Landscape composition mediates movement and habitat selection in bobcats (<Emphasis Type="Italic">Lynx rufus</Emphasis>): implications for conservation planning

Context

The analysis of individual movement choices can be used to better understand population-level resource selection and inform management.

Objectives

We investigated movements and habitat selection of 13 bobcats in Vermont, USA, under the assumption individuals makes choices based upon their current location. Results were used to identify “movement-defined” corridors.

Methods

We used GPS-collars and GIS to estimate bobcat movement paths, and extracted statistics on land cover proportions, topography, fine-scale vegetation, roads, and streams within “used” and “available” space surrounding each movement path. Compositional analyses were used to determine habitat preferences with respect to landcover and topography; ratio tests were used to determine if used versus available ratios for vegetation, roads, and streams differed from 1. Results were used to create travel cost maps, a primary input for corridor analysis.

Results

Forested and scrub-rock land cover were most preferred for movement, while developed land cover was least preferred. Preference depended on the composition of the “available” landscape: Bobcats moved?>?3 times more quickly through forest and scrub-rock habitat when these habitats were surrounded by agriculture or development than when the available buffer was similarly composed. Overall, forest edge, wetland edge and higher stream densities were selected, while deep forest core and high road densities were not selected. Landscape-scale connectivity maps differed depending on whether habitat suitability, preference, or selection informed the travel cost map.

Conclusions

Both local and landscape scale land cover characteristics affect habitat preferences and travel speed of bobcats, which in turn can inform management and conservation activities.

     

Activating landscape ecology: a governance framework for design-in-science

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.

     

Multi-scale Mexican spotted owl (<Emphasis Type="Italic">Strix occidentalis lucida</Emphasis>) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Context

Organisms commonly respond to their environment across a range of scales, however many habitat selection studies still conduct selection analyses using a single-scale framework. The adoption of multi-scale modeling frameworks in habitat selection studies can improve the effectiveness of these studies and provide greater insights into scale-dependent relationships between species and specific habitat components.

Objectives

Our study assessed multi-scale nest/roost habitat selection of the federally “Threatened” Mexican spotted owl (Strix occidentalis lucida) in northern Arizona, USA in an effort to provide improved conservation and management strategies for this subspecies.

Methods

We conducted multi-scale habitat modeling to assess habitat selection by Mexican spotted owls using survey data collected by the USFS. Each selected covariate was included in multi-scale models at their “characteristic scale” and we used an all-subsets approach and model selection framework to assess habitat selection.

Results

The “characteristic scale” identified for each covariate varied considerably among covariates and results from multi-scale models indicated that percent canopy cover and slope were the most important covariates with respect to habitat selection by Mexican spotted owls. Multi-scale models consistently outperformed their analogous single-scale counterparts with respect to the proportion of deviance explained and model predictive performance.

Conclusions

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective conservation and management strategies.

     

Landscape-scale modelling of agroforestry ecosystems services in Swiss orchards: a methodological approach

Context

Agroforestry systems in temperate Europe are known to provide both, provisioning and regulating ecosystem services (ES). Yet, it is poorly understood how these systems affect ES provision at a landscape scale in contrast to agricultural practises.

Objectives

This study aimed at developing a novel, spatially explicit model to assess and quantify bundles of provisioning and regulating ES provided by landscapes with and without agroforestry systems and to test the hypothesis that agroforestry landscapes provide higher amounts of regulating ES than landscapes dominated by monocropping.

Methods

Focussing on ES that are relevant for agroforestry and agricultural practices, we selected six provisioning and regulating ES—“biomass production”, “groundwater recharge”, “nutrient retention”, “soil preservation”, “carbon storage”, “habitat and gene pool protection”. Algorithms for quantifying these services were identified, tested, adapted, and applied in a traditional cherry orchard landscape in Switzerland, as a case study. Eight landscape test sites of 1 km?×?1 km, four dominated by agroforestry and four dominated by agriculture, were mapped and used as baseline for the model.

Results

We found that the provisioning ES, namely the annual biomass yield, was higher in landscape test sites with agriculture, while the regulating ES were better represented in landscape test sites with agroforestry. The differences were found to be statistically significant for the indicators annual biomass yield, groundwater recharge rate, nitrate leaching, annual carbon sequestration, flowering resources, and share of semi-natural habitats.

Conclusions

This approach provides an example for spatially explicit quantification of provisioning and regulating ES and is suitable for comparing different land use scenarii at landscape scale.

     

Multi-scale feedbacks between tree regeneration traits and herbivore behavior explain the structure of pasture-woodland mosaics

Context

The pasture-woodlands of Central Europe are low-intensity grazing systems in which the structural richness of dynamic forest-grassland mosaics is causal for their high biodiversity. Distinct mosaic patterns in Picea abies- and Fagus sylvatica-dominated pasture-woodlands in the Swiss Jura Mountains suggest a strong influence of tree species regeneration ecology on landscape structural properties. At the landscape scale, however, cause-effect relationships are complicated by habitat selectivity of livestock.

Objectives

We asked which tree species regeneration traits and what kind of feedbacks among local-scale vegetation dynamics and landscape-scale herbivore behavior are causal for the contrasted landscape structural characteristics of Picea- and Fagus-dominated pasture-woodlands.

Methods

We performed simulation experiments of mosaic pattern formation in both pasture-woodland types. The regeneration traits, namely dispersal distance, resistance to browsing and tolerance to shade, and the rules for habitat selection of cattle were modified and the corresponding shifts in landscape structure were analyzed.

Results

Dispersal distance showed a significant, but only local, effect promoting forest fringe formation. Saplings’ resistance to browsing mainly determined overall tree cover, but did not influence landscape structure. At the landscape scale, both shade tolerance of saplings and selective habitat use by cattle were responsible for forest-grassland segregation: high shade tolerance triggered segregation, whereas non-selective habitat use hindered it.

Conclusions

Existing local-scale theory on pasture-woodland dynamics is complemented by an herbivore-vegetation feedback among spatial scales. In low-intensity pastures, where large herbivores are preferentially “grazers” and trees form dense canopies, an intrinsic trend towards forest-grassland segregation at the expense of forest-grassland ecotones is predicted.

     

What determines the spatial extent of landscape effects on species?

Context

Landscape ecologists are often interested in measuring the effects of an environmental variable on a biological response; however, the strength and direction of effect depend on the size of the area within which the environmental variable is measured. Thus a central objective is to identify the optimal spatial extent within which to measure the environmental variable, i.e. the “scale of effect”.

Objectives

Our objectives are (1) to provide a comprehensive summary of the hypotheses concerning what determines the scale of effect, (2) to provide predictions that can be tested in empirical studies, and (3) to show, with a review of the literature, that most of these predictions have so far been inadequately tested.

Methods

We propose 14 predictions derived from five hypotheses explaining what determines the scale of effect, and review the literature (if any) supporting each prediction. These predictions involve five types of factors: (A) species traits, (B) landscape variables, (C) biological responses (e.g. abundance vs. occurrence), (D) indirect influences, and (E) regional context of the study. We identify methodological issues that hinder estimation of the scale of effect.

Results

Of the 14 predictions, only nine have been tested empirically and only five have received some empirical support. Most support is from simulation studies. Empirical evidence usually does not support predictions.

Conclusions

The study of the spatial scale at which landscape variables influence biological outcomes is in its infancy. We provide directions for future research by clarifying predictions concerning the determinants of the scale of effect.

     

Multi-scale habitat selection modeling: a review and outlook

Context

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Objectives

Our goals in this review are to describe the conceptual origins of multi-scale habitat selection modeling, evaluate the current state-of-the-science, and suggest ways forward to improve analysis of scale-dependent habitat selection.

Methods

We reviewed more than 800 papers on habitat selection from 23 major ecological journals published between 2009 and 2014 and recorded a number of characteristics, such as whether they addressed habitat selection at multiple scales, what attributes of scale were evaluated, and what analytical methods were utilized.

Results

Our results show that despite widespread recognition of the importance of multi-scale analyses of habitat relationships, a large majority of published habitat ecology papers do not address multiple spatial or temporal scales. We also found that scale optimization, which is critical to assess scale dependence, is done in less than 5 % of all habitat selection modeling papers and less than 25 % of papers that address “multi-scale” habitat analysis broadly defined.

Conclusions

Our review confirms the existence of a powerful conceptual foundation for multi-scale habitat selection modeling, but that the majority of studies on wildlife habitat are still not adopting multi-scale frameworks. Most importantly, our review points to the need for wider adoption of a formal scale optimization of organism response to environmental variables.

     

Bat richness and activity in heterogeneous landscapes: guild-specific and scale-dependent?

Context

The conversion of natural environments into agricultural land has profound effects on the composition of the landscape, often resulting in a mosaic of human-altered and natural habitats. The response to these changes may however vary among organisms. Bats are highly vagile, and their requirements often imply the use of distinct habitats, which they select responding to both landscape and local features.

Objectives

We aimed to identify which features influence bat richness and activity within Baixo Vouga Lagunar, a heterogeneous landscape located on the Central-North Portuguese coast, and to investigate if that influence varies across a gradient of focal scales.

Methods

We sampled bats acoustically, while simultaneously sampling insects with light traps. We assessed the relationships between species richness, bat activity, and activity of eco-morphological guilds with landscape and local features, across four scales.

Results

Our results revealed both scale- and guild-dependent responses of bats to landscape and local features. At broader scales we found positive associations between open-space foraging bats and habitat heterogeneity and between edge-space foraging bats and greater edge lengths. Woodland cover and water availability at an intermediate scale and weather conditions and insect abundance at a local scale were the factors that mostly influenced the response variables.

Conclusions

Globally, our results suggest that bats are sensitive to local resource availability and distribution, while simultaneously reacting to landscape features acting at coarser scales. Finally, our results suggest that the responses given by bats are guild-dependent, and some habitats act as keystone structures for bats within this mosaic.

     

Modeling local spatial patterns of wild bee diversity in Pennsylvania apple orchards

Context

The positive correlation between landscape area of semi-natural habitat and wild pollinator richness and abundance in agroecosystems has been well studied. However, we lack a deep understanding of local scale floral resource and nest provisioning for wild bees necessary to optimize implementation of pollinator conservation practices.

Objectives

The primary objective of this study was to use a spatially interactive landscape pollination model (hereafter, the Lonsdorf model) to represent field scale spatial patterns of wild bee abundance and richness within a heterogeneous landscape in the mid-Atlantic USA.

Methods

We parameterized the Lonsdorf model with high resolution aerial imagery and insight from a previously published floristic study. To test the Lonsdorf model predictions, field studies were conducted to measure wild bee abundance and species richness in apple orchards as a function of distance from a forest edge.

Results

Field measurements indicated apple pollinator abundance and species richness significantly decreased with increasing distance from the forest edge. The Lonsdorf model pollination service score was highly sensitive to changes in resource provisioning in orchard and non-crop areas, and including resource rich forest and forest edge habitats in the model significantly improved pollination service estimates.

Conclusions

We demonstrated a novel application of the Lonsdorf model at a field scale to predict trends in pollination service provisioning as a factor of local habitat features. With sufficiently detailed inputs, the Lonsdorf model is a promising tool to quantify field scale pollination service deficits, guiding more cost effective habitat supplementation and other conservation efforts.

     

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition,landscape configuration,and bioenergy crop area

Context

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees.

Objectives

Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations.

Methods

Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7, 23.5 and 28.8% of agricultural land converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape.

Results

Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale.

Conclusions

Strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.

     

Multi-scale prediction of landscape resistance for tiger dispersal in central India

Context

Connectivity models for animal movement frequently use resistance surfaces, but rarely incorporate actual movement data and multiple scale drivers of landscape resistance.

Objectives

Using GPS data, we developed a multi-scale model of landscape resistance for tiger (Panthera tigris) dispersal in central India and evaluated the performance, interpretation and predictions against single scale models.

Methods

Six dispersing tiger paths were subjected to a path level analysis with conditional logistic regression to parameterize a resistance surface. We evaluated for 21 scales of available habitat and selected the best scale for each variable. We derived a scale-optimized multivariate path selection function and predicted landscape resistance across the landscape.

Results

The tigers preferred to move along areas with forest cover at relatively high elevations along the ridges with rugged topography at broad scale, while avoiding areas with agriculture-village matrix at fine scale. We found that the scale that was most supported by Akaike’s information criterion was not always the scale that maximized the magnitude (effect size) of the relationship. Further, the multi-scale optimized model differed substantially from the single scale models in terms of variable importance, magnitude of coefficients and predictions of connectivity.

Conclusions

Our results demonstrate that the variables in landscape resistance models produce markedly different predictions of population connectivity depending on the scales of analyses and interpretation. Thus, scale optimization in parameterization is critical for appropriate inferences and sound management strategies.

     

Thresholds and hotspots for shrub restoration following a heterogeneous megafire

Context

Reestablishing foundational plant species through aerial seeding is an essential yet challenging step for restoring the vast semiarid landscapes impacted by plant invasions and wildfire-regime shifts. A key component of the challenge stems from landscape variability and its effects on plant recovery.

Objectives

We assessed landscape correlates, thresholds, and tipping points for sagebrush presence from fine-scale sampling across a large, heterogeneous area burned the previous year, where we were able to quantify soil surface features that are typically occluded yet can strongly affect recovery patterns.

Methods

Hypothesis testing and binary-decision trees were used to evaluate factors affecting initial sagebrush establishment, using 2171 field plots (totaling?~?2,000,000 m² sampled) over a 113,000-ha region.

Results

Sagebrush established in 50% of plots where it was seeded, a?>?12-fold greater establishment frequency than in unseeded areas. Sagebrush establishment was enhanced in threshold-like ways by elevation (>?1200 m ASL), topographic features that alter heatload and soil water, and by soil-surface features such as “fertile islands” that bore the imprint of pre-fire sagebrush. Sagebrush occupancy had a negative, linear relationship with exotic-annual grass cover and parabolic relationship with perennial bunchgrasses (optimal at 40% cover).

Conclusions

Our approach revealed interactive, ecological relationships such as novel soil-surface effects on first year establishment of sagebrush across the burned landscape, and identified “hot spots” for recovery. The approach could be expanded across sites and years to provide the information needed to explain past seeding successes or failures, and in designing treatments at the landscape scale.

     

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.

     

Disaggregating ecosystem services and disservices in the cultural landscapes of southwestern Ethiopia: a study of rural perceptions

Context

Cultural landscapes provide essential ecosystem services to local communities, especially in poor rural settings. However, potentially negative impacts of ecosystems—or disservices—remain inadequately understood. Similarly, how benefit–cost outcomes differ within communities is unclear, but potentially important for cultural landscape management.

Objectives

Here we investigated whether distinct forest ecosystem service–disservice outcomes emerge within local communities. We aimed to characterize groups of community members according to service–disservice outcomes, and assessed their attitudes towards the forest.

Methods

We interviewed 150 rural households in southwestern Ethiopia about locally relevant ecosystem services (provisioning services) and disservices (wildlife impacts). Households were grouped based on their ecosystem service–disservice profiles through hierarchical clustering. We used linear models to assess differences between groups in geographic and socioeconomic characteristics, as well as attitudes toward the forest.

Results

We identified three groups with distinct ecosystem service–disservice profiles. Half of the households fell into a “lose–lose” profile (low benefits, high costs), while fewer had “lose–escape” (low benefits, low costs) and “win–lose” (high benefits, high costs) profiles. Location relative to forest and altitude explained differences between the “lose–escape” profile and other households. Socioeconomic factors were also important. “Win–lose” households appeared to be wealthier and had better forest use rights compared to “lose–lose” households. Attitudes towards the forest did not differ between profiles.

Conclusions

Our study demonstrates the importance of disaggregating both ecosystem services and disservices, instead of assuming that communities receive benefits and costs homogenously. To manage cultural landscapes sustainably, such heterogeneity must be acknowledged and better understood.

     

Influences of scale on bat habitat relationships in a forested landscape in Nicaragua

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.

     

Butterfly assemblages in residential gardens are driven by species’ habitat preference and mobility

Context

Understanding the factors contributing to maintaining biodiversity is crucial to mitigate the impact of anthropogenic disturbances. Representing large proportions of green area in highly modified landscapes, residential gardens are often seen as local habitats that can contribute to larger networks of suitable environments at the landscape scale.

Objectives

We investigated the impact of the landscape context on butterfly communities observed in residential gardens, taking into account garden characteristics, land-use types and presence of linear features in the surrounding landscape. We examined how species traits affected butterflies’ response to landscape context and habitat quality.

Methods

We performed a cross-scale study, based on citizen science data documenting butterfly species composition and abundance in 920 gardens across France. We examined the effect of garden quality, the area of different land-use types and the length of linear elements measured at three scales within the surrounding landscape. Species were grouped according to their habitat preference and mobility.

Results

Urbanization negatively affected total species richness and the abundance of butterfly in each group. This was related to declining habitat quality and reduced area of suitable habitat in the surrounding landscape. The magnitude of this effect, however, was negatively correlated with mobility, a trait related to habitat preference. The spatial scale at which landscape context best explained variation in butterfly abundance changed with species’ habitat preference.

Conclusions

This study highlights the importance of preserving high quality habitats in altered landscapes and considering species’ mobility and habitat preference when assessing the impact of landscapes on butterfly communities.

     

Spatial configuration matters: a test of the habitat amount hypothesis for plants in calcareous grasslands

Context

A recent hypothesis, the habitat amount hypothesis, predicts that the total amount of habitat in the landscape can replace habitat patch size and isolation in studies of species richness in fragmented landscapes.

Objectives

To test the habitat amount hypothesis by first evaluating at which spatial scale the relationship between species richness in equal-sized sample quadrats and habitat amount was the strongest, and then test the importance of spatial configuration of habitat—measured as local patch size and isolation—when habitat amount was taken into account.

Methods

A quasi-experimental setup with 20 habitat patches of dry calcareous grasslands varying in patch size, patch isolation and habitat amount at the landscape scale was established in the inner Oslo fjord, Southern Norway. We recorded species richness of habitat specialists of vascular plants in equal-sized sample quadrats and analysed the relationship between species richness, habitat amount in the landscape and patch size and isolation.

Results

Although the total amount of habitat in a 3 km-radius around the local patch was positively related to species richness in the sample quadrats, local patch size had an additional positive effect, and the effect of patch size was higher when the amount of habitat within the 3 km-radius was high than when it was low.

Conclusions

In our study system of specialist vascular plants in dry calcareous grasslands, we do not find support for the habitat amount hypothesis.

     

multifit: an R function for multi-scale analysis in landscape ecology

Context

Multi-scale analyses are a common approach in landscape ecology. Their aim is to find the appropriate spatial scale for a particular landscape attribute in order to perform a correct interpretation of results and conclusions.

Objectives

I present an R function that performs statistical analysis relating a biological response with a landscape attribute at a set of specified spatial scales and extracts the statistical strength of the models through a specified criterion index. Also, it draws a plot with the value of these indexes, allowing the user to choose the most appropriate spatial scale. This paper introduces the usage of multifit and demonstrates its functionality through a case study.

Conclusions

The spatial scale at which ecologists conduct studies may change study outcomes and conclusions. Because of this, landscape ecologists commonly conduct multi-scale studies in order to establish an appropriate spatial scale for particular biological or ecological responses. The tool presented here allows ecologists to simultaneously run several statistical models for a response variable and a specified set of spatial scales, automating the process of multi-scale analysis.

     

Estimating the spatial scales of landscape effects on abundance

Context

Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering approach does not acknowledge that the influence of surrounding landscape features should diminish with distance, and it does not yield an estimate of the unknown scale parameters.

Objectives

The purpose of this paper is to present an approach that allows for statistical inference about the scales at which landscape variables affect abundance.

Methods

Our method uses smoothing kernels to average landscape variables around focal sites and uses maximum likelihood to estimate the scale parameters of the kernels and the effects of the smoothed variables on abundance. We assessed model performance using a simulation study and an avian point count dataset.

Results

The simulation study demonstrated that estimators are unbiased and produce correct confidence interval coverage except in the rare case in which there is little spatial autocorrelation in the landscape variable. Canada warbler abundance was more highly correlated with site-level measures of NDVI than landscape-level NDVI, but the reverse was true for elevation. Canada warbler abundance was highest when elevation in the surrounding landscape, defined by an estimated Gaussian kernel, was between 1300 and 1400 m.

Conclusions

Our method provides a rigorous way of formally estimating the scales at which landscape variables affect abundance, and it can be embedded within most classes of statistical models.

     

Soundscapes reveal disturbance impacts: biophonic response to wildfire in the Sonoran Desert Sky Islands

Context

While remote sensing imagery is effective for quantifying land cover changes across large areas, its utility for directly assessing the response of animals to disturbance is limited. Soundscapes approaches—the recording and analysis of sounds in a landscape—could address this shortcoming.

Objectives

In 2011, a massive wildfire named “the Horseshoe 2 Burn” occurred in the Chiricahua National Monument, Arizona, USA. We evaluated the impact of this wildfire on acoustic activity of animal communities.

Methods

In 2013, soundscape recordings were collected over 9 months in 12 burned and 12 non-burned sites in four ecological systems. The seasonal and diel biological acoustic activity were described using the “Bioacoustic Index”, a detailed aural analysis of sound sources, and a new tool called “Sonic Timelapse Builder” (STLB).

Results

Seasonal biophony phenology showed a diurnal peak in June and a nocturnal peak in October in all ecological systems. On June mornings, acoustic activity was lower at burned than at non-burned sites in three of four ecological systems, due to a decreased abundance of cicadas directly impacted by the death of trees. Aural analyses revealed that 55% of recordings from non-burned sites contained insect sounds compared to 18% from burned sites. On October nights, orthopteran activity was more prevalent at some burned sites, possibly due to post-fire emergence of herbaceous.

Conclusions

Soundscape approaches can help address long-term conservation issues involving the responses of animal communities to wildfire. Acoustic methods can serve as a valuable complement to remote sensing for disturbance-based landscape management.