Context

A challenge devising revegetation strategies in fragmented landscapes is conserving for the widest spectrum of biodiversity. Habitat network reconstruction should improve landscape capacity to maintain species populations. However, the location of revegetation often fails to account for species occurrence and dispersal processes operating across spatial scales.

Objectives

Our objective was to integrate metapopulation theory with estimates of landscape capacity and dispersal pathways to highlight connectivity gaps. Maintenance of populations could thereby be facilitated through reconnecting habitat networks across regional and broader scales, with assumed benefit for the dispersal needs of less sensitive species.

Methods

Predicted occupancy and metapopulation capacity were calculated for a generic focal species derived from fragmentation-sensitive woodland birds, mammals and reptiles. A metapopulation connectivity analysis predicted regional dispersal links to identify likely routes through which individuals may move to contribute to the viability of the population. We used the revegetation programmes of the Brigalow–Nandewar Biolinks project, eastern New South Wales, Australia, to demonstrate our approach.

Results

Landscape capacity of the current landscape varied across the region. Low-value links between populations provided greatest opportunities for revegetation and improved landscape capacity. Where regional connectivity did not indicate a pathway between populations, broader scale connectivity provided guidance for revegetation.

Conclusions

The metapopulation-based model, coupled with a habitat dispersal network analysis, provided a platform to inform revegetation locations and better support biodiversity. Our approach has application for directing on-ground action to support viable populations, assess the impact of revegetation schemes or monitor the progress of staged implementations.

Context

Landscape graphs are widely used to model connectivity and to support decision-making in conservation planning. Compartmentalization methods applied to such graphs aim to define clusters of highly interconnected patches. Recent studies show that compartmentalization based on modularity is suitable, but it applies to non-weighted graphs whereas most landscape graphs involve weighted nodes and links.

Objectives

We propose to adapt modularity computation to weighted landscape graphs and to validate the relevance of the resulting compartments using demographic or genetic data about the patches.

Methods

A weighted adjacency matrix was designed to express potential fluxes, associating patch capacities and inter-patch distances. Eight weighting scenarios were compared. The statistical evaluation of each compartmentalization was based on Wilks’ Lambda. These methods were performed on a grassland network where patches are documented by annual densities of water voles in the Jura massif (France).

Results

The scenarios in which patch capacity is assigned a small weight led to the more relevant results, giving high modularity values and low Wilks’ Lambda values. When considering a fixed number of compartments, we found a significant negative correlation between these two criteria. Comparison showed that compartments are ecologically more valid than graph components.

Conclusions

The method proposed is suitable for designing ecologically functional areas from weighted landscape graphs. Maximum modularity values can serve as a guide for setting the parameters of the adjacency matrix.

Context

Land-cover changes (LCCs) could impact wildlife populations through gains or losses of natural habitats and changes in the landscape mosaic. To assess such impacts, we need to focus on landscape connectivity from a diachronic perspective.

Objectives

We propose a method for assessing the impact of LCCs on landscape connectivity through a multi-species approach based on graph theory. To do this, we combine two approaches devised to spatialize the variation of multi-species connectivity and to quantify the importance of types of LCCs for single-species connectivity by highlighting the possible contradictory effects.

Methods

We begin with a list of landscape species and create virtual species with similar ecological requirements. We model the ecological network of these virtual species at two dates and compute the variation of a local and global connectivity metric to assess the impacts of the LCCs on their dispersal capacities.

Results

The spatial variation of multi-species connectivity showed that local impacts range from ?6.4% to +3.2%. The assessment of the impacts of types of LCCs showed a variation in global connectivity ranging from ?45.1% for open-area reptiles to +170.2% for natural open-area birds with low-dispersion capacities.

Conclusions

This generic approach can be reproduced in a large variety of spatial contexts by adapting the selection of the initial species. The proposed method could inform and guide conservation actions and landscape management strategies so as to enhance or maintain connectivity for species at a landscape scale.

Context

Complex structural connectivity patterns can influence the distribution of animals in coastal landscapes, particularly those with relatively large home ranges, such as birds. To understand the nuanced nature of coastal forest avifauna, where there may be considerable overlap in assemblages of adjacent forest types, the concerted influence of regional landscape context and vegetative structural connectivity at multiple spatial scales warrants investigation.

Objectives

This study determined whether species compositions of coastal forest bird assemblages differ with regional landscape context or with forest type, and if this is influenced by structural connectivity patterns measured at multiple spatial scales.

Methods

Three replicate bird surveys were conducted in four coastal forest types at ten survey locations across two regional landscape contexts in northeast Australia. Structural connectivity patterns of 11 vegetation types were quantified at 3, 6, and 12 km spatial scales surrounding each survey location, and differences in bird species composition were evaluated using multivariate ordination analysis.

Results

Bird assemblages differed between regional landscape contexts and most coastal forest types, although Melaleuca woodland bird assemblages were similar to those of eucalypt woodlands and rainforests. Structural connectivity was primarily correlated with differences in bird species composition between regional landscape contexts, and correlation depended on vegetation type and spatial scale.

Conclusions

Spatial scale, landscape context, and structural connectivity have a combined influence on bird species composition. This suggests that effective management of coastal landscapes requires a holistic strategy that considers the size, shape, and configuration of all vegetative components at multiple spatial scales.

Context

Efficient restoration of longitudinal river connectivity relies on barrier mitigation prioritization tools that incorporate stream network spatial structure to maximize ecological benefits given limited resources. Typically, ecological benefits of barrier mitigation are measured using proxies such as the amount of accessible riverine habitat.

Objectives

We developed an optimization approach for barrier mitigation planning which directly incorporates the ecology of managed taxa, and applied it to an urbanizing salmon-bearing watershed in Alaska.

Methods

A novel river connectivity metric that exploits information on the distribution and movement of managed taxon was embedded into a barrier prioritization framework to identify optimal mitigation actions given limited restoration budgets. The value of ecological information on managed taxa was estimated by comparing costs to achieve restoration targets across alternative barrier prioritization approaches.

Results

Barrier mitigation solutions informed by life history information outperformed those using only river connectivity proxies, demonstrating high value of ecological information for watershed restoration. In our study area, information on salmon ecology was typically valued at 0.8–1.2 M USD in costs savings to achieve a given benefit level relative to solutions derived only from stream network information, equating to 16–28% of the restoration budget.

Conclusions

Investing in ecological studies may achieve win–win outcomes of improved understanding of aquatic ecology and greater watershed restoration efficiency.

Context

The definition of the geospatial landscape is the underlying basis for species-habitat models, yet sensitivity of habitat use inference, predicted probability surfaces, and connectivity models to landscape definition has received little attention.

Objectives

We evaluated the sensitivity of resource selection and connectivity models to four landscape definition choices including (1) the type of geospatial layers used, (2) layer source, (3) thematic resolution, and (4) spatial grain.

Methods

We used GPS telemetry data from pumas (Puma concolor) in southern California to create multi-scale path selection function models (PathSFs) across landscapes with 2500 unique landscape definitions. To create the landscape definitions, we identified seven geospatial layers that have been shown to influence puma habitat use. We then varied the number, sources, spatial grain, and thematic resolutions of these layers to create our suite of plausible landscape definitions. We assessed how PathSF model performance (based on AIC) was affected by landscape definition and examined variability among the predicted probability of movement surfaces, connectivity models, and road crossing locations.

Results

We found model performance was extremely sensitive to landscape definition and identified only seven top models out of our suite of definitions (<1%). Spatial grain and the number of geospatial layers selected for a landscape definition significantly affected model performance measures, with finer grains and greater numbers of layers increasing model performance.

Conclusions

Given the sensitivity of habitat use inference, predicted probability surfaces, and connectivity models to landscape definition, out results indicate the need for increased attention to landscape definition in future studies.

Context

Dispersal has important fitness consequences for individuals, populations, and species. Despite growing theoretical insights into the evolution of dispersal, its behavioral underpinnings remain empirically understudied, limiting our understanding of the extent and impact of responses to landscape-level heterogeneity of environments, and increasing the risk of inferring species-level responses from biased population sampling.

Objectives

We asked if predictable ecological variation among naturally fragmented arid waterbodies is correlated with disparate dispersal responses of populations of the desert goby Chlamydogobius eremius, which naturally inhabits two habitat “types” (permanent springs, ephemeral rivers), and different levels of hydrological connectivity (high and low) that potentially convey different costs and benefits of dispersal.

Methods

To test for possible behavioral divergence between such populations, we experimentally compared the movement behaviors (correlates of emigration and exploration) of wild-caught fish. We used two biologically relevant spatial scales to test movement relevant to different stages of the dispersal process.

Results

Behavior differed at both spatial scales, suggesting that alternative dispersal strategies enable desert gobies to exploit diverse habitat patches. However, while emigration was best predicted by the connectivity (flood risk) of fish habitats, exploration was linked to their habitat type (spring versus river).

Conclusions

Our findings demonstrate that despite a complex picture of ecological variation, key landscape factors have an overarching effect on among-population variation in dispersal traits. Implications include the maintenance of within-species variation, potentially divergent evolutionary trajectories of naturally or anthropogenically isolated populations, and the direction of future experimental studies on the ecology and evolution of dispersal behavior.

Context

Spatial conservation prioritization (SCP) concerns, for example, identification of spatial priorities for biodiversity conservation or for impact avoidance in economic development. Software useable for SCP include Marxan, C-Plan and Zonation. SCP is often based on data about the distributions of biodiversity features (e.g., species, habitats), costs, threats, and/or ecosystem services (ES).

Objectives and methods

At simplest ES can be entered into a SCP analysis as independent supply maps, but this is not very satisfactory because connectivity requirements and consequent ideal spatial priority patterns may vary between ES. Therefore, we examine different ES and their connectivity requirements at the conceptual level.

Results

We find that the ideal spatial priority pattern for ES may differ in terms of: local supply area size and regional network requirements for the maintenance of ES provision, for flow between provision and demand, and with respect to the degree of dispersion that is needed for ES provision and access across different administrative regions. We then identify existing technical options in the Zonation software for dealing with such connectivity requirements of ES in SCP.

Conclusions

This work helps users of SCP to improve how ES are accounted for in analysis together with biodiversity and other considerations.

Context

The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.

Objectives

The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).

Methods

We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.

Results

We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.

Conclusions

Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.

Context

Interactions between landscape-scale processes and fine-grained habitat heterogeneity are usually invoked to explain species occupancy in fragmented landscapes. In variegated landscapes, however, organisms face continuous variation in micro-habitat features, which makes necessary to consider ecologically meaningful estimates of habitat quality at different spatial scales.

Objectives

We evaluated the spatial scales at which forest cover and tree quality make the greatest contribution to the occupancy of the long-horned beetle Microplophorus magellanicus (Coleoptera: Cerambycidae) in a variegated forest landscape.

Methods

We used averaged data of tree quality (as derived from remote sensing estimates of the decay stage of single trees) and spatially independent pheromone-baited traps to model the occurrence probability as a function of multiple cross-scale combinations between forest cover and tree quality (with scales ranging between 50 and 400 m).

Results

Model support and performance increased monotonically with the increasing scale at which tree quality was measured. Forest cover was not significant, and did not exhibit scale-specific effects on the occurrence probability of M. magellanicus. The interactive effect between tree quality and forest cover was stronger than the independent (additive) effects of tree quality and particularly forest cover. Significant interactions included tree quality measured at spatial scales ≥200 m, but cross-scale interactions occurred only in four of the seven best-supported models.

Conclusions

M. magellanicus respond to the high-quality trees available in the landscape rather than to the amount of forest per se. Conservation of viable metapopulations of M. magellanicus should consider the quality of trees at spatial scales >200 m.

Context

Many aquatic communities are linked by the aerial dispersal of multiple, interacting species and are thus structured by processes occurring in both the aquatic and terrestrial compartments of the ecosystem.

Objectives

To evaluate the environmental factors shaping the aquatic macroinvertebrate communities associated with tank bromeliads in an urban landscape.

Methods

Thirty-two bromeliads were georeferenced to assess the spatial distribution of the aquatic meta-habitat in one city. The relative influence of the aquatic and terrestrial habitats on the structure of macroinvertebrate communities was analyzed at four spatial scales (radius = 10, 30, 50, and 70 m) using redundancy analyses.

Results

We sorted 18,352 aquatic macroinvertebrates into 29 taxa. Water volume and the amount of organic matter explained a significant part of the taxa variance, regardless of spatial scale. The remaining variance was explained by the meta-habitat size (i.e., the water volume for all of the bromeliads within a given surface area), the distance to the nearest building at small scales, and the surface area of buildings plus ground cover at larger scales. At small scales, the meta-habitat size influenced the two most frequent mosquito species in opposite ways, suggesting spatial competition and coexistence. Greater vegetation cover favored the presence of a top predator.

Conclusions

The size of the meta-habitat and urban landscape characteristics influence the structure of aquatic communities in tank bromeliads, including mosquito larval abundance. Modifications to this landscape will affect both the terrestrial and aquatic compartments of the urban ecosystem, offering prospects for mosquito management during urban planning.

Context

In a global context of erosion of biodiversity, the current environmental policy in Europe is oriented towards the creation and the preservation of ecological networks for wildlife. However, most of the management guidelines arose from a structural landscape diagnostic without truly taking into consideration species’ needs.

Objectives

We tested whether and how landscape elements influence the functional connectivity of landscapes for a forest specialist species, the European pine marten (Martes martes), in Northeastern France.

Methods

We collected pine marten scats and tissues from 13 evenly distributed study sites across the whole study area in order to test several types of barriers such as highways, waterways, and open agricultural fields. We crossed the results of several methods: spatial autocorrelation analysis, causal modelling framework, and clustering methods.

Results

The study indicates significant genetic differentiation among the sampling sites. A signal of isolation by distance was detected but disappeared after partialling out landscape or barrier resistance. The only model that was fully supported by causal modelling was the one identifying waterways as the main driver of genetic differentiation. Moreover, clustering analyses indicated the presence of genetic clusters, suggesting that pine marten spatial genetic pattern could be explained by the presence of waterways but also by their reluctance to cross open fields.

Conclusions

The current ecological network could thus be improved by increasing permeability of waterways, in particular navigation canals, and by maintaining and restoring forested corridors in agricultural plains.

Context

Landscapes and animal behavior can exhibit temporal variability and connectivity estimates should consider this phenomenon. In many species, timing of activities such as nesting, mate searching, and hibernation occurs during distinct periods in which movement events may differ, along with physical characteristics of the surrounding landscape.

Objectives

We estimate movement, landscape conductance, and patch importance for a turtle species across two seasonal activity periods (spring, late summer) in a fragmented agricultural region. Three connectivity approaches are compared to identify their advantages and disadvantages.

Methods

A least-cost distance model, circuit-based approach, and patch-based index were used to collectively describe the potential functional connectivity of Blanding’s turtle (Emydoidea blandingii) across a multi-temporal scale in an agricultural region of south western Ontario.

Results

Connectivity decreased further into the active season exhibited through lower conductance of the landscape and fewer pathways, while the importance of habitat nodes shifted due to temporal variability in the number and distribution of nodes. Models provided different yet complimentary information, with least-cost models overestimating discrete pathways yet providing a secondary measure of landscape barriers. The circuit-based model estimated corridors of least resistance providing an overall characterization of the landscape, while patch-based indices provided key information on the importance of individual habitat patches.

Conclusion

Findings highlight the importance of including a temporal aspect in connectivity modelling as results demonstrate a change in functional connectivity over time. We also recommend employing multiple connectivity metrics to capture variation in movement behavior.

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.

Context

Playa wetlands are the primary habitat for numerous wetland-dependent species in the Southern Great Plains of North America. Plant and wildlife populations that inhabit these wetlands are reciprocally linked through the dispersal of individuals, propagules and ultimately genes among local populations.

Objective

To develop and implement a framework using network models for conceptualizing, representing and analyzing potential biological flows among 48,981 spatially discrete playa wetlands in the Southern Great Plains.

Methods

We examined changes in connectivity patterns and assessed the relative importance of wetlands to maintaining these patterns by targeting wetlands for removal based on network centrality metrics weighted by estimates of habitat quality and probability of inundation.

Results

We identified several distinct, broad-scale sub networks and phase transitions among playa wetlands in the Southern Plains. In particular, for organisms that can disperse >2 km a dense and expansive wetland sub network emerges in the Southern High Plains. This network was characterized by localized, densely connected wetland clusters at link distances (h) >2 km but <5 km and was most sensitive to changes in wetland availability (p) and configuration when h = 4 km, and p = 0.2–0.4. It transitioned to a single, large connected wetland system at broader spatial scales even when the proportion of inundated wetland was relatively low (p = 0.2).

Conclusions

Our findings suggest that redundancy in the potential for broad and fine-scale movements insulates this system from damage and facilitates system-wide connectivity among populations with different dispersal capacities.

Context

Conservation research often focuses on individual threats at a single spatial scale, but population declines can result from multiple stressors occurring at different spatial scales. Analyses incorporating alternative hypotheses across spatial scales allow more robust evaluation of the ecological processes underlying population declines.

Objectives

Populations of many aerially insectivorous birds are declining, yet conservation efforts remain focused on habitat due to an absence of data on changes in prey availability. We evaluate the potential for prey and habitat availability at multiple spatial scales to influence a population of eastern whip-poor-wills (Antrostomus vociferous).

Methods

We assess relationships between landcover (topographical map and satellite imagery) and insect abundance (moths and beetles from blacklight traps), and whip-poor-will distribution and abundance within eastern Canada using Ontario breeding bird atlas data (1980s and 2000s), acoustic recordings (regional), and point counts (local).

Results

Whip-poor-will occurrence in both atlas time periods was positively associated with forest area and fragmentation, but only a delayed effect of urban area explained reductions in detection. Contemporary regional whip-poor-will presence was positively related to moth abundance, and local whip-poor-will abundance was best predicted by area of open-canopy forest, anthropogenic linear disturbance density, and beetle abundance. Our finding that bird presence and abundance were associated with human activity and insect abundance across spatial scales suggests factors beyond habitat structure are likely driving population declines in whip-poor-wills and other aerial insectivores.

Conclusions

This study demonstrates the importance of examining multiple hypotheses, including seasonally and locally variable food availability, across a range of spatial scales to direct conservation efforts.

Context

Species distributions are driven by a wide variety of abiotic and biotic factors, including nest placement for breeding individuals. As such, the spatial distribution of nests within a landscape can reflect environmental heterogeneity, habitat preferences, or even interactions with predators and other species.

Objectives

We determined the extent to which environmental heterogeneity and predation risk accounted for the observed spatial distribution of nests.

Methods

We assessed the spatial distribution of 112 nests of a migratory shorebird, the Hudsonian Godwit (Limosa haemastica), at Beluga River, Alaska, from 2009 to 2012, and explicitly tested for the relative influence of habitat characteristics and predation risk on nest locations. We also evaluated the effect of nest location, distance to conspecific nests, and proximity to roads on nest fate using 64 nests that were monitored through completion.

Results

Hudsonian Godwit nests were clustered across the landscape despite a lack of significant spatial autocorrelation (i.e., patchiness) in vegetation characteristics at either the micro- or landscape scale. Nest fate also was not predicted by either the distance to the nearest conspecific neighbor or proximity to roads. Thus, neither habitat characteristics nor predation risk explained the clustering of godwit nests.

Conclusions

These results suggest that godwits may select nest locations based more on social cues than underlying heterogeneity in vegetation or predation risk. As such, intra- and inter-specific interactions should be considered when developing management plans for species of conservation concern.

Context

Land use changes have modified the extent and structure of native vegetation, resulting in fragmentation of native species habitat. Connectivity is increasingly seen as a requirement for effective conservation in these landscapes, but the question remains: ‘connectivity for which species?’.

Objective

The aim of this study was to develop and then apply a rapid, expert-based, dispersal guild approach where species are grouped on similar fine-scale dispersal behaviour (such as between scattered trees) and habitat characteristics.

Methods

Dispersal guilds were identified using clustering techniques to compare dispersal and habitat parameters elicited from experts. We modelled least-cost paths and corridors between patches and individual movement probabilities within these corridors for each of the dispersal guilds using Circuitscape. We demonstrate our approach with a case study in the Tasmanian Northern Midlands, Australia.

Results

The dispersal guild approach grouped the 12 species into five dispersal guilds. The connectivity modelling of those five guilds found that broadly dispersing species in this landscape, such as medium-sized carnivorous mammals, were unaffected by fragmentation while from the perspective of the three dispersal guilds made up of smaller mammals, the landscape appeared highly fragmented.

Conclusions

Our approach yields biologically defensible outputs that are broadly applicable, particularly for conservation planning where data and resources are limited. It is a useful first step in multi-species conservation planning which aims to identify those species most in need of conservation efforts.

Context

Regime shifts are well known for driving penetrating ecological change, yet we do not recognise the consequences of these shifts much beyond species diversity and productivity. Sound represents a multidimensional space that carries decision-making information needed for some dispersing species to locate resources and evaluate their quantity and quality.

Objectives

Here we assessed the effect of regime shifts on marine soundscapes, which we propose has the potential function of strengthening the positive or negative feedbacks that mediate ecosystem shifts.

Methods

We tested whether biologically relevant cues are altered by regime shifts in kelp forests and seagrass systems and how specific such shifted soundscapes are to the type of driver; i.e. local pollution (eutrophication) vs. global change (ocean acidification).

Results

Here, we not only provide the first evidence for regime-shifted soundscapes, but also reveal that the modified cues of shifted ecosystems are similar regardless of spatial scale and type of environmental driver. Importantly, biological sounds can act as functional cues for orientation by dispersing larvae, and observed shifts in soundscape loudness may alter this function.

Conclusions

These results open the question as to whether shifted soundscapes provide a functional role in mediating the positive or negative feedbacks that govern the arrival of species associated with driving change or stasis in ecosystem state.