Modeling the invasive emerald ash borer risk of spread using a spatially explicit cellular model

The emerald ash borer (EAB, Agrilus planipennis) is decimating native ashes (Fraxinus sp.) throughout midwestern North America, killing millions of trees over the years. With plenty of ash available throughout the continent, the spread of this destructive insect is likely to continue. We estimate that the insect has been moving along a “front” at about 20 km/year since about 1998, but more alarming is its long-range dispersal into new locations facilitated by human activities. We describe a spatially explicit cell-based model used to calculate risk of spread in Ohio, by combining the insect’s flight and short-range dispersal (“insect flight”) with human-facilitated, long-range dispersal (“insect ride”). This hybrid model requires estimates of EAB abundance, ash abundance, major roads and traffic density, campground size and usage, distance from the core infested zone, wood products industry size and type of wood usage, and human population density. With the “insect flight” model, probability of movement is dependent on EAB abundance in the source cells, the quantity of ash in the target cells, and the distances between them. With the “insect-ride” model, we modify the value related to ash abundance based on factors related to potential human-assisted movements of EAB-infested ash wood or just hitchhiking insects. We attempt to show the advantage of our model compared to statistical approaches and to justify its practical value to field managers working with imperfect knowledge. We stress the importance of the road network in distributing insects to new geographically dispersed sites in Ohio, where 84% were within 1 km of a major highway.     

Conservation planning with spatially explicit models: a case for horseshoe bats in complex mountain landscapes

Context

Context Bats are considered as an ecological indicator of habitat quality due to their sensitivity to human-induced ecosystem changes. Hence, we will focus the study on two indicator species of bats as a proxy to evaluate structure and composition of the landscape to analyze anthropic pressures driving changes in patterns.

Objectives

This study develops a spatially-explicit model to highlight key habitat nodes and corridors which are integral for maintaining functional landscape connectivity for bat movement. We focus on a complex mountain landscape and two bat species: greater (Rhinolophus ferrumequinum) and lesser (Rhinolophus hipposideros) horseshoe bats which are known to be sensitive to landscape composition and configuration.

Methods

Species distribution models are used to delineate high-quality foraging habitat for each species using opportunistic ultrasonic bat data. We then performed connectivity analysis combining (modelled) suitable foraging habitat and (known) roost sites. We use graph-theory and the deviation in the probability of connectivity to quantify resilience of the landscape connectivity to perturbations.

Results

Both species were confined to lowlands (<1000 m elevation) and avoided areas with high road densities. Greater horseshoe bats were more generalist than lesser horseshoe bats which tended to be associated with broadleaved and mixed forests.

Conclusions

The spatially-explicit models obtained were proven crucial for prioritizing foraging habitats, roost sites and key corridors for conservation. Hence, our results are being used by key stakeholders to help integrate conservation measures into forest management and conservation planning at the regional level. The approach used can be integrated into conservation initiatives elsewhere.

     

Graph theory as an invasive species management tool: case study in the Sonoran Desert

Context

Biodiversity in arid regions is usually concentrated around limited water resources, so natural resource managers have constructed artificial water catchments in many areas to supplement natural waters. Because invasive species may also use these waters, dispersing into previously inaccessible areas, the costs and benefits of artificial waters must be gauged and potential invasion- and climate change-management strategies assayed.

Objectives

We present a network analysis framework to identify waters that likely contribute to the spread of invasive species.

Methods

Using the Sonoran Desert waters network and the American bullfrog (Lithobates catesbeianus)—a known predator, competitor, and carrier of pathogens deadly to other amphibians—as an example, we quantified the structural connectivity of the network to predict regional invasion potential under current and two future scenarios (climate change and management reduction) to identify waters to manage and monitor for invasive species.

Results

We identified important and vulnerable waters based on connectivity metrics under scenarios representing current conditions, projected climate-limited conditions, and conditions based on removal of artificial waters. We identified 122,607 km² of land that could be used as a buffer against invasion and 67,745 km² of land that could be augmented by artificial water placement without facilitating invasive species spread.

Conclusions

Structural connectivity metrics can be used to evaluate alternative management strategies for invasive species and climate mitigation.

     

Modelling the impacts of agriculture in mixed-use landscapes: a review and case study involving two species of dabbling ducks

Context

This study synthesizes evidence from three separate surveys of American Black Duck and Mallard breeding habitat usage to quantify the effects of agriculture at the landscape scale.

Objectives

To assess duck breeding activity in agricultural landscapes within the Canadian maritimes in order to measure the overall impact of agricultural land use, the response to particular agricultural activities, and the influence of landscape configuration.

Methods

Models, constructed using a long-term census (SURVEY1), were used to predict habitat selection for two other independent surveys (SURVEY2, SURVEY3). Predictions incorporated information about wetland area and diversity, as well as anthropogenic factors, allowing subsequent analyses to focus on the remaining residual error attributable to agricultural effects.

Results

SURVEY2 results demonstrated that the proportion of active agriculture is an important indicator of the severity of human disturbance, yielding threshold estimates of 39% for Mallards and 60% for Black Ducks, with an overall average of 50%. Agricultural conversion beyond these thresholds deterred breeding ducks independently of other factors. SURVEY3 land cover information demonstrated that the presence of cropland intensified this deterrence effect, even at levels as low as 10%. Woodland cover (in excess of 30%) was important for both species, but its configuration was not.

Conclusions

In addition to quantifying threshold effects, this study reaffirms that woodland is an important part of the maritime landscape matrix, and contributes positively to habitat diversity in mixed use, moderate intensity agricultural regions. Wetland restoration in agricultural landscapes should monitor and promote less crop-intensive, mixed-use practices.

     

Landscape metrics as a framework to measure the effect of landscape structure on the spread of invasive insect species

Context

With accelerated land-use change throughout the world, increased understanding of the relative effects of landscape composition and configuration on biological system and bioinvasion in particular, is needed to design effective management strategies. However, this topic is poorly understood in part because empirical studies often fail to account for large gradients of habitat complexity and offer insufficient or even no replication across habitats.

Objectives

The aim of this study was to disentangle the independent and interactive effects of landscape composition and landscape configuration on the establishment and spread of invasive insect species.

Methods

We explore a spatially-explicit, mechanistic modeling framework that allows for systematic investigation of the impact of changes in landscape composition and landscape configuration on establishment and spread of invasive insect species. Landscape metrics are used as an indicators of invasive insect establishment and spread.

Results

We showed that the presence of an Allee effect leads to a balance between the effectiveness of spread and invasion success. Spread is maximized at an intermediate dispersal level and inhibited at both low and high levels of dispersal. The landscape, by either increasing or mitigating the dispersal abilities of a species, can lead to a rate of spread under a dispersal threshold for which density and spread is at the highest.

Conclusion

Our study proposes that change in landscape structure is an additional explanation of the highly variable spread dynamics observed in natural and anthropogenic landscapes. Consequently, a landscape-scale perspective could significantly improve spread risk assessment and the design of control or containment strategies.

     

Modeling configuration dynamics of harvested forest landscapes in the Canadian boreal plains

Habitat configuration has important implications for the persistence of faunal and floral populations at a variety of spatial scales. Forest harvesting alters habitat configurations. However, measuring and predicting such alterations remains challenging, in part because previously developed metrics of habitat configuration are often not statistically independent of habitat amount. Thus, their ability to measure independent effects of habitat configurations and habitat amount on ecosystem components such as wildlife populations has been limited. Here, we evaluate habitat configuration based on newly developed metrics that are independent of habitat amount but do not depend on regression residuals of abundance and configuration relationships on any population of landscapes. We use these new metrics to measure and predict changes in habitat configuration following forest harvesting in the boreal forest of Alberta, Canada. Our findings clearly demonstrate changes in habitat configuration resulting from forest harvesting can be predicted precisely with information about initial habitat patch structure and harvesting patterns. Because forest harvesting has significant implications for habitat configuration, accurately predicting these changes is critical for determining if forest harvesting strategies are sustainable for ecosystem components and processes. This study provides a set of novel, robust metrics for tracking landscape-scale changes in habitat configuration in harvested boreal forests.     

Landscape pattern in topographically complex landscapes: issues and techniques for analysis

Ecological research provides ample evidence that topography can exert a significant influence on the processes shaping broad-scale landscape vegetation patterns. Studies that ignore this influence run the risk of misinterpreting observations and making inappropriate recommendations to the management community. Unfortunately, the standard methods for landscape pattern analysis are not designed to include topography as a pattern-shaping factor. In this paper, we present a set of techniques designed to incorporate the topographic mosaic into analyses of landscape pattern and dynamics. This toolbox includes adjustments to classic landscape indices that account for non-uniform landscape topography, indices that capture associations and directionality in vegetation pattern due to topographic structure, and the application of statistical models to describe relationships between topographic characteristics and vegetation pattern. To illustrate these methods, we draw on examples from our own analysis of landscape pattern dynamics in logged and unlogged forest landscapes in southwestern British Columbia. These examples also serve to illustrate the importance of considering topography in both research and management applications.This revised version was published online in May 2005 with corrections to the Cover Date.     

Within-patch habitat quality determines the resilience of specialist species in fragmented landscapes

Patch geometry and habitat quality among patches are widely recognized as important factors affecting population dynamics in fragmented landscapes. Little is known, however, about the influence of within-patch habitat quality on population dynamics. In this paper, we investigate the relative importance of patch geometry and within-patch habitat quality in determining population dynamics using a spatially explicit, agent-based model. We simulate two mobile species that differ in their species traits: one resembles a habitat specialist and the other a habitat generalist. Habitat quality varies continuously within habitat patches in space (and time). The results show that spatial variation in within-patch quality, together with patch area, controls population abundance of the habitat specialist. In contrast, the population size of the generalist species depends on patch area and isolation. Temporal variation in within-patch quality is, however, less influential in driving the population resilience of both species. We conclude that specialist species are more sensitive than generalist species to within-patch variation in habitat quality. The patch area-isolation paradigm, developed in metapopulation theory, should incorporate variation in within-patch habitat quality, particularly for habitat specialists.     

Modeling spatial distribution of European badger in arid landscapes: an ecosystem functioning approach

Understanding the factors determining the spatial distribution of species is a major challenge in ecology and conservation. This study tests the use of ecosystem functioning variables, derived from satellite imagery data, to explore their potential use in modeling the distribution of the European badger in Mediterranean arid environments. We found that the performance of distribution models was enhanced by the inclusion of variables derived from the Enhanced Vegetation Index (EVI), such as mean EVI (a proxy for primary production), the coefficient of variation of mean EVI (an indicator of seasonality), and the standard deviation of mean EVI (representing spatial heterogeneity of primary production). We also found that distributions predicted by remote sensing data were consistent with the ecological preferences of badger in those environments, which may be explained by the link between EVI-derived variables and the spatial and temporal variability of food resource availability. In conclusion, we suggest the incorporation of variables associated with ecosystem function into species modeling exercises as a useful tool for improving decision-making related to wildlife conservation and management.     

Modeling seasonal dynamics of small fish cohorts in fluctuating freshwater marsh landscapes

Small-bodied fishes constitute an important assemblage in many wetlands. In wetlands that dry periodically except for small permanent waterbodies, these fishes are quick to respond to change and can undergo large fluctuations in numbers and biomasses. An important aspect of landscapes that are mixtures of marsh and permanent waterbodies is that high rates of biomass production occur in the marshes during flooding phases, while the permanent waterbodies serve as refuges for many biotic components during the dry phases. The temporal and spatial dynamics of the small fishes are ecologically important, as these fishes provide a crucial food base for higher trophic levels, such as wading birds. We develop a simple model that is analytically tractable, describing the main processes of the spatio-temporal dynamics of a population of small-bodied fish in a seasonal wetland environment, consisting of marsh and permanent waterbodies. The population expands into newly flooded areas during the wet season and contracts during declining water levels in the dry season. If the marsh dries completely during these times (a drydown), the fish need refuge in permanent waterbodies. At least three new and general conclusions arise from the model: (1) there is an optimal rate at which fish should expand into a newly flooding area to maximize population production; (2) there is also a fluctuation amplitude of water level that maximizes fish production, and (3) there is an upper limit on the number of fish that can reach a permanent waterbody during a drydown, no matter how large the marsh surface area is that drains into the waterbody. Because water levels can be manipulated in many wetlands, it is useful to have an understanding of the role of these fluctuations.     

Determinants of plant species richness and patterns of nestedness in fragmented landscapes: evidence from land-bridge islands

Land-bridge islands formed by dam construction are considered to be “experimental” systems for studying the effects of habitat loss and fragmentation, offering many distinct advantages over terrestrial fragments. The Thousand Island Lake in Southeast China is one such land-bridge system with more than 1000 islands. Based on a field survey of vascular plant richness on 154 land-bridge islands during 2007–2008, we examined the effects of island and landscape attributes on plant species richness and patterns of species nestedness. We also examined the different responses of plant functional groups (classified according to growth form and shade tolerance) to fragmentation. We found that island area explained the greatest amount of variation in plant species richness. Island area and shape index positively affected species diversity and the degree of nestedness exhibited by plant communities while the perimeter to area ratio of the islands had a negative effect. Shade-tolerant plants were the most sensitive species group to habitat fragmentation. Isolation negatively affected the degree of nestedness in herb and shade-intolerant plants including species with various dispersal abilities in the fragmented landscape. Based on these results, we concluded that the effects of habitat loss and fragmentation on overall species richness depended mostly on the degree of habitat loss, but patterns of nestedness were generated from different ecological mechanisms due to species-specific responses to different characteristics of habitat patches.     

Quantifying determinants contributing to plant species richness in mosaic landscapes: a single- and multi-patch perspective

Despite good theoretical knowledge about determinants of plant species richness in mosaic landscapes, validations based on complete surveys are scarce. We conducted a case study in a highly fragmented, traditional agricultural landscape. In 199 patches of 20 representative multi-patch-plots (MPPs, 1 ha) we recorded a total of 371 plant species. In addition to an additive partitioning of species diversity at the (a) patch- and (b) MPP-scale, we adopted the recently proposed ‘specificity’ measure to quantify the contribution of a spatial subunit to landscape species richness (subunit-to-landscape-contribution, SLC). SLC-values were calculated at both scales with respect to various spatial extents. General regression models were used to quantify the relative importance of hypothesis-driven determinants for species richness and SLC-values. At the patch scale, habitat type was the main determinant of species richness, followed by area and elongated shape. For SLC-values, area was more important than habitat type, and its relevance increased with the extent of the considered landscape. Influences of elongated shape and vegetation context were minor. Differences between habitat types were pronounced for species richness and also partly scale-dependent for SLC-values. Relevant predictors at the MPP-scale were nonlinear habitat richness, the gradient from anthropogenic to seminatural vegetation, and the proportions of natural vegetation and rare habitats. Linear elements and habitat configuration did not contribute to species richness and SLC. Results at the MPP-scale were in complete accordance with the predictions of the mosaic concept. Hence, our study represents its first empirical validation for plant species diversity in mosaic landscapes.     

Airborne multispectral imagery and deep learning for biosecurity surveillance of invasive forest pests in urban landscapes

Urban and peri-urban trees in major cities provide a gateway for exotic pests and diseases (hereafter “pests”) to establish and spread into new countries. Consequently, they can be used as sentinels for early detection of exotic pests that could threaten commercial, environmental and amenity forests. Biosecurity surveillance for exotic forest pests relies on monitoring of host trees — or sentinel trees — around high-risk sites, such as airports and seaports. There are few publicly available spatial databases of urban street and park trees, so locating and mapping host trees is conducted via ground surveys. This is time-consuming and resource-intensive, and generally does not provide complete coverage. Advances in remote sensing technologies and machine learning provide an opportunity for semi-automation of tree species mapping to assist in biosecurity surveillance. In this study, we obtained high resolution (≥12 cm), 10-band, multispectral imagery using the ArborCam™ system mounted to a fixed-wing aircraft over Sydney, Australia. We mapped 630 Pinus trees and 439 Platanus trees on-foot, validating their exact location on the airborne imagery using an in-field mapping app. Using a machine learning, convolutional neural network workflow, we were able to classify the two target genera with a high level of accuracy in a complex urban landscape. Overall accuracy was 92.1% for Pinus and 95.2% for Platanus, precision (user’s accuracy) ranged from 61.3% to 77.6%, sensitivity (producer’s accuracy) ranged from 92.7% to 95.2%, and F1-score ranged from 74.6% to 84.4%. Our study validates the potential for using multispectral imagery and machine learning to increase efficiencies in tree biosecurity surveillance. We encourage biosecurity agencies to consider greater use of this technology.     

High-elevation landforms limit the movement of invasive small mammal species

Landscape Ecology - Large-scale programs for eradication of pest mammals are confronted with the challenge of managing reinvasion. Exploiting high-elevation landscape features that naturally limit...     

Separating the effects of habitat area,fragmentation and matrix resistance on genetic differentiation in complex landscapes

Little is known about how variation in landscape mosaics affects genetic differentiation. The goal of this paper is to quantify the relative importance of habitat area and configuration, as well as the contrast in resistance between habitat and non-habitat, on genetic differentiation. We hypothesized that habitat configuration would be more influential than habitat area in influencing genetic differentiation. Population size is positively related to habitat area, and therefore habitat area should affect genetic drift, but not gene flow. In contrast, differential rates and patterns of gene flow across a landscape should be related to habitat configuration. Using spatially explicit, individual-based simulation modeling, we found that habitat configuration had stronger relationships with genetic differentiation than did habitat area, but there was a high degree of confounding between the effects of habitat area and configuration. We evaluated the predictive ability of six widely used landscape metrics and found that patch cohesion and correlation length of habitat are among the strongest individual predictors of genetic differentiation. Correlation length, patch density and clumpy are the most parsimonious set of variables to predict the magnitude of genetic differentiation in complex landscapes.     

Modeling multiscale effects of light limitations and edge-induced mortality on carbon stores in forest landscapes

Analyses of carbon (C) dynamics at broad scales usually do not consider spatial interactions. The assumption is that C dynamics can be modeled within homogenous (i.e., even-aged) patches and then summed to predict broad-scale dynamics (an additive approach). The goal of this paper is to elucidate the scales over which this additive approach is sufficient to explain observed C dynamics at broad scales. We define emergent behaviors (vs. emergent properties) as those behaviors that cannot be predicted solely from the additive properties of units at a finer scale. We used a forest process model to check for possible emergent behaviors due to pattern-process interactions at multiple levels, from the patch to the landscape. Specifically, using artificial forest landscapes with various spatial structures, we estimated the relative effects of edge-induced, tree mortality (mainly due to wind) and light limitations on C dynamics. Emergent behaviors were observed at all levels examined, indicating that emergent behaviors did not cease as one proceeded from the patch to the landscape level, as we had expected. However, the magnitude of the emergent behaviors depended on the level of spatial interaction considered as well as the type and intensity of the processes included. In all simulations, interactions of light and wind processes resulted in significant emergent behaviors only when parameters controlling wind mortality were set to the highest levels observed in the literature. In one simulation, the magnitude of emergent behaviors differed among the landscapes, indicating that interactions among patches may not be accounted for by an additive correction for edge effects unless spatial interactions are addressed. The implication is that some C dynamics in fragmented landscapes may not be captured at broad-scales using an additive approach, whereas in other cases spatial interactions are small enough to be ignored.This revised version was published online in May 2005 with corrections to the Cover Date.     

Hierarchical factors impacting the distribution of an invasive species: landscape context and propagule pressure

Distribution of invasive species is the outcome of several processes that interact at different hierarchical levels. A hierarchical approach is taken here to analyze the landscape level distribution pattern of Purple loosestrife (Lythrum salicaria), an aggressive wetland invader. Using land use/land cover (LULC) data and loosestrife presence records we were able to identify and characterize the key processes that resulted in the observed large-scale distribution. Herbaceous wetlands, edges of open water sites, and developed open spaces were identified as loosestrife’s preferred LULC types. Analysis of spatial neighborhoods of these key land cover types revealed that disturbance modified open water edges and herbaceous wetlands were more likely to be invaded by loosestrife. Moreover, developed open spaces appear to hold loosestrife only if there is water rich conditions in the immediate neighborhood. Neighborhood analyses also showed that wetlands and open water edges embedded within a neighborhood matrix of grassland and agricultural environments is less likely to contain loosestrife. Finally, there is strong evidence of propagule pressure. Open water edges and wetlands invaded by loosestrife had on an average more loosestrife as neighbors than uninvaded lake edges and wetlands. Taken together, it is apparent that loosestrife’s landscape level distribution is the outcome of three nested hierarchical factors: habitat preference, the spatial neighborhood and propagule pressure. The patterns characterized suggests that occurrence of an invasive species is not merely contingent on availability of suitable habitat but is also influenced by human actions within its proximity, and is further constrained by dispersal limitation.