Context

Scale dependence of bat habitat selection is poorly known with few studies evaluating relationships among landscape metrics such as class versus landscape, or metrics that measure composition or configuration. This knowledge can inform conservation approaches to mitigate habitat loss and fragmentation.

Objectives

We evaluated scale dependence of habitat associations and scaling patterns of landscape metrics in relation to bat occurrence or capture rate in forests of southwestern Nicaragua.

Methods

We captured 1537 bats at 35 locations and measured landscape and class metrics across 10 spatial scales (100–1000 m) surrounding capture locations. We conducted univariate scaling across the 10 scales and identified scales and variables most related to bat occurrence or capture rate.

Results

Edge and patch density, at both landscape and class levels, were the most important variables across species. Feeding guilds varied in their response to metrics. Certain landscape and configuration metrics were most influential at fine (100 m) and/or broad (1000 m) spatial scales while most class and composition metrics were influential at intermediate scales.

Conclusions

These results provide insight into the scale dependence of habitat associations of bat species and the influence of fine and broad scales on habitat associations. The effects of scale, examined in our study and others from fine (100 m) to broad (5 km) indicate habitat relationships for bats may be more informative at larger scales. Our results suggest there could be general differences in scale relationships for different groups of landscape metrics, which deserves further evaluation in other taxonomic groups.

Context

Urban sprawl and the expanding transportation infrastructure drive land consumption and landscape fragmentation, causing environmental deterioration and loss of species. Current understanding of how these drivers interact to shape landscape fragmentation is still poor. However, a strong correlation between urban sprawl and landscape fragmentation patterns is commonly assumed.

Objectives

Our main objective was to test the strength, non-stationarity, and scale-dependency of the relationship between urban sprawl and landscape fragmentation patterns (‘sprawl-fragmentation relationship’). Subsequently, we propose an extended framework for the links between urban sprawl, expansion of transport infrastructure, and landscape fragmentation.

Methods

We quantified spatial patterns of urban sprawl and landscape fragmentation for mainland Spain at multiple scales. We then fitted global regression models and geographically weighted regression models with metrics of landscape fragmentation and urban sprawl.

Results

Most variation in landscape fragmentation values (almost 80 % on average) is not explained by urban sprawl metrics through global modeling. Local models show substantial improvements in model performance, with an average of 37 % of the variance remaining unexplained. The contribution of urban sprawl to landscape fragmentation patterns varies locally and depends on scale, with higher contributions at coarser scales and at higher organizational levels.

Conclusions

Our investigation revealed three critical characteristics of the sprawl-fragmentation relationship: it does not prevail, is non-stationary, and scale-dependent. We propose four mechanisms that may have resulted in this mismatch: scale, time-lagged development, spatial arrangement of development, and other external variables including teleconnections. These spatial mismatches provide windows of opportunity for conservation through better development strategies.

Context

The patch-mosaic model is lauded for its conceptual simplicity and ease with which conventional landscape metrics can be computed from categorical maps, yet many argue it is inconsistent with ecological theory. Gradient surface models (GSMs) are an alternative for representing landscapes, but adoption of surface metrics for analyzing spatial patterns in GSMs is hindered by several factors including a lack of meaningful interpretations.

Objectives

We investigate the performance and applicability of surface metrics across a range of ecoregions and scales to strengthen theoretical foundations for their adoption in landscape ecology.

Methods

We examine metric clustering across scales and ecoregions, test correlations with patch-based metrics, and provide ecological interpretations for a variety of surface metrics with respect to forest cover to support the basis for selecting surface metrics for ecological analyses.

Results

We identify several factors complicating the interpretation of surface metrics from a landscape perspective. First, not all surface metrics are appropriate for landscape analyses. Second, true analogs between surface metrics and patch-based, landscape metrics are rare. Researchers should focus instead on how surface measures can uniquely measure spatial patterns. Lastly, scale dependencies exist for surface metrics, but relationships between metrics do not appear to change considerably with scale.

Conclusions

Incorporating gradient surfaces into landscape ecological analyses is challenging, and many surface metrics may not have patch analogs or be ecologically relevant. For this reason, surface metrics should be considered in terms of the set of pattern elements they represent that can then be linked to landscape characteristics.

Context

Considerable research has examined scale effects for patch-based metrics with the ultimate goal of predicting values at finer resolutions (i.e., downscaling), but results have been inconsistent. Surface metrics have been suggested as an alternative to patch-based metrics, although far less is known about their scaling relationships and downscaling potential. If successful, downscaling would enable integration of disparate datasets and comparison of landscapes using different resolution datasets.

Objectives

(1) Determine how surface metrics scale as resolution changes and how consistent those scaling relationships are across landscapes. (2) Test whether these scaling relationships can be accurately downscaled to predict metric values for finer resolutions.

Methods

Various scaling functions were fit to 16 surface metrics computed for multiple resolutions for a set of landscapes. Best-fitting functions were then extrapolated to test downscaling behavior (i.e., predict metric value for a finer resolution) for an independent set of validation landscapes. Relative error was assessed between the predicted and true values to determine downscaling robustness.

Results

Seven surface metrics (Sa, Sq, S10z, Sdq, Sds, Sdr, Srwi) fit consistently well (R² > 0.99) with a 3rd order polynomial or power law. Of those, the scaling functions for Sa, Sq, and S10z were able to predict metric values at a finer resolution within 5 %. Three metrics, (Ssk, Sku, Sfd) were also notable in terms of fit and downscaling.

Conclusions

Many metrics exhibit consistent scaling relations across resolution, and several are able to accurately predict values at finer resolutions. However, prediction accuracy is likely related to the amount of information lost during aggregation.

Context

Revealing the interaction between landscape pattern and urban land surface temperature (LST) can provide insight into mitigating thermal environmental risks. However, there is no consensus about the key landscape indicators influencing LST.

Objectives

This study sought to identify the key landscape indicators influencing LST considering a large number of landscape pattern variables and multiple scales.

Methods

This study applied ordinary least squares regression and partial least squares regression to explore a combination of landscape metrics and identify the key indicators influencing LST. A total of 49 Landsat images of the main city of Shenzhen, China were examined at 13 spatial scales.

Results

The landscape composition indicators derived from biophysical proportion, a new metric developed in this study, more effectively determined LST variation than those derived from land cover proportion. Area-related landscape configuration indicators independently characterized LST variation, but did not give much more new information beyond that given by land cover proportion. Shape-related landscape configuration indicators were effective in combination with land cover proportion, but their importance was uncertain when temporal and spatial scales varied.

Conclusions

The influence of landscape configuration on LST exists but should not be overestimated. Comparison of numerous variables at multiple spatiotemporal scales can help identify the influence of multiple landscape characteristics on LST variation.

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

In response to predominantly local and private approaches to landscape change, landscape ecologists should critically assess the multiscalar influences on landscape design.

Objectives

This study develops a governance framework for Nassauer and Opdam’s “Design-in-Science” model. Its objective is to create an approach for examining hierarchical constraints on landscape design in order to investigate linkages among urban greening initiatives, patterns of landscape change, and the broader societal values driving those changes. It aims to provide an integrative and actionable approach for landscape sustainability science.

Methods

This framework is examined through an ethnographic study of public policy processes surrounding the urban tree initiatives in Boston, MA; Philadelphia, PA; and Baltimore, MD.

Results

These initiatives demonstrate the impact of political and economic decentralization on urban landscape patterns. Their collaborative governance approach incorporates diverse resources to implement programming at a fine-scale. The predominant tree giveaway program fragments the urban and regional forest.

Conclusion

Spatial and temporal fragmentation undermines the long-term security of urban greening programs, and it suggests reconsideration of the role of state regimes in driving broad scale spatial planning.

Context

The study of ecosystem services has extended its influence into spatial planning and landscape ecology, the integration of which can offer an opportunity to enhance the saliency, credibility, and legitimacy of landscape ecology in spatial planning issues.

Objectives

This paper presents a conceptual framework suitable for spatial planning in human dominated environments supported by landscape ecological thinking. It seeks to facilitate the integration of ecosystem services into current practice, including landscape metrics as suitable indicators.

Methods

A literature review supported the revision of existing open questions pertaining to ecosystem services as well as their integration into landscape ecology and spatial planning. A posterior reflection of the current state-of-the-art was then used as a basis for developing the spatial planning conceptual framework.

Results and conclusion

The framework is articulated around four phases (characterisation, assessment, design, and monitoring) and three concepts (character, service, and value). It advocates integration of public participation, consideration of “landscape services”, the inclusion of ecosystem disservices, and the use of landscape metrics for qualitative assessment of services. As a result, the framework looks to enhance spatial planning practice by providing: (i) a better consideration of landscape configuration in the supply of services (ii) the integration of anthropogenic services with ecosystem services; (iii) the consideration of costs derived from ecosystems (e.g. disservices); and (iv) an aid to the understanding of ecosystem services terminology for spatial planning professionals and decision makers.

Context

Landscape metrics represent powerful tools for quantifying landscape structure, but uncertainties persist around their interpretation. Urban settings add unique considerations, containing habitat structures driven by the surrounding built-up environment. Understanding urban ecosystems, however, should focus on the habitats rather than the matrix.

Objectives

We coupled a multivariate approach with landscape metric analysis to overcome existing shortcomings in interpretation. We then explored relationships between landscape characteristics and modelled ecosystem service provision.

Methods

We used principal component analysis and cluster analysis to isolate the most effective measures of landscape variability and then grouped habitat patches according to their attributes, independent of the surrounding urban form. We compared results to the modelled provision of three ecosystem services. Seven classes resulting from cluster analysis were separated primarily on patch area, and secondarily by measures of shape complexity and inter-patch distance.

Results

When compared to modelled ecosystem services, larger patches up to 10 ha in size consistently stored more carbon per area and supported more pollinators, while exhibiting a greater risk of soil erosion. Smaller, isolated patches showed the opposite, and patches larger than 10 ha exhibited no additional areal benefit.

Conclusions

Multivariate landscape metric analysis offers greater confidence and consistency than analysing landscape metrics individually. Independent classification avoids the influence of the urban matrix surrounding habitats of interest, and allows patches to be grouped according to their own attributes. Such a grouping is useful as it may correlate more strongly with the characteristics of landscape structure that directly affect ecosystem function.

Context

Wildfires destroy thousands of buildings every year in the wildland urban interface. However, fire typically only destroys a fraction of the buildings within a given fire perimeter, suggesting more could be done to mitigate risk if we understood how to configure residential landscapes so that both people and buildings could survive fire.

Objectives

Our goal was to understand the relative importance of vegetation, topography and spatial arrangement of buildings on building loss, within the fire’s landscape context.

Methods

We analyzed two fires: one in San Diego, CA and another in Boulder, CO. We analyzed Google Earth historical imagery to digitize buildings exposed to the fires, a geographic information system to measure some of the explanatory variables, and FRAGSTATS to quantify landscape metrics. Using logistic regression we conducted an exhaustive model search to select the best models.

Results

The type of variables that were important varied across communities. We found complex spatial effects and no single model explained building loss everywhere, but topography and the spatial arrangement of buildings explained most of the variability in building losses. Vegetation connectivity was more important than vegetation type.

Conclusions

Location and spatial arrangement of buildings affect which buildings burn in a wildfire, which is important for urban planning, building siting, landscape design of future development, and to target fire prevention, fuel reduction, and homeowner education efforts in existing communities. Landscape context of buildings and communities is an important aspect of building loss, and if taken into consideration, could help communities adapt to fire.

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

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

Hill stations are known for their favorable cool climate and natural environments which generate valuable ecosystem services that benefit the local population, tourists and visitors. However, rapid urbanization threatens the sustainability of these highly valued fragile landscapes.

Objectives

We aim to characterize and quantify the changes in the landscape patterns and ecosystem service values (ESVs) of Baguio (Philippines), Bogor (Indonesia), Dalat (Vietnam), and Pyin Oo Lwin (Myanmar), and discuss their implications to landscape sustainability.

Methods

We used remote sensing imagery to map land-use/cover (2001 and 2014), and spatial metrics and gradient analysis to characterize the changes in landscape pattern. We employed a benefit transfer method to estimate the changes in ESV and human-to-ESV ratio. A land-change model was used to simulate different scenarios of future built-up expansions (2014–2030).

Results

The landscapes of Dalat and Pyin Oo Lwin are becoming more fragmented, while those of Baguio and Bogor are getting more aggregated. Dalat had the highest decrease (absolute change) in ESV and H-ESV ratio, while Bogor had the highest percentage decrease (2001–2014).

Conclusions

Rapid urbanization has been a major factor in the landscape transformation of Baguio, Bogor, Dalat and Pyin Oo Lwin. If the current built-up expansion rate will speed up, the decline in future ESV and H-ESV ratio (2014–2030) will be higher than if the rate will continue or slow down. Unless the concept of landscape sustainability is taken seriously in landscape and urban planning, the respective ‘values’ of these precious hill stations will become less and less.

Context

Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent.

Objectives

We highlight milestones in the development of forest dynamics models and identify future research and application opportunities.

Methods

We reviewed milestones in the evolution of forest dynamics models from the 1930s to the present with emphasis on forest growth and yield models and forest landscape models We combined past trends with emerging issues to identify future needs.

Results

Historically, capacity to model forest dynamics at tree, stand, and landscape scales was constrained by available data for model calibration and validation; computing capacity; model applicability to real-world problems; and ability to integrate biological, social, and economic drivers of change. As computing and data resources improved, a new class of spatially explicit forest landscape models emerged.

Conclusions

We are at a point of great opportunity in development and application of forest dynamics models. Past limitations in computing capacity and in data suitable for model calibration or evaluation are becoming less restrictive. Forest landscape models, in particular, are ready to transition to a central role supporting forest management, planning, and policy decisions.

Recommendations

Transitioning forest landscape models to a central role in applied decision making will require greater attention to evaluating performance; building application support staffs; expanding the included drivers of change, and incorporating metrics for social and economic inputs and outputs.

Context

Seagrass landscapes vary substantially in extent and pattern, resulting from depth zonation and hydrodynamic stress gradients and may exhibit threshold behavior in response to changes in physical drivers. Seagrass landscapes persist in a delicate balance between processes of disturbance and recovery and therefore may exhibit behavior typical of classic critical systems.

Objectives

Examine how hydrodynamic drivers and physical setting influence seagrass landscape composition and configuration. Determine if seagrass patch size distributions typify patterns observed for critical systems.

Methods

We used landscape metrics to quantify the spatial configuration of seagrass and then modeled the response of these metrics to wave energy, tidal current speed, and water depth at 62 estuarine sites in North Carolina, USA. Seagrass landscapes were representative of cover types observed in the estuary generated by wave energy.

Results

Percent cover, patch size, and number of patches all declined with increasing wave energy. Threshold behavior occurred at wave energy change points between 675–774 J m^?1. Seagrass landscapes differed in spatial configuration and physical setting, above and below change points. There was moderate support for a power law relationship for patch size distribution across a wide range of seagrass landscape cover and wave energy.

Conclusions

With weather extremes on the rise, much of this estuarine seagrass will be exposed to increased wave energy. Where seagrass exists just below the wave energy change points, increases in wave energy could tip those habitats into a new stable state of lower cover resulting in less cover overall in the estuary.

Context

Landscape spatio-temporal heterogeneity is regarded as an important driver of biodiversity. In agricultural landscapes, the composition and configuration of cultivated fields and their multi-year dynamics should be considered. But the habitat-matrix paradigm in landscape ecology has resulted in little consideration of cropped areas.

Objectives

The main objective of our study was to determine the influences of spatial and multi-year temporal heterogeneity of the crop mosaic on carabid beetle assemblages of agricultural landscapes.

Methods

Carabids were sampled in 40 cereal fields in western France, and their species richness, total abundance and abundance of species groups with different dispersal abilities were measured. For each sampling site, we computed different metrics that characterized crop mosaic spatial and temporal heterogeneity. We quantified relationships between carabid assemblages and heterogeneity metrics and tested their significance.

Results

Total carabid abundance increased with increase in temporal heterogeneity of the crop mosaic. However, all species were not influenced in the same way by spatial and temporal heterogeneity metrics. Some species with high dispersal power such as Trechus quadristriatus were more abundant in landscapes with high spatial heterogeneity, whereas the abundance of less mobile species such as Poecilus cupreus were only positively influenced by temporal crop dynamics.

Conclusions

Our results suggest that both the spatial and temporal heterogeneity of the crop mosaic affects farmland biodiversity, at least for species that use crops during their life cycle or disperse through fields. We highlight the importance of taking this heterogeneity into account in further ecological studies on biodiversity in agricultural landscapes.

Context

Urban environments create a wide range of habitats that harbour a great diversity of plant species, many of which are of alien origin. For future urban planning and management of the green areas within the city, understanding of the spatial distribution of invasive alien species is of great importance.

Objectives

Our main aim was to assess how availability of different ecosystem types within a city area, as well as several parameters describing urban structure interact in determining the cover and identity of invasive alien species.

Methods

We studied the distribution of chosen invasive plant species in a mid-sized city in the Czech Republic, central Europe, on a gradient of equal sized cells from the city centre to its outskirts.

Results

A great amount of variation was explained by spatial predictors but not shared with any measured variables. The species cover of invasive species decreased with increasing proportion of urban greenery and distance from the city centre, but increased with habitat richness; road margins, ruderal sites, and railway sites were richest in invasive species. In contrast, the total number of invasive species in cells significantly decreased with increasing distance from the city centre, but increased with habitat richness.

Conclusions

Our results suggest that different invasive species prefer habitats in the vicinity of the city centre and at its periphery and the spatial structure and habitat quality of the urban landscape needs to be taken into account, in efforts to manage alien plant species invasions in urban environments.

Context

To prevent the area of arable land from crossing the limit of 120 million ha arable land red line, China’s government proposed a linked urban–rural construction land policy. This policy helps to protect the arable land but will impact the rural landscape.

Objective

The objective is to evaluate the effect of the linked urban–rural construction land policy on rural landscape in the future.

Methods

We performed a simulation method to predict the rural landscape pattern changes in Tianjin during 2005–2020 using a cellular automata and multi-agent system model under the scenarios with or without implementing this policy. The landscape metrics were calculated for both scenarios to find the effects caused by this policy.

Results

Following this policy, the Total Area and Large Patch Index of arable land decreased slowly. 65.50% of the occupied arable land can be compensated. For rural settlements, the Mean Patch Area increased to 2.87 times that in 2005. Number of Patches reduced greatly, and 1053 of the total rural settlements distributed along the periphery of Tianjin were reclaimed for arable land during 2005–2020. Aggregation Index increased greatly.

Conclusions

According to the simulation model, the policy is effective on slowing down the loss of total arable land and the process of large arable land fragmentation. The increasing degree of aggregation of rural settlements is beneficial to the optimal allocation of resources and rural centralized management. However, as the rural settlements gather to urban construction land, they are more vulnerable to urban issues.

Context

Habitat loss, fragmentation and degradation are widespread drivers of biodiversity decline. Understanding how habitat quality interacts with landscape context, and how they jointly affect species in human-modified landscapes, is of great importance for informing conservation and management.

Objectives

We used a whole-ecosystem manipulation experiment in the Brazilian Amazon to investigate the relative roles of local and landscape attributes in affecting bat assemblages at an interior-edge-matrix disturbance gradient.

Methods

We surveyed bats in 39 sites, comprising continuous forest (CF), fragments, forest edges and intervening secondary regrowth. For each site, we assessed vegetation structure (local-scale variable) and, for five focal scales, quantified habitat amount and four landscape configuration metrics.

Results

Smaller fragments, edges and regrowth sites had fewer species and higher levels of dominance than CF. Regardless of the landscape scale analysed, species richness and evenness were mostly related to the amount of forest cover. Vegetation structure and configurational metrics were important predictors of abundance, whereby the magnitude and direction of response to configurational metrics were scale-dependent. Responses were ensemble-specific with local-scale vegetation structure being more important for frugivorous than for gleaning animalivorous bats.

Conclusions

Our study indicates that scale-sensitive measures of landscape structure are needed for a more comprehensive understanding of the effects of fragmentation on tropical biota. Although forest fragments and regrowth habitats can be of conservation significance for tropical bats our results further emphasize that primary forest is of irreplaceable value, underlining that their conservation can only be achieved by the preservation of large expanses of pristine habitat.

Context

The importance of landscape context is increasingly recognized when studying relationships between populations. Recent advances in open population modeling allow the employment of landscape metrics to estimate demographic parameters underlying population variation through time and space.

Objectives

Our primary objectives were to (1) describe the influence of landscape metrics on demographic parameters in the grasshopper sparrow (Ammodramus savannarum) and (2) quantify the contributions of these demographic parameters in influencing variation in territory counts through time. We anticipated results would allow us to make recommendations for prioritizing site conservation for this grassland-obligate species of regional conservation concern.

Methods

We employed territory counts spanning 13 years from Massachusetts, USA in open population models to estimate the effects of landscape metrics, territory density, and site quality on three demographic parameters.

Results

The best model estimated highest initial numbers of territories in larger, more distant sites. Overall growth rates <1 were estimated during 1993–2005, while growth rates >1 were estimated in larger sites with a higher habitat quality index and low to medium relative density. Highest rates of annual immigration were estimated for larger sites. Growth rate explained the greatest proportion of variation in territory counts through time.

Conclusions

Open population models allowed us to identify the effects of landscape context on multiple grasshopper sparrow demographic parameters. We encourage further application of these and related models to grassland birds. Beyond maintaining grasslands in the region, we recommend the conservation of large, distant, and previously occupied sites to benefit regional populations.