Context

Winter soundscapes are likely different from soundscapes in other seasons considering wildlife vocalizations (biophony) decrease, wind events (geophony) increase, and winter vehicle noise (technophony) occurs. The temporal variation and spatial relationships of soundscape components to the landscape in winter have not been quantified and described until now.

Objectives

Our objectives were to determine the temporal and spatial variation and acoustic–environmental relationships of a winter soundscape in south-central Alaska.

Methods

We recorded ambient sounds at 62 locations throughout Kenai National Wildlife Refuge (December 2011–April 2012). We calculated the normalized power spectral density in 59,597 recordings and used machine learning to determine acoustic–environmental relationships and produce spatial models of soundscape components.

Results

Geophony was the most prevalent component (84 %) followed by technophony (15 %), and biophony (1 %). Geophony occurred primarily at night, varied little by month, and was strongly associated with lakes. Technophony and biophony had similar temporal variation, peaking in April. Technophony occurred closer to urban areas and at locations with high snowmobile activity. Biophony occurred closer to rivers and was inversely related to snowmobile activity. Over 75 % of sample sites had >1 recordings of airplane or snowmobile noise, mainly in remote areas.

Conclusions

The soundscape displayed distinct patterns across 24-h and monthly timeframes. These patterns were strongly associated with land cover variables which demonstrate discrete acoustic–environmental relationships exhibiting distinct spatial patterns in the landscape. Despite the predominance of geophony, the presence of technophony in this winter soundscape may have significant negative effects to wildlife and wilderness quality.

Context

Despite decades of research, there is an intense debate about the consistency of the hump-shaped pattern describing the relationship between diversity and disturbance as predicted by the intermediate disturbance hypothesis (IDH). Previous meta-analyses have not explicitly considered interactive effects of disturbance frequency and intensity of disturbance on plant species diversity in terrestrial landscapes.

Objective

We conducted meta-analyses to test the applicability of IDH by simultaneously examining the relationship between species richness, disturbance frequency (quantified as time since last disturbance as originally proposed) and intensity of disturbance in forest landscapes.

Methods

The effects of disturbance frequency, intensity, and their interaction on species richness was evaluated using a mixed-effects model.

Results

We found that species richness peaks at intermediate frequency after both high and intermediate disturbance intensities, but the richness-frequency relationship differed between intensity classes.

Conclusions

Our study highlights the need to measure multiple disturbance components that could help reconcile conflicting empirical results on the effect of disturbance on plant species diversity.

Context

Anthropogenic landscape simplification and natural habitat loss can negatively affect wild bees. Alternatively, anthropogenic land-use change may diversify landscapes, creating complementary habitats that maintain overall resource continuity and diversity.

Objectives

We examined the effects of landscape composition, including land-cover diversity and percent semi-natural habitat, on wild bee abundance and species richness within apples, a pollinator-dependent crop. We also explored whether different habitats within diverse landscapes can provide complementary floral resources for bees across space and time.

Methods

We sampled bees during apple bloom over 2 years within 35 orchards varying in surrounding landscape diversity and percent woodland (the dominant semi-natural habitat) at 1 km radii. To assess habitat complementarity in resource diversity and temporal continuity, we sampled flowers and bees within four unique habitats, including orchards, woodlands, semi-natural grasslands, and annual croplands, over three periods from April–June.

Results

Surrounding landscape diversity positively affected both wild bee abundance and richness within orchards during bloom. Habitats in diverse landscapes had different flower communities with varying phenologies; flowers were most abundant within orchards and woodlands in mid-spring, but then declined over time, while flowers within grasslands marginally increased throughout spring. Furthermore, bee communities were significantly different between the closed-canopy habitats, orchards and woodlands, and the open habitats, grasslands and annual croplands.

Conclusions

Our results suggest that diverse landscapes, such as ones with both open (grassland) and closed (woodland) semi-natural habitats, support spring wild bees by providing flowers throughout the entire foraging period and diverse niches to meet different species’ requirements.

Context

Land-use/land-cover (LU/LC) dynamics is one of the main drivers of global environmental change. In the last years, aerial and satellite imagery have been increasingly used to monitor the spatial extent of changes in LU/LC, deriving relevant biophysical parameters (i.e. primary productivity, climate and habitat structure) that have clear implications in determining spatial and temporal patterns of biodiversity, landscape composition and ecosystem services.

Objectives

An innovative hierarchical modelling framework was developed in order to address the influence of nested attributes of LU/LC on community-based ecological indicators.

Methods

Founded in the principles of the spatially explicit stochastic dynamic methodology (StDM), the proposed methodological advances are supported by the added value of integrating bottom-up interactions between multi-scaled drivers.

Results

The dynamics of biophysical multi-attributes of fine-scale subsystem properties are incorporated to inform dynamic patterns at upper hierarchical levels. Since the most relevant trends associated with LU/LC changes are explicitly modelled within the StDM framework, the ecological indicators’ response can be predicted under different social-economic scenarios and site-specific management actions. A demonstrative application is described to illustrate the framework methodological steps, supporting the theoretic principles previously presented.

Conclusions

We outline the proposed multi-model framework as a promising tool to integrate relevant biophysical information to support ecosystem management and decision-making.

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.

Context

Mediterranean forests have been fragmented intensively over time, thereby yielding small and isolated forest remnants. They host a rich variety of epiphytes, which may be affected by landscape structure. Previous studies have analyzed the influence of habitat quality on these epiphytic communities, but there is little knowledge of the effects of other fragment features.

Objectives

We evaluated the impacts of forest loss and fragmentation on epiphytic communities (lichens and bryophytes) at plot and fragment scales after controlling the variation in forest structure and management.

Methods

We considered 40 fragments of dense oak forests in a human-modified landscape. We quantified their spatial attributes (size and shape), the quality of the surrounding matrix and the forest stand structure. We modeled community traits, and the presence and abundance of species at fragment and plot scales.

Results

Fragment size, shape, and the quality of the surrounding matrix were key factors that affected epiphytic richness and diversity. Larger and more regularly shaped fragments hosted the richest and most diverse communities, possibly offering a larger core area and thus favoring the entry of typical forest species. A high-contrast matrix was only favorable in small fragments, probably allowing the arrival of propagules. The species-level response was highly variable.

Conclusions

Landscape structure provides powerful explanations of the richness and diversity losses among epiphytes. Forest management should ensure the retention of the largest possible continuous forests. The management strategy of the matrix will depend on the conservation goal, since we observed different effects related with quality and fragment size.

Context

The Brazilian Cerrado, a global biodiversity hotspot, is being converted to agricultural production. Amphibians in particular are susceptible to agricultural practices that threaten both their wetland and upland habitats. Although local site variables are important for determining species occurrence, site occupancy is also mediated by the broader landscape and management context in which the site occurs.

Objectives

Investigate the relative effects of broad-, intermediate-, and local-scale factors on species occurrence for pond-breeding anurans within different landscapes across an agricultural-disturbance gradient in the Cerrado.

Methods

Ponds were surveyed for adult anurans over 3 years within 18 landscapes (each 625 km²) that varied in their degree of agricultural land use (landscape context). We analyzed species distribution models for eight pond-breeding anurans, using hierarchical binomial generalized linear models.

Results

The broader landscape context had a significant effect on the incidence of pond-breeding anurans, even after accounting for variation in other environmental factors at more local (pond) or intermediate (1-km²) scales. The top-ranked models for most species included some combination of broad-, intermediate- and local-scale factors, however. These covariates influenced species occurrence in different ways, with the response to agricultural disturbance varying among species. Although some species were negatively affected, others appeared to benefit from agricultural activities that increased breeding habitat (e.g., impoundments to provide water for cattle).

Conclusions

Landscape context, the degree to which landscapes have been transformed by agricultural land use, has a major influence on the distribution of pond-breeding anurans in the Brazilian Cerrado.

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.