A practical method for creating a digital topographic surface for ecological plots using ground-based measurements

Context

Digital elevation models (DEMs) are widely used in landscape ecology to link topographic features with biotic and abiotic factors. However, to date, high-resolution, affordable, and easy to process elevation data are not available for many regions.

Objectives

Here we propose a field-based method for efficiently and inexpensively collecting or analysing already existing slope data. We compare the field approach to two commonly used remote sensing techniques to test the similarly of the DEMs using different methods.

Methods

To provide an ecological example of the method, we selected four 1-ha forest plots and compared the DEM generated by using our field method with those derived from: (i) coarse (~ 30 m pixel) data from the Shuttle Radar Topography Mission and (ii) high-resolution (~ 1 m) data from Light Detection and Ranging devices (LiDAR).

Results

Field- and LiDAR-based DEMs showed strong concordance in two of the four sites. The sites where field-based and LiDAR DEMs substantially differed, suffered from relatively few LiDAR sampling points. Diagnostic tests suggested that the field–LiDAR discrepancy was due to dense over-storey vegetation, which reduced LiDAR’s accuracy due to a failure to penetrate the forest canopy adequately in some areas.

Conclusions

Our method has the advantage of being quick and cheap to collect yet able to produce small-scale (plot-scale) DEMs of high quality. By using the R-code we have provided, ecologists will be able to use slope data (collected using any means) to generate a DEM without the need of specific skills in spatial sciences.

     

The KDE+ software: a tool for effective identification and ranking of animal-vehicle collision hotspots along networks

Context

Objective identification of locations on transportation networks, where animal-vehicle collisions (AVC) occur more frequently than expected (hotspots), is an important step for the effective application of mitigation measures.

Objectives

We introduce the KDE+ software which is a programmed version of the KDE+ method for effective identification of traffic accident hotspots. The software can be used in order to analyze animal-vehicle collision data.

Methods

The KDE+ method is based on principles of Kernel Density Estimation (KDE). The symbol ‘+’ indicates that the method allows for the objective selection of significant clusters and for the ranking of the hotspots. It is also simultaneously applicable to an unlimited number of road segments.

Results

We applied the KDE+ method to the entire Czech road network. The hotspots were ranked according to their significance. The resulting hotspots represent a short overall road length which should require a more detailed assessment in the field. The 100 most important clusters of AVC represent, for example, only 19.7 km of the entire road network (37,469 km).

Conclusions

We present an objective method for hotspots identification which can be used for AVC data. This method is unique because it determines the significance level of hotspots in an objective way. The prioritization of hotspots allows a transportation manager to effectively allocate resources to a feasible number of identified hotspots. We describe the software, data preparation and present the KDE+ application to AVC data.

     

Teaching landscape ecology: the importance of field-oriented,inquiry-based approaches

Context

Landscape ecology has traditionally been taught through theoretical classes or computer labs. On the other hand, field labs have been generally less used as a way of teaching landscape ecology concepts.

Objectives

We show that field labs with an inquiry-based approach, where students are involved in the investigation, are feasible for training students in landscape ecology. We evaluated how common field labs are in landscape ecology courses, and also their contribution for student learning.

Methods

We evaluated whether field labs are used in landscape ecology courses by scanning available syllabi. We also used outcomes from a course offered in Brazil to show how field labs can be integrated into landscape ecology courses.

Results

Only 18.2 % of the 44 syllabi we found had field labs. The case study developed in Brazil showed that field labs allowed students to develop important skills, including the ability to design field studies, choose appropriate scales of analysis, detect ecological patterns, and judge multiple hypotheses.

Conclusions

Field labs are still uncommon in landscape ecology courses, but they can be a useful tool to teach landscape ecology concepts and to help students developing the necessary skills to do research. We offer recommendations regarding how to incorporate field labs in landscape ecology courses.

     

Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest,California

Context

Spatial scale and pattern play important roles in forest aboveground biomass (AGB) estimation in remote sensing. Changes in the accuracy of satellite images-estimated forest AGBs against spatial scales and pixel distribution patterns has not been evaluated, because it requires ground-truth AGBs of fine resolution over a large extent, and such data are difficult to obtain using traditional ground surveying methods.

Objectives

We intend to quantify the accuracy of AGB estimation from satellite images on changing spatial scales and varying pixel distribution patterns, in a typical mixed coniferous forest in Sierra Nevada mountains, California.

Methods

A forest AGB map of a 143 km² area was created using small-footprint light detection and ranging. Landsat Thematic Mapper images were chosen as typical examples of satellite images, and resampled to successively coarser resolutions. At each spatial scale, pixels forming random, uniform, and clustered spatial patterns were then sampled. The accuracies of the AGB estimation based on Landsat images associated with varying spatial scales and patterns were finally quantified.

Results

The changes in the accuracy of AGB estimation from Landsat images are not monotonic, but increase up to 60–90 m in spatial scale, and then decrease. Random and uniform spatial patterns of pixel distributions yield better accuracy for AGB estimation than clustered spatial patterns. The corrected NDVI (NDVIc) was the best predictor of AGB estimation.

Conclusions

A spatial scale of 60–90 m is recommended for forest AGB estimation at the Sierra Nevada mountains using Landsat images and those with similar spectral resolutions.

     

Diversity–disturbance relationship in forest landscapes

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.

     

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.

     

Spatial patterns of cultural ecosystem services provision in Southern Patagonia

Context

Although there is a need to develop a spatially explicit methodological approach that addresses the social importance of cultural ecosystem services for regional planning, few studies have analysed the spatial distribution on the cultural ecosystem services based on social perceptions.

Objective

The main objective of this study was to identify cultural ecosystem service hot-spots, and factors that characterize such hot-spots and define the spatial associations between cultural ecosystem services in Southern Patagonia (Argentina).

Methods

The study was carried out in Southern Patagonia (243.9 thousand km²) located between 46° and 55° SL with the Andes mountains on the western fringe and the Atlantic Ocean on the eastern fringe of the study area. The study region has a range of different vegetation types (grasslands, shrub-lands, peat-lands and forests) though the cold arid steppe is the main vegetation type. We used geo-tagged digital images that local people and visitors posted in the Panoramio web platform to identify hot-spots of four cultural ecosystem services (aesthetic value, existence value, recreation and local identity) and relate these hot-spots with social and biophysical landscape features.

Results

Aesthetic value was the main cultural service tagged by people, followed by the existence value for biodiversity conservation, followed by local identity and then recreational activity. The spatial distribution of these cultural ecosystem services are associated with different social and biophysical characteristics, such as the presence of water bodies, vegetation types, marine and terrestrial fauna, protected areas, urbanization, accessibility and tourism offer. The most important factors are the presence of water in Santa Cruz and tourism offer in Tierra del Fuego.

Conclusions

Our results demonstrate that this methodology is useful for assessing cultural ecosystem services at the regional scale, especially in areas with low data availability and field accessibility, such as Southern Patagonia. We also identify new research challenges that can be addressed in cultural ecosystem services research through the use of this method.

     

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.

     

Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations

Context

Methods for detecting contemporary, fine-scale population genetic structure in continuous populations are scarce. Yet such methods are vital for ecological and conservation studies, particularly under a changing landscape.

Objectives

Here we present a novel, spatially explicit method that we call landscape relatedness (LandRel). With this method, we aim to detect contemporary, fine-scale population structure that is sensitive to spatial and temporal changes in the landscape.

Methods

We interpolate spatially determined relatedness values based on SNP genotypes across the landscape. Interpolations are calculated using the Bayesian inference approach integrated nested Laplace approximation. We empirically tested this method on a continuous population of brown bears (Ursus arctos) spanning two counties in Sweden.

Results

Two areas were identified as differentiated from the remaining population. Further analysis suggests that inbreeding has occurred in at least one of these areas.

Conclusions

LandRel enabled us to identify previously unknown fine-scale structuring in the population. These results will help direct future research efforts, conservation action and aid in the management of the Scandinavian brown bear population. LandRel thus offers an approach for detecting subtle population structure with a focus on contemporary, fine-scale analysis of continuous populations.

     

Locating wildlife crossings for multispecies connectivity across linear infrastructures

Context

Linear transportation infrastructures traverse and separate wildlife populations, potentially leading to their short- and long-term decline at local and regional scales. To attenuate such effects, we need wildlife crossings suitable for a wide range of species.

Objectives

We propose a method for identifying the best locations for wildlife crossings along linear infrastructures so as to improve the connectivity of species with varying degrees of mobility and living in different habitats. We evaluate highway impacts on mammal species.

Methods

The study area is the Grésivaudan Valley, France. We used allometric relationships to create eight virtual species and model their connectivity networks, developing a nested method defining populations by daily travel distances and connecting them by dispersal. We tested the gain in connectivity for each species produced by 100 and 600 crossing locations respectively in crossable, i.e. with crossing infrastructures, and uncrossable highway scenarios. We identified the crossings that optimize the connectivity of the maximum number of species combining the results in multivariate analyses.

Results

Highly mobile species needing a large habitat area were the most sensitive to highways. The importance of locomotive performance in structuring the graphs decreased with highway impermeability. Depending on the species, the best locations improved connectivity by 0–10 and 2–75 % respectively in the crossable and uncrossable scenarios. Compromise locations were found for seven of the eight species in both scenarios.

Conclusions

This method could guide planners in identifying crossing locations to increase the connectivity of different species at regional scales over the long term.

     

Spatial prioritisation for conserving ecosystem services: comparing hotspots with heuristic optimisation

Context

The variation in spatial distribution between ecosystem services can be high. Hence, there is a need to spatially identify important sites for conservation planning. The term ‘ecosystem service hotspot’ has often been used for this purpose, but definitions of this term are ambiguous.

Objectives

We review and classify methods to spatially delineate hotspots. We test how spatial configuration of hotspots for a set of ecosystem services differs depending on the applied method. We compare the outcomes to a heuristic site prioritisation approach (Marxan).

Methods

The four tested hotspot methods are top richest cells, spatial clustering, intensity, and richness. In a conservation scenario we set a target of conserving 10 % of the quantity of five regulating and cultural services for the forest area of Telemark county, Norway.

Results

Spatial configuration of selected areas as retrieved by the four hotspots and Marxan differed considerably. Pairwise comparisons were at the lower end of the scale of the Kappa statistic (0.11–0.27). The outcomes also differed considerably in mean target achievement, cost-effectiveness in terms of land-area needed per unit target achievement and compactness in terms of edge-to-area ratio.

Conclusions

An ecosystem service hotspot can refer to either areas containing high values of one service or areas with multiple services. Differences in spatial configuration among hotspot methods can lead to uncertainties for decision-making. This also has consequences for analysing the spatial co-occurrence of hotspots of multiple services and of services and biodiversity.

     

Spatial assessment of aesthetic services in a complex mountain region: combining visual landscape properties with crowdsourced geographic information

Context

Human and natural systems interact at multiple scales which are context specific in relation to ecosystem service supply. Scenic beauty is recognised as a cultural ecosystem service whose aesthetic value is perceived at a holistic landscape level.

Objectives

In this study we provide methodological advancements for assessing the relationship between landscape visual character and scenic beauty based on crowdsourced geographic information. The final aim is to demonstrate, through a case study application, an empirical method for mapping the scenic beauty of complex mountain landscapes from the perspective of observers which are realistically exposed to the environment being evaluated.

Methods

We propose a viewshed based approach which relies on visual indicators and the location of visitors retrieved by public image storage analysis. A cluster analysis was used to integrate visual characters of the landscape and visiting users’ preferences.

Results

Four different typologies of landscapes were finally characterized by distinct values of visual indicators. The spatial distribution of the landscape typologies presented a clustered pattern, allowing a regionalization of the landscape characters. The analysis of the visiting users’ provenance revealed that visual scale, naturalness and ephemera attract mainly foreign users, while imageability, complexity and historicity attract mostly domestic and local users.

Conclusions

The combination of crowdsourced images with visual indicators allows a systematic analysis of landscape scenic beauty properties. In all, by understanding how specific landscape characters contributes to aesthetic service provision we provide a tool for facilitating the visualization and interpretation of complex landscape characters.

     

Application of partial least squares regression in detecting the important landscape indicators determining urban land surface temperature variation

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.

     

Integrating land cover structure and functioning to predict biodiversity patterns: a hierarchical modelling framework designed for ecosystem management

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.

     

How does a transforming landscape influence bird breeding success?

Context

The conversion of agricultural landscapes to tree plantations is a major form of landscape transformation worldwide, but its effects on biodiversity, particularly key population processes like reproductive success, are poorly understood.

Objectives

We compared bird breeding success between woodland remnants surrounded by maturing stands of plantation Radiata Pine and a matched set of woodland remnants in semi-cleared grazing land.

Methods

Our study was conducted in the Nanangroe region in south-eastern New South Wales, Australia. Using repeated field measurements, we quantified bird breeding success in 23 woodland remnants; 13 surrounded by Radiata Pine plantations and 10 on farms where remnants were surrounded by semi-cleared grazing land. We matched the attributes of native remnant patches between two types of matrix.

Results

We found that: (1) rates of nesting success of smaller-bodied birds in woodland remnants surrounded by grazing land were significantly higher than in woodland remnants surrounded by pine plantations; and (2) taxa with domed nests were more successful at nesting than species that constructed open cup/bowl nests in woodland remnants within farmlands.

Conclusions

Our findings suggest that bird breeding success in remnant woodland patches is significantly diminished as a result of the conversion of semi-cleared grazing land to pine plantations.

     

Small-scale agricultural landscapes promote spider and ground beetle densities by offering suitable overwintering sites

Context

Intensive agricultural management practices and landscape homogenisation are the main drivers of biodiversity loss in agricultural landscapes. Agricultural fields are regularly disturbed and provide unstable habitats due to crop management regimes. This may lead to movement of arthropods into neighbouring non-arable habitats, as natural and semi-natural habitats provide suitable overwintering sites.

Objectives

Here we assessed the effect of landscape composition and configuration on the overwintering spider and carabid fauna of grassy field margins and hedgerows.

Methods

We sampled ground-dwelling arthropods at field edges of different types (grassy field margin and hedgerows), landscape composition (diverse and simple) and configuration (mosaic and large-scale agricultural landscapes).

Results

We detected larger spiders in hedgerows than in grassy field margins and in complex landscapes rather than in simple landscapes. We found a significant effect of interaction between landscape composition and edge type on ballooning propensity of spiders. Agrobiont carabids were more abundant in field edges of compositionally simple and large-scale agricultural landscapes. Furthermore, we showed an effect of interaction between landscape composition and edge type on agrobiont spiders. We collected larger carabids in grassy field margins than in hedgerows and carabids were smaller in simple landscapes than in diverse landscapes. The spider community was affected by edge type, and landscape composition had a significant effect on the carabid community.

Conclusions

Small-scale agricultural landscapes may have higher overall densities of ground-dwelling spiders and carabids than large scale landscapes due to the relatively high edge density and the higher quantity of available overwintering sites.

     

Improving tree cover estimates for fine-scale landscape ecology

Context

Mapping the presence of trees is an important tool for assessing tree-covered habitats, their changes, and calculating variables, like forest area and fragmentation.

Objective

Despite the popularity of automated pattern recognition to make tree cover maps, their accuracy and precision are rarely tested or compared to more modest methods, like human-based pattern recognition to identify tree cover.

Methods

Here, we test the performance of two computer-generated tree mapping products, the Global Change Forest database and the Carnegie Landsat Analysis System, against ground surveys and a human-made tree cover map created using Google Earth to hand digitize the presence and absence of trees in a diversified agricultural region in Costa Rica (934 km²).

Results

The human-made tree cover map properly classified 100% ground survey sites and explained 81% of the variance in percent of canopy cover values from the field. The Global Change Forest database misclassified 18 of 23 ground survey sites in deforested locations and explained 6% of the variance in percent of canopy cover values from ground surveys. The Carnegie Landsat Analysis System misclassified 9 of 23 ground survey sites in deforested locations and explained 38% of the variance in percent of canopy cover values from the field.

Conclusions

Our results suggest that the Global Change Forest database overestimated tree cover by of 20% and the Carnegie Landsat Analysis System by 1%. We caution landscape ecologists working at fine spatial scales against using computer-generated tree cover, especially in the partially forested lands that increasingly cover the planet.

     

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.