Characterising landscape connectivity for conservation planning using a dispersal guild approach

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.

     

Quantifying landscape connectivity through the use of connectivity response curves

Habitat connectivity is an essential component of biodiversity conservation. Simulated landscapes were manipulated to quantify the impact of changes to the amount, fragmentation and dispersion of habitat on a widely applied landscape connectivity metric, the probability of connectivity index. Index results for different landscape scenarios were plotted against the dispersal distances used for their calculation to create connectivity response curves for each scenario. Understanding index response to controlled changes in landscape structure at a range of spatial scales can be used to give context to comparison of alternative landscape management scenarios. Increased amounts of habitat, decreased fragmentation and decreased inter-patch distances resulted in increased connectivity index values. Connectivity response curves demonstrated increases in assessed connectivity for scenarios with continuous corridors or “stepping stone” connectors. The sensitivity of connectivity response curves to controlled changes in landscape structure indicate that this approach is able to detect and distinguish between different types of landscape changes, but that delineation of habitat and method of quantifying dispersal probability incorporate assumptions that must be recognized when interpreting results to guide landscape management. Representing landscape connectivity in this manner allows for the impacts of alternative landscape management strategies to be compared visually through comparative plots, or statistically through the parameters that describe connectivity response curves.     

Measuring landscape connectivity: On the importance of within-patch connectivity

Context

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity.

Objectives

A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results.

Methods

The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (m_eff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity.

Results

We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using m_eff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT.

Conclusions

Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

     

Considering landscape connectivity and gene flow in the Anthropocene using complementary landscape genetics and habitat modelling approaches

Landscape Ecology - A comprehensive understanding of how rapidly changing environments affect species gene flow is critical for mitigating future biodiversity losses. While recent methodological...     

Assessing landscape functional connectivity in a forest carnivore using path selection functions

Context

Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty.

Objectives

We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks.

Methods

We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces.

Results

Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures.

Conclusions

Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.

     

Impact of agricultural subsidies on biodiversity at the landscape level

Agricultural management is a major factor driving the change of faunal richness in anthropogenic landscapes. Thus, there is an urgent need to develop tools that allow decision-makers to understand better intended and unintended effects of agricultural policy measures on biodiversity. Here we demonstrate the potential of such a tool by combining a socio-economic model with the biodiversity model GEPARD to forecast the response of bird and carabid species richness to two scenarios of agricultural subsidies: (1) subsidies based on production levels and prices and (2) direct income support that is independent of production levels. We focussed on farmland of the Lahn-Dill area, Germany, as an example of European regions with low intensity farming. GEPARD predicts faunal richness and is based on multi-scaled resource-selection functions. Under both scenarios the area of predicted losses in species richness of birds and carabids was larger than the area of predicted gains in species richness. However, the area with predicted losses of avian richness was smaller under the direct income support scenario than under the production-based subsidy scenario, whereas the area with predicted losses of carabid species richness was smaller under the production-based subsidy scenario than under the direct income support. Yet locally, richness gains of up to four species were predicted for carabids under both scenarios. We conclude that the sometimes contrasting and heterogeneous responses of birds and carabids at different localities suggest the need for spatially targeted subsidy schemes. With the help of the GIS-based approach presented in this study, prediction maps on potential changes in local and regional species richness can be easily generated.     

Genetic analysis of landscape connectivity in tree populations

Genetic connectivity in plant populations is determined by gene movement within and among populations. When populations become genetically isolated, they are at risk of loss of genetic diversity that is critical to the long-term survival of populations. Anthropogenic landscape change and habitat fragmentation have become so pervasive that they may threaten the genetic connectivity of many plant species. The theoretical consequences of such changes are generally understood, but it is not immediately apparent how concerned we should be for real organisms, distributed across real landscapes. Our goals here are to describe how one can study gene movement of both pollen and seeds in the context of changing landscapes and to explain what we have learned so far. In the first part, we will cover methods of describing pollen movement and then review evidence for the impact of fragmentation in terms of both the level of pollen flow into populations and the genetic diversity of the resulting progeny. In the second part, we will describe methods for contemporary seed movement, and describe findings about gene flow and genetic diversity resulting from seed movement. Evidence for pollen flow suggests high connectivity, but it appears that seed dispersal into fragments may create genetic bottlenecks due to limited seed sources. Future work should address the interaction of pollen and seed flow and attention needs to be paid to both gene flow and the diversity of the incoming gene pool. Moreover, if future work is to model the impact of changing landscapes on propagule movement, with all of its ensuing consequences for genetic connectivity and demographic processes, we will need an effective integration of population genetics and landscape ecology.     

Evaluating static and dynamic landscape connectivity modelling using a 25-year remote sensing time series

Context

Despite calls for landscape connectivity research to account for spatiotemporal dynamics, studies have overwhelmingly evaluated the importance of habitats for connectivity at single or limited moments in time. Remote sensing time series represent a promising resource for studying connectivity within dynamic ecosystems. However, there is a critical need to assess how static and dynamic landscape connectivity modelling approaches compare for prioritising habitats for conservation within dynamic environments.

Objectives

To assess whether static landscape connectivity analyses can identify similar important areas for connectivity as analyses based on dynamic remotely sensed time series data.

Methods

We compared degree and betweenness centrality graph theory metric distributions from four static scenarios against equivalent results from a dynamic 25-year remotely sensed surface-water time series. Metrics were compared at multiple spatial aggregation scales across south-eastern Australia’s 1 million km² semi-arid Murray–Darling Basin and three sub-regions with varying levels of hydroclimatic variability and development.

Results

We revealed large differences between static and dynamic connectivity metric distributions that varied by static scenario, region, spatial scale and hydroclimatic conditions. Static and dynamic metrics showed particularly low overlap within unregulated and spatiotemporally variable regions, although similarities increased at coarse aggregation scales.

Conclusions

In regions that exhibit high spatiotemporal variability, static connectivity modelling approaches are unlikely to serve as effective surrogates for more data intensive approaches based on dynamic, remotely sensed data. Although this limitation may be moderated by spatially aggregating static connectivity outputs, our results highlight the value of remotely sensed time series for assessing connectivity in dynamic landscapes.

     

Sensitivity of resource selection and connectivity models to landscape definition

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.

     

Estimation of metademographic rates and landscape connectivity for a conservation-reliant anuran

Landscape Ecology - Amphibian conservation efforts commonly assume populations are tied to waterbodies that collectively function as a metapopulation. This assumption is rarely evaluated, and there...     

Role of green roofs in urban connectivity,an exploratory approach using landscape graphs in the city of Paris,France

Green roofs provide many ecosystem services, but little is known about the way they contribute to urban functional connectivity. This paper has the following four objectives: (1) to compare the potential green roofs’ role to connectivity in relation to other urban green spaces, (2) to specify the green roofs contribution’s type, (3) to explore the influence of building height integration method and finally (4) to assess the impact on connectivity of simulated greening new roofs. Using a landscape graph approach, we modeled ecological networks of three species groups with different dispersion capacities in the Paris region (France). Then, we computed several connectivity metrics to assess the potential contribution of green roofs to functional connectivity. At a large scale (metropole scale), our results show that green roofs can slightly improve the global connectivity largely through the connections rather than the addition of habitat area. More than a stepping stone function, green roofs would have a dispersion flux function at a local scale. Furthermore, when the difficulty of crossing movement is exponential to the height of buildings, green roofs over 20 m high are mostly disconnected from the ecological networks. In addition to the green roof’s height, our analysis highlights the very strong role played by buildings’ configuration. This study raises promising directions for the integration of building height into the analysis of urban connectivity. Detailed research and long-term biological data from green roofs and green spaces are needed to confirm our results.     

Effect of landscape connectivity on plant communities: a review of response patterns

Landscape Ecology - Fragmentation in agricultural landscapes is considered as a major threat to biodiversity. Thus, ecological corridors are deployed at multiple scales to increase connectivity....     

A multi-species approach for assessing the impact of land-cover changes on landscape connectivity

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.

     

Prioritization of habitat patches for landscape connectivity conservation differs between least-cost and resistance distances

Context

Methods quantifying habitat patch importance for maintaining habitat network connectivity have been emphasized in helping to prioritize conservation actions. Functional connectivity is accepted as depending on landscape resistance, and several measures of functional inter-patch distance have been designed. However, how the inter-patch distance, i.e., based on least-cost path or multiple paths, influences the identification of key habitat patches has not been explored.

Objectives

We compared the prioritization of habitat patches according to least-cost distance (LCD) and resistance distance (RD), using common binary and probabilistic connectivity metrics.

Methods

Our comparison was based on a generic functional group of forest mammals with different dispersal distances, and was applied to two landscapes differing in their spatial extent and fragmentation level.

Results

We found that habitat patch prioritization did not depend on distance type when considering the role of patch as contributing to dispersal fluxes. However, the role of patch as a connector facilitating dispersal might be overestimated by LCD-based indices compared with RD for short- and medium-distance dispersal. In particular, when prioritization was based on dispersal probability, the consideration of alternatives routes identified the connectors that probably provided functional connectivity for species in the long term. However, the use of LCD might help identify landscape areas that need critical restoration to improve individual dispersal.

Conclusions

Our results provide new insights about the way that inter-patch distance is viewed changes the evaluation of functional connectivity. Accordingly, prioritization methods should be carefully selected according to assumptions about population functioning and conservation aims.

     

Successional change in the insect community of a fragmented landscape

Habitat fragmentation strongly affects insect species diversity and community composition, but few studies have examined landscape effects on long term development of insect communities. As mobile consumers, insects should be sensitive to both local plant community and landscape context. We tested this prediction using sweep-net transects to sample insect communities for 8 years at an experimentally fragmented old-field site in northeastern Kansas, USA. The site included habitat patches undergoing secondary succession, surrounded by a low turf matrix. During the first 5 years, plant richness and cover were measured in patches. Insect species richness, total density, and trophic diversity increased over time on all transects. Cover of woody plants and perennial forbs increased each year, adding structural complexity to successional patches and potentially contributing to increased insect diversity. Within years, insect richness was significantly greater on transects through large successional patches (5000 m²) than on transects through fragmented arrays of 6 medium-sized (total area 1728 m²) or 15 small (480 m²) patches. However, plant cover did not differ among patch types and was uncorrelated with insect richness within years. Insect richness was strongly correlated with insect density, but trophic and α diversities did not differ among patch types, indicating that patch insect communities were subsets of a common species pool. We argue that differences in insect richness resulted from landscape effects on the size of these subsets, not patch succession rates. Greater insect richness on large patches can be explained as a community-level consequence of population responses to resource concentration.     

Individual-based modeling highlights the importance of mortality and landscape structure in measures of functional connectivity

Landscape Ecology - Functional landscape connectivity is vital for the conservation of wildlife species. Landscape connectivity models often overlook factors such as mortality and asymmetry in...     

Regional assessment on influence of landscape configuration and connectivity on range size of white-tailed deer

Variation in the size of home range of white-tailed deer (Odocoileus virginianus) has broad implications for managing populations, agricultural damage, and disease spread and transmission. Size of home range of deer also varies seasonally because plant phenology dictates the vegetation types that are used as foraging or resting sites. Knowledge of the landscape configuration and connectivity that contributes to variation in size of home range of deer for the region is needed to fully understand differences and similarities of deer ecology throughout the Midwest. We developed a research team from four Midwestern states to investigate how size of home range of deer in agro-forested landscapes is influenced by variations in landscape characteristics that provide essential habitat components. We found that for resident female deer, annual size of home range in Illinois (mean = 0.99 km²), Michigan (mean = 1.34 km²), Nebraska (mean = 1.20 km²), and Wisconsin (mean = 1.47 km²) did not differ across the region (F _3,175 = 0.42, P = 0.737), but differences between agricultural growing and nongrowing periods were apparent. Variables influencing size of home range included: distance to forests, roads, and urban development from the centroid of deer home range, and percent of crop as well as four landscape pattern indices (contrast-weighted edge density, mean nearest neighbor, area-weighted mean shape index, and patch size coefficient of variation). We also identified differences in model selection for four landscapes created hierarchically to reflect levels of landscape connectivity determined from perceived ability of deer to traverse the landscape. Connectivity of selected forested regions within agro-forested ecosystems across the Midwest plays a greater role in understanding the size of home ranges than traditional definitions of deer habitat conditions and landscape configuration.     

Moving beyond landscape resistance: considerations for the future of connectivity modelling and conservation science

Landscape Ecology - Landscape connectivity, the extent to which a landscape facilitates the flow of ecological processes such as organism movement, has emerged as a central focus of landscape...     

Modeling scale-dependent landscape pattern,dispersal, and connectivity from the perspective of the organism

Understanding the impacts of habitat fragmentation on dispersal is an important issue in landscape and conservation ecology. Here I examine the effects of fine- to broad-scale patterns in landscape structure on dispersal success of organisms with differing life-history traits. An individual-based model was used to simulate dispersal of amphibian-like species whose movements were driven by land cover and moisture conditions. To systematically control spatial pattern, a landscape model was created by merging simulated land cover maps with synthetic topographic surfaces. Landscapes varied in topographic roughness and spatial contagion in agriculture and urban land cover. Simulations included three different species types that varied in their maximum potential dispersal distances by 1-, 2-, or 4-fold. Two sets of simulations addressed effects of varying aspects of landscape structure on dispersal success. In the first set of simulations, which incorporated variable distances between breeding patches, dispersal success was lowest for all species types when anthropogenic cover was patchily distributed. In the second set, with interpatch distances held constant as landscape composition varied, dispersal success decreased as anthropogenic cover became spatially contagious. Both sets revealed strong main effects of species characteristics, interpatch distances and landscape composition on dispersal success; furthermore, scale-dependent patterns in land cover and moisture gradients had a stronger effect on longer- than shorter-ranging species types. Taken together, these simulations suggest that heuristic conservation strategies could potentially be developed based on important but limited life history information.