which are defined by the rare coincidence of widespread dispersal, high seed production and favorable establishment conditions. Life-history traits of Alder (mast year cycle, high seed weight, weak establishment in fen) spatially and temporarily constrain the encroachment process. The structural diversity of long-term encroachment patterns is explained by the event-driven character of encroachment.Modelling individual establishment pathways of seedlings starting from germination revealed an endogenous stochasticity in establishment patterns emerging from low seed densities in the tail of the dispersal function. We conclude an inherent stochastic structure of dispersal-limited tree line ecotones, which limits reconstruction of processes from patterns.In order to describe long-term successional patterns of Alder encroachment at landscape scale, we propose the combination of two concepts: deterministic “patch-movement” of Alder woodland driven by continuous ecotone migration together with rare and stochastic “infiltration” of single Alder trees into open fen grasslands. Conservation management can control predictable “patch-movement” by cutting off maturing saplings around existing Alder woods. But the preservation of the actual large proportion of open grassland in fen pastures from infiltrating Alder seedlings and from the subsequent shift of the pasture to a densely wooded state would require mowing additionally to extensive grazing.     

Modelling the spatial population dynamics of the green oak leaf roller (Tortrix viridana) using density dependent competitive interactions: Effects of herbivore mortality and varying host-plant quality

Cyclic population dynamics of forest insects with periods of more than two generations have been discussed in relation to a variety of extrinsic and intrinsic forces. In the present study, we employed the selection pressure of density dependent competitive interactions according to Witting's equations (Witting, 2000) as driver for a discrete spatiotemporal model of the green oak leaf roller (Tortrix viridana). The model was successfully parameterised to rebuild the cyclic population dynamics of an empirical data set of a 30-year leaf roller monitoring in Russia. Our analysis focussed on the role of herbivore mortality and host plant food quality, which have a significant effect on T. viridana population dynamics. An additional egg or larvae mortality lowers population density and can lead to selection pressures that favour individuals with higher growth rate. This increased population growth rate can not only compensate the additional mortality, but also can lead to higher average moth abundances in subsequent generations. Furthermore, we analysed the effect of inter- and intraspecific variation in host plant quality on herbivore population dynamics and the spatial distribution of abundance and defoliation patterns. We found significant effects of the qualitative composition of a trees neighbourhood on the herbivore population of the respective tree. Also, the patchy damage patterns observable in reality have been reproduced by the present model. The applicability of the model approach and the putative genetic processes underlying Witting's model are discussed.     

Modeling the role of macroalgae in a shallow sub-estuary of Narragansett Bay, RI (USA)

Proliferation of macroalgal mats is a frequent consequence of nutrient-driven eutrophication in shallow, photic coastal marine ecosystems. These macroalgae have the potential to significantly modify water quality, plankton productivity, nutrient cycling, and dissolved oxygen dynamics. We developed a model for Ulva lactuca and Gracilaria tikvahiae in Greenwich Bay, RI (USA), a shallow sub-estuary of Narragansett Bay, as part of a larger estuarine ecosystem model. The model predicts the biomass of both species in units of carbon, nitrogen, and phosphorus as a function of primary production, respiration, grazing, decay, and physical exchange, with particular attention to the effects of biomass layering on light attenuation and suppression of metabolic rates. The model successfully reproduced the magnitude and seasonal cycle of area-weighted and peak biomass in Greenwich Bay along with tissue C:N ratios, and highlighted the importance of grazing and inclusion of self-limitation primarily in the form of self-shading to overcome an order of magnitude difference in rates of production and respiration. Inclusion of luxury nutrient uptake demonstrated the importance of internal nutrient storage in fueling production when nutrients are limiting. Macroalgae were predicted to contribute a small fraction of total system primary production and their removal had little effect on predicted water quality. Despite a lack of data for calibration and a fair amount of sensitivity to individual parameter values, which highlights the need for further autecological studies to constrain formulations, the model successfully predicted macroalgal biomass dynamics and their role in ecosystem functioning. Our formulations should be exportable to other temperate systems where macroalgae occur in abundance.     

A pattern-oriented modelling approach to simulating populations of grey partridge

A number of wildlife species including the grey partridge (Perdix perdix) have shown dramatic post-war population declines. Multiple drivers have been proposed as reasons for the declines, for example agrochemical use and intensification of agricultural practices, climate, predation, and changes in landscape structure. These drivers may interact in non-linear ways and are inherently spatio-temporal in nature. Therefore models used to investigate mechanisms should be spatio-temporal, of proper scale, and have a high degree of biological realism. Here we describe the development and testing of an agent-based model (ABM) of grey partridge using a well documented pre-decline historical data set in conjunction with a pattern-oriented modelling (POM) approach. Model development was an iterative process of defining performance criteria, testing model behaviour, and reformulating as necessary to emulate system properties whilst ensuring that internal mechanisms were biologically realistic. The model was documented using ODdox, a new protocol for describing large agent-based models. Parameter fitting in the model was achieved to within ±2% accuracy for 15 out of 17 field data patterns used, and within 5% for the remaining two. Tests of interactions between input parameters showed that 62% of parameter pairs tested had significant interactions underlining the complex nature of the model structure. Sensitivity analysis identified chick mortality as being the most sensitive factor, followed by adult losses to hunting and adult overwinter mortality, agreeing in general with previous partridge models. However, the ABM used here could separate individual drivers, providing a better understanding of the underlying mechanisms behind population regulation, and allowing factors to be compared directly. The ABM used is rich in output signals allowing detailed testing and refinement of the model. This approach is particularly suited to systems such as the partridge system where data for comparison to model outputs is readily available. Despite the accurate fit between historical data and model output, making use of the predictive power of the approach the model requires further calibration and testing under modern field conditions.     

Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.     

Ecological relevance of performance criteria for species distribution models

Species distribution models have often been developed based on ecological data. To develop reliable data-driven models, however, a sound model training and evaluation procedures are needed. A crucial step in these procedures is the assessment of the model performance, with as key component the applied performance criterion. Therefore, we reviewed seven performance criteria commonly applied in presence-absence modelling (the correctly classified instances, Kappa, sensitivity, specificity, the normalised mutual information statistic, the true skill statistic and the odds ratio) and analysed their application in both the model training and evaluation process. Although estimates of predictive performance have been used widely to assess final model quality, a systematic overview was missing because most analyses of performance criteria have been empirical and only focused on specific aspects of the performance criteria. This paper provides such an overview showing that different performance criteria evaluate a model differently and that this difference may be explained by the dependency of these criteria on the prevalence of the validation set. We showed theoretically that these prevalence effects only occur if the data are inseparable by an n-dimensional hyperplane, n being the number of input variables. Given this inseparability, different performance criteria focus on different aspects of model performance during model training, such as sensitivity, specificity or predictive accuracy. These findings have important consequences for ecological modelling because ecological data are mostly inseparable due to data noise and the complexity of the studied system. Consequently, it should be very clear which aspect of the model performance is evaluated, and models should be evaluated consistently, that is, independent of, or taking into account, species prevalence. The practical implications of these findings are clear. They provide further insight into the evaluation of ecological presence/absence models and attempt to assist modellers in their choice of suitable performance criteria.     

Assessing competition between Steller sea lions and the commercial groundfishery in Alaska: A bioenergetics modelling approach

In the last three decades the western stock of the Steller sea lion (Eumetopias jubatus) has declined by more than 85%. Nutritional stress resulting in increased juvenile mortality is one of the leading hypotheses to account for this decline. Competition between Steller sea lions and the commercial groundfishery for walleye pollock (Theragra chalcogramma) has been proposed as a mechanism underlying the nutritional stress. In order to examine the competition component of the nutritional stress hypothesis, we developed a bioenergetics-based model to project the population trends of Steller sea lions under various scenarios of continued groundfish harvest. Annual energy budgets were calculated for the Gulf of Alaska population of Steller sea lions, and compared with projected available energy from walleye pollock under a variety of harvest scenarios. Model simulations produced 50-year Steller sea lion population projections consistent with current trends, as well as with published projections for stable and increasing populations from stable age distribution life table models. Model simulations were unable to produce energy deficits sufficient to account for the decline in Steller sea lions, but do suggest areas where existing data need supplementing.     

Modeling amphibian energetics, habitat suitability, and movements of western toads, Anaxyrus (=Bufo) boreas, across present and future landscapes

Effective conservation of amphibian populations requires the prediction of how amphibians use and move through a landscape. Amphibians are closely coupled to their physical environment. Thus an approach that uses the physiological attributes of amphibians, together with knowledge of their natural history, should be helpful. We used Niche Mapper™ to model the known movements and habitat use patterns of a population of Western toads (Anaxyrus (=Bufo) boreas) occupying forested habitats in southeastern Idaho. Niche Mapper uses first principles of environmental biophysics to combine features of topography, climate, land cover, and animal features to model microclimates and animal physiology and behavior across landscapes. Niche Mapper reproduced core body temperatures (T_c) and evaporation rates of live toads with average errors of 1.6 ± 0.4 °C and 0.8 ± 0.2 g/h, respectively. For four different habitat types, it reproduced similar mid-summer daily temperature patterns as those measured in the field and calculated evaporation rates (g/h) with an average error rate of 7.2 ± 5.5%. Sensitivity analyses indicate these errors do not significantly affect estimates of food consumption or activity. Using Niche Mapper we predicted the daily habitats used by free-ranging toads; our accuracy for female toads was greater than for male toads (74.2 ± 6.8% and 53.6 ± 15.8%, respectively), reflecting the stronger patterns of habitat selection among females. Using these changing to construct a cost surface, we also reconstructed movement paths that were consistent with field observations. The effect of climate warming on toads depends on the interaction of temperature and atmospheric moisture. If climate change occurs as predicted, results from Niche Mapper suggests that climate warming will increase the physiological cost of landscapes thereby limiting the activity for toads in different habitats.     

Modelling habitat overlap among sympatric mesocarnivores in southern Illinois,USA

Few researchers have developed large-scale habitat models for sympatric carnivore species. We created habitat models for red foxes (Vulpes vulpes), coyotes (Canis latrans) and bobcats (Lynx rufus) in southern Illinois, USA, using the Penrose distance statistic, remotely sensed landscape data, and sighting location data within a GIS. Our objectives were to quantify and spatially model potential habitat differences among species. Habitat variables were quantified for 1-km² buffered areas around mesocarnivore sighting locations. Following variable reduction procedures, five habitat variables (percentage of grassland patches, interspersion–juxtaposition of forest patches, mean fractal dimension of wetland patches and the landscape, and road density) were used for analysis. Only one variable differed (P < 0.05) between red fox and coyote sighting areas (road density) and bobcat and coyote sighting areas (mean fractal dimension of the landscape). However, all five variables differed between red fox and bobcat sighting areas, indicating considerable differences in habitat affiliation between this pair-group. Compared to bobcats, red fox sightings were affiliated with more grassland cover and larger grassland patches, higher road densities, lower interspersion and juxtaposition of forest patches, and lower mean fractal dimension of wetland patches. These differences can be explained by different life history requirements relative to specific cover types. We then used the Penrose distance statistic to create habitat models for red foxes and bobcats, respectively, based on the five-variable dataset. An independent set of sighting locations were used to validate these models; model fit was good with 65% of mesocarnivore locations within the top 50% of Penrose distance values. In general, red foxes were affiliated with mixtures of agricultural and grassland cover, whereas bobcats were associated with a combination of grassland, wetland, and forest cover. The greatest habitat overlap between red foxes and bobcats was found at the interface between forested areas and more open cover types. Our study provides insight into habitat overlap among sympatric mesocarnivores, and the distance-based modelling approach we used has numerous applications for modelling wildlife–habitat relationships over large scales.     

Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (Athene cunicularia hypugaea) as a case study

We describe an ecotoxicological model that simulates the sublethal and lethal effects of chronic, low-level, chemical exposure on birds wintering in agricultural landscapes. Previous models estimating the impact on wildlife of chemicals used in agro-ecosystems typically have not included the variety of pathways, including both dermal and oral, by which individuals are exposed. The present model contains four submodels simulating (1) foraging behavior of individual birds, (2) chemical applications to crops, (3) transfers of chemicals among soil, insects, and small mammals, and (4) transfers of chemicals to birds via ingestion and dermal exposure. We demonstrate use of the model by simulating the impacts of a variety of commonly used herbicides, insecticides, growth regulators, and defoliants on western burrowing owls (Athene cunicularia hypugaea) that winter in agricultural landscapes in southern Texas, United States. The model generated reasonable movement patterns for each chemical through soil, water, insects, and rodents, as well as into the owl via consumption and dermal absorption. Sensitivity analysis suggested model predictions were sensitive to uncertainty associated with estimates of chemical half-lives in birds, soil, and prey, sensitive to parameters associated with estimating dermal exposure, and relatively insensitive to uncertainty associated with details of chemical application procedures (timing of application, amount of drift). Nonetheless, the general trends in chemical accumulations and the relative impacts of the various chemicals were robust to these parameter changes. Simulation results suggested that insecticides posed a greater potential risk to owls of both sublethal and lethal effects than do herbicides, defoliants, and growth regulators under crop scenarios typical of southern Texas, and that use of multiple indicators, or endpoints provided a more accurate assessment of risk due to agricultural chemical exposure. The model should prove useful in helping prioritize the chemicals and transfer pathways targeted in future studies and also, as these new data become available, in assessing the relative danger to other birds of exposure to different types of agricultural chemicals.     

Neutral modelling of agricultural landscapes by tessellation methods—Application for gene flow simulation

Neutral landscape models are not frequently used in the agronomical domain, whereas they would be very useful for studying given agro-ecological or physical processes. Contrary to ecological neutral landscape models, agricultural models have to represent and manage geometrical patches and thus should rely on tessellation methods. We present a three steps approach that aimed at simulating such landscapes. Firstly, we characterized the geometry of three real field patterns; secondly, we generated simulated field patterns with two tessellation methods attempting to control the value of some of the observed characteristics and, thirdly, we evaluated the simulated field patterns. For this evaluation, we considered that good simulated field patterns should capture characteristics of real landscapes that are important for the targeted agro-ecological process. Real landscapes and landscapes simulated using either a Voronoi or a rectangular tessellation were thus compared when used as input data within a gene flow model. The results showed that neither tessellation method captured field shapes correctly, thus leading to over or (small) under estimation of gene flow. The Voronoi tessellation, though, performed better than the rectangular tessellation. Possible research directions are proposed to improve the simulated patterns, including the use of post-processing, the control of cell orientation or the implementation of other tessellation techniques.     

Simulating regeneration and vegetation dynamics in Mediterranean coniferous forests

This study aims to provide a quantitative framework to model the dynamics of Mediterranean coniferous forests by integrating existing ecological data within a generic mathematical simulator. We developed an individual-based vegetation dynamics model, constrained on long-term field regeneration data, analyses of tree-rings and seed germination experiments. The simulator implements an asymmetric competition algorithm which is based on the location and size of each individual. Growth is parameterized through the analysis of tree-rings from more than thirty individuals of each of the three species of interest. A super-individual approach is implemented to simulate regeneration dynamics, constrained with available regeneration data across time-since-disturbance and light-availability gradients. The study concerns an insular population of an endemic to Greece Mediterranean fir (Abies cephalonica Loudon) on the island of Cephalonia (Ionian Sea) and two interacting populations of a Mediterranean pine (Pinus brutia Ten.) and a more temperate-oriented pine (Pinus nigra Arn. ssp. pallasiana) on the island of Lesbos (NE Aegean Sea), Greece. The model was validated against plot-level observations in terms of species standing biomass and regeneration vigour and adequately captured regeneration patterns and overall vegetation dynamics in both study sites. The potential effects of changing climatic patterns on the regeneration dynamics of the three species of interest were subsequently explored. With the assumption that a warmer future would probably cause changes in the duration of cold days, we tested how this change would affect the overall dynamics of the study sites, by focusing on the process of cold stratification upon seed germination. Following scenarios of a warmer future and under the current model parameterization, changes in the overall regeneration vigour controlled by a reduction in the amount of cold days, did not alter the overall dynamics in all plant populations studied. No changes were identified in the relative dominance of the interacting pine populations on Lesbos, while the observed reduction in the amount of emerging seedlings of A. cephalonica on Cephalonia did not affect biomass yield at later stages of stand development.     

Modelling the responses of wildlife to human disturbance: An evaluation of alternative management scenarios for black-crowned night-herons

The impact of anthropogenic disturbance on wildlife is increasing becoming a source of concern as the popularity of outdoor recreation rises. There is now more pressure on site managers to simultaneously ensure the continued persistence of wildlife and provide recreational opportunities. Using ‘Simulation of Disturbance Activities’, a model designed to investigate the impact of recreational disturbance on wildlife, we demonstrate how a simulation modelling approach can effectively inform such management decisions. As an example, we explored the implications of various design and management options for a proposed recreational area containing a historic breeding bird colony. By manipulating the proximity, orientation and intensity of recreation, we were able to evaluate the impact of recreational activities on the behaviour of black-crowned night-heron nestlings (Nycticorax nycticorax). Using a classification and regression tree (CART) procedure to analyse simulation output, we explored the dynamics of multiple strategies in concert. Our analysis revealed that there are inherent advantages in implementing multiple strategies as opposed to any single strategy. Nestlings were not disturbed by recreation when bird-watching facility placement (proximity and orientation) and type were considered in combination. In comparison, proximity alone only led to a <10% reduction in disturbance. Thus we demonstrate how simulation models based on customised empirical data can bridge the gap between field studies and active management, enabling users to test novel management scenarios that are otherwise logistically difficult. Furthermore, such models potentially have broad application in understanding human-wildlife interactions (e.g. exploring the implications of roads on wildlife, probability of bird strikes around airports, etc.). They therefore represent a valuable decision-making tool in the ecological design of urban infrastructures.     

Individual-based modeling of flooding and salinity effects on a coastal swamp forest

Coastal swamps are among the rapidly vanishing wetland habitats in Louisiana. Increased flooding, nutrient and sediment deprivation, and salt-water intrusion have been implicated as probable causes of the decline of coastal swamps. We developed a two-species individual-based forest succession model to compare the growth and composition of a cypress-tupelo swamp under various combinations of flooding intensity and salinity levels, using historical time-series of stage and salinity data as inputs. Our model simulates forest succession over 500 years by representing the growth, mortality, and reproduction of individual Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) trees in a 1-km² spatial grid of 10 m × 10 m cells that vary in water levels and salinity through differences in elevation. We independently adjusted the elevations of each cell to obtain different grid-wide mean elevations and standard deviations of elevation; this affected the temporal and spatial pattern of flooding. We calibrated the model by adjusting selected parameters until averaged basal area, stem density and wood production rates under two different mean elevations (partially versus highly flooded) were qualitatively similar to comparable values reported for swamps in the literature. Corroboration involved comparing model predictions to four well-monitored contrasting habitat sites within the Maurepas Basin, Louisiana, USA. Model predictions of both species combined showed the same patterns among sites as the data, but the model overestimated wood production and the dominance of T. distichum. Exploratory simulations predicted that increased flooding leads to swamps with reduced basal areas and stem densities, while increased salinity resulted in lower basal areas at low salinity concentration (∼1-3 psu) and complete tree mortality at higher salinity concentrations (∼2-6 psu). Our model can provide insight into the succession dynamics of coastal swamps and information for the effective design of restoration actions.     

Simulating population variation and movement within fragmented landscapes: An application to the gopher tortoise (Gopherus polyphemus)

As the human activity footprint grows, land-use decisions play an increasing role in determining the future of plant and animal species. Studies have shown that urban and agricultural development cannot only harm species populations directly through habitat destruction, but also by destroying the corridors that connect habitat patches and populations within a metapopulation. Without these pathways, populations can encounter inbreeding depression and degeneration, which can increase death rates and lower rates of reproduction. This article describes the development and application of the FRAGGLE model, a spatial system dynamics model designed to calculate connectivity indices among populations. FRAGGLE can help planners and managers identify the relative contribution of populations associated with habitat patches to future populations in those patches, taking into account the importance of interstitial land to migration success. The model is applied to the gopher tortoise (Gopherus polyphemus), a threatened species whose southeastern U.S. distribution has diminished significantly within its native range due to agricultural and urban development over the last several decades. This model is parameterized with life history and movement traits of the gopher tortoise in order to simulate population demographics and spatial distribution within an area in west-central Georgia that supports a significant tortoise population. The implications of this simulation modeling effort are demonstrated using simple landscape representations and a hypothetical on land-use management scenario. Our findings show that development resulting in even limited habitat losses (10%) may lead to significant increases in fragmentation as measured by a loss in the rate of dispersions (31%) among area subpopulations.