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.     

Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles

When the objective is to characterize landscapes with respect to relative degree and type of forest (or other critical habitat) fragmentation, it is difficult to decide which variables to measure and what type of discriminatory analysis to apply. It is also desirable to incorporate multiple measurement scales. In response, a new method has been developed that responds to changes in both the marginal and spatial distributions of land cover in a raster map. Multiscale features of the map are captured in a sequence of successively coarsened resolutions based on the random filter for degrading raster map resolutions. Basically, the entropy of spatial pattern associated with a particular pixel resolution is calculated, conditional on the pattern of the next coarser parent resolution. When the entropy is plotted as a function of changing resolution, we obtain a simple two-dimensional graph called a conditional entropy profile, thus providing a graphical visualization of multi-scale fragmentation patterns.Using eight-category raster maps derived from 30-meter resolution LANDSAT Thematic Mapper images, the conditional entropy profile was obtained for each of 102 watersheds covering the state of Pennsylvania (USA). A suite of more conventional single-resolution landscape measurements was also obtained for each watershed using the FRAGSTATS program. After dividing the watersheds into three major physiographic provinces, cluster analysis was performed within each province using various combinations of the FRAGSTATS variables, land cover proportions and variables describing the conditional entropy profiles. Measurements of both spatial pattern and marginal land cover proportions were necessary to clearly discriminate the watersheds into distinct clusters for most of the state; however, the Piedmont province essentially only required the land cover proportions. In addition to land cover proportions, only the variables describing a conditional entropy profile appeared to be necessary for the Ridge and Valley province, whereas only the FRAGSTATS variables appeared to be necessary for the Appalachian Plateaus province. Meanwhile, the graphical representation of conditional entropy profiles provided a visualization of multi-scale fragmentation that was quite sensitive to changing pattern.     

Habitat connectivity for pollinator beetles using surface metrics

Measuring habitat connectivity in complex landscapes is a major focus of landscape ecology and conservation research. Most studies use a binary landscape or patch mosaic model for describing spatial heterogeneity and understanding pattern-process relationships. While the value of landscape gradient approaches proposed by McGarigal and Cushman are recognized, applications of these newly proposed three dimensional surface metrics remain under-used. We created a gradient map of habitat quality from several GIS layers and applied three dimensional surface metrics to measure connectivity between 67 locations in Indiana, USA surveyed for one group of ecosystem service providers, flower longicorn beetles (Cerambycidae: Lepturinae). The three dimensional surface metrics applied to the landscape gradient model showed great potential to explain the differences of lepturine assemblages among the 2,211 studied landscapes (between site pairs). Surface kurtosis and its interaction with geographic distance were among the most important metrics. This approach provided unique information about the landscape through four configuration metrics. There were some uniform trends of the responses of many species to some of surface metrics, however some species responded differently to other metrics. We suggest that three dimensional surface metrics applied to a habitat surface map created with insight into species requirements is a valuable approach to understanding the spatial dynamics of species, guilds, and ecosystem services.     

Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation

Since the fragmentation of natural habitats is one of the most serious problems for many endangered species, it is highly interesting to study the properties of fragmented landscapes. As a basic property, landscape connectivity and its effects on various ecological processes are frequently in focus. First, we discuss the relevance of some graph properties in quantifying connectivity. Then, we propose a method how to quantify the relative importance of habitat patches and corridors in maintaining landscape connectivity. Our combined index explicitly considers pure topological properties and topographical measures, like the quality of both patches (local population size) and corridors (permeability). Finally, for illustration, we analyze the landscape graph of the endangered, brachypterous bush-cricket Pholidoptera transsylvanica. The landscape contains 11 patches and 13 corridors and is situated on the Aggtelek Karst, NE-Hungary. We characterize the importance of each node and link of the graph by local and global network indices. We show how different measures of connectivity may suggest different conservation preferences. We conclude, accordingly to our present index, by identifying one specific habitat patch and one specific corridor being in the most critical positions in maintaining connectivity.This revised version was published online in May 2005 with corrections to the Cover Date.     

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.

     

Evaluation of landscape connectivity at community level using satellite-derived NDVI

Landscape connectivity, defined as the degree to which the landscape facilitates or impedes movement among resource patches, has been considered to be a key issue for biodiversity conservation. However, the use of landscape connectivity measurements has been strongly criticised due to uncertainties in the methods used and the lack of validation. Moreover, measurements are typically restricted to the population level, whereas management is generally carried out at the community level. Here, we used satellite imagery and network metrics to predict the landscape connectivity at community level for semi-natural herbaceous patches in an urban area near Paris (France). We tested different measurement methods, both taking into account and ignoring the spatial heterogeneity of matrix resistance estimated by the normalised difference vegetation index (NDVI), and quantifying the link strength between patches with the shortest path and flow metrics. We assessed the fit of these connectivity predictions with empirical data on plant communities embedded in an urban matrix. Our results indicate that the best fit with the empirical data is obtained when the connectivity is estimated with the flow metric and takes into account the matrix heterogeneity. Overall, our study helps to estimate the landscape connectivity of urban areas and makes recommendations for ways in which we might optimise landscape planning with respect to conservation of urban biodiversity.     

Examining speed versus selection in connectivity models using elk migration as an example

Context

Landscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.

Objective

To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.

Methods

Using movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.

Results

All connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.

Conclusions

CTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.

     

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.

     

用微卫星标记研究樱桃品种间的亲缘关系(英文)

从来自不同地理区域的36个樱桃基因型中筛选了33对不同樱桃品种的微卫星引物,以鉴定和描述他们的基因型并确定亲缘关系。33对微卫星引物中,29对获得了预期的扩增片段,17对引物在所研究的36个基因型中产生了多态性高、稳定扩增片段,17个位点共检测到71个等位基因。微卫星分子标记技术可以准确的鉴别所有樱桃品种的基因型,为微卫星序列的通用性提供强有力的证据,可以用蔷薇科李属的序列来区分樱桃品种的不同基因型,根据不同品种的地理起源及其亲缘关系用UPGMA聚类分析法对其基因型进行分类。     

Static vs dynamic connectivity: how landscape changes affect connectivity predictions in the Iberian Peninsula

Landscape Ecology - Climate and land-use changes affect species ranges and movements. However, these changes are usually overlooked in connectivity studies, and this could have adverse consequences...     

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...     

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.

     

Mapping sources,sinks, and connectivity using a simulation model of northern spotted owls

Source-sink dynamics are an emergent property of complex species–landscape interactions. A better understanding of how human activities affect source-sink dynamics has the potential to inform and improve the management of species of conservation concern. Here we use a study of the northern spotted owl (Strix occidentalis caurina) to introduce new methods for quantifying source-sink dynamics that simultaneously describe the population-wide consequences of changes to landscape connectivity. Our spotted owl model is mechanistic, spatially-explicit, individual-based, and incorporates competition with barred owls (Strix varia). Our observations of spotted owl source-sink dynamics could not have been inferred solely from habitat quality, and were sensitive to landscape connectivity and the spatial sampling schemes employed by the model. We conclude that a clear understanding of source-sink dynamics can best be obtained from sampling simultaneously at multiple spatial scales. Our methodology is general, can be readily adapted to other systems, and will work with population models ranging from simple and low-parameter to complex and data-intensive.     

Identification and investigation of relationships of mandarin types using isozyme analysis

Sixteen enzyme systems with 19 loci were used to discriminate 19 mandarin cultivars and hybrids. Variability was observed at 12 loci, and all but 3 mandarin types could be discriminated, 2 of which were probably identical. Relatedness within the tangelo and tangor groups was high, probably reflecting their recent origin. Relatedness within the common mandarin group was low, reflecting their multiple origins and long cultivation. Exceptions were cultivars ‘Algerian’ and ‘Beauty of Glen Retreat’, which differed at only 1 locus. Relatedness between the groups was generally low, with the least relatedness between the tangelos and the other groups, probably owing to their grapefruit parent. The ‘Ellendale’ cultivars formed a particularly cohesive group, but with 2 isozyme genotypes, differing at 2 loci, both marketed as ‘Ellendale’. Three of the ‘Ellendale’-type cultivars probably arose by self-pollination of ‘Ellendale’, the rest either by self-pollination or by mutation.     

Yards increase forest connectivity in urban landscapes

Landscape Ecology - Tree canopy connectivity is important for supporting biodiversity. In urban landscapes, empirical examinations of habitat connectivity often overlook residential land, though...     

Pollination graphs: quantifying pollen pool covariance networks and the influence of intervening landscape on genetic connectivity in the North American understory tree, Cornus florida L.

The manner by which pollinators move across a landscape and their resulting preferences and/or avoidances of travel through particular habitat types can have a significant impact on plant population genetic structure and population-level connectivity. We examined the spatial genetic structure of the understory tree Cornus florida (Cornaceae) adults (N _Adults = 452) and offspring (N _Offspring = 736) across two mating events to determine the extent to which pollen pool genetic covariance is influenced by intervening forest architecture. Resident adults showed no spatial partitioning but genotypes were positively autocorrelated up to a distance of 35 m suggesting a pattern of restricted seed dispersal. In the offspring, selfing rates were small (s_m = 0.035) whereas both biparental inbreeding (s _{b;open canopy} = 0.16, s _{b;closed canopy} = 0.11) and correlated paternity (r _{p;open canopy} = 0.21, r _{p;closed canopy} = 0.07) were significantly influenced by primary canopy opening above individual mothers. The spatial distribution of genetic covariance in pollen pool composition was quantified for each reproductive event using Pollination Graphs, a network method based upon multivariate conditional genetic covariance. The georeferenced graph topology revealed a significant positive relationship between genetic covariance and pollinator movement through C. florida canopies, a negative relationship with open primary canopy (e.g., roads under open canopies and fields with no primary canopy), and no relationship with either conifer or mixed hardwood canopy species cover. These results suggest that both resident genetic structure within stands and genetic connectivity between sites in C. florida populations are influenced by spatial heterogeneity of mating individuals and quality of intervening canopy cover.     

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.     

Ecosystem services and connectivity in spatial conservation prioritization

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.

     

Dynamic connectivity of temporary wetlands in the southern Great Plains

We quantified fluctuations in the status of individual patches (wetlands) in supporting connectivity within a network of playas, temporary wetlands of the southern Great Plains of North America that are loci for regional biodiversity. We used remote sensing imagery to delineate the location of surface waters in >8,000 playa basins in a ~31,900 km² portion of Texas and quantified connectivity in this region from 2007 to 2011. We ranked playas as stepping-stones, cutpoints, and hubs at different levels of environmental conditions (regionally wet, dry, and average periods of precipitation) for dispersal distances ranging from 0.5 to 34 km, representing a range of species’ vagilities, to provide baseline dynamics within an area likely to experience disrupted connectivity due to anthropogenic activities. An individual playa’s status as a stepping-stone, cutpoint, or hub was highly variable over time (only a single playa was a top 20 stepping-stone, cutpoint, or hub in >50 % of all of the dates examined). Coalescence of the inundated playa network usually occurred at ≥10 km dispersal distance and depended on wetland density, indicating that critical thresholds in connectivity arose from synergistic effects of dispersal ability (spatial scale) and wet playa occurrence (a function of precipitation). Organisms with dispersal capabilities limited to <10 km routinely experienced effective isolation during our study. Connectivity is thus a dynamic emergent landscape property, so management to maintain connectivity for wildlife within ephemeral habitats like inundated playas will need to move beyond a patch-based focus to a network focus by including connectivity as a dynamic landscape property.