Addressing the interplay of poverty and the ecology of landscapes: a Grand Challenge Topic for landscape ecologists?

We argue for the landscape ecology community to adopt the study of poverty and the ecology of landscapes as a Grand Challenge Topic. We present five areas of possible research foci that we believe that landscape ecologists can join with other social and environmental scientists to increase scientific understanding of this pressing issue: (1) scale and poverty; (2) landscape structure and human well-being; (3) social and ecological processes linked to spatial patterns in landscapes; (4) conservation and poverty, and (5) applying the landscape ecologist’s toolkit. A brief set of recommendations for landscape ecologists is also presented. These include the need to utilize broad frameworks that integrate social and ecological variables, build capacity to do this kind of work through the development of strong collaborations of researchers in developed and developing countries, create databases in international locations where extreme poverty exists, and create a new generation of researchers capable of addressing this pressing social and environmental issue.     

Spatial resilience: integrating landscape ecology,resilience, and sustainability

Landscape ecology has a high potential to contribute to sustainability in the interactions of people and nature. Landscape ecologists have already made considerable progress towards a more general understanding of the relevance of spatial variation for ecosystems. Incorporating the complexities of societies and economies into landscape ecology analyses will, however, require a broader framework for thinking about spatial elements of complexity. An exciting recent development is to explicitly try to integrate landscape ecology and ideas about resilience in social–ecological systems through the concept of spatial resilience. Spatial resilience focuses on the importance of location, connectivity, and context for resilience, based on the idea that spatial variation in patterns and processes at different scales both impacts and is impacted by local system resilience. I first introduce and define the concepts of resilience and spatial resilience and then discuss some of their potential contributions to the further interdisciplinary integration of landscape ecology, complexity theory, and sustainability science. Complexity theorists have argued that many complex phenomena, such as symmetry-breaking and selection, share common underlying mechanisms regardless of system type (physical, social, ecological, or economic). Similarities in the consequences of social exclusion and habitat fragmentation provide an informative example. There are many strong parallels between pattern–process interactions in social and ecological systems, respectively, and a number of general spatial principles and mechanisms are emerging that have relevance across many different kinds of system. Landscape ecologists, with their background in spatially explicit pattern–process analysis, are well placed to contribute to this emerging research agenda.     

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

Natural reforestation of European mountain landscapes raises major environmental and societal issues. With local stakeholders in the Pyrenees National Park area (France), we studied agricultural landscape colonisation by ash (Fraxinus excelsior) to enlighten its impacts on biodiversity and other landscape functions of importance for the valley socio-economics. The study comprised an integrated assessment of land-use and land-cover change (LUCC) since the 1950s, and a scenario analysis of alternative future policy. We combined knowledge and methods from landscape ecology, land change and agricultural sciences, and a set of coordinated field studies to capture interactions and feedback in the local landscape/land-use system. Our results elicited the hierarchically-nested relationships between social and ecological processes. Agricultural change played a preeminent role in the spatial and temporal patterns of LUCC. Landscape colonisation by ash at the parcel level of organisation was merely controlled by grassland management, and in fact depended on the farmer’s land management at the whole-farm level. LUCC patterns at the landscape level depended to a great extent on interactions between farm household behaviours and the spatial arrangement of landholdings within the landscape mosaic. Our results stressed the need to represent the local SES function at a fine scale to adequately capture scenarios of change in landscape functions. These findings orientated our modelling choices in the building an agent-based model for LUCC simulation (SMASH–Spatialized Multi-Agent System of landscape colonization by ASH). We discuss our method and results with reference to topical issues in interdisciplinary research into the sustainability of multifunctional landscapes.     

Spatial structure of shell polychromatism in <Emphasis Type="Italic">Cepaea hortensis</Emphasis> in relation to a gradient of landscape fragmentation in Western France

Because of their highly polymorphic shell patterns, Cepaea land snails have been the subject of numerous studies in ecological genetics. Here, we investigated the spatial structure of polychromatism in Cepaea hortensis in agricultural landscapes with zones from low to high hedgerow densities. Our main purpose was to search for a relationship between landscape composition and spatial structuring of chromatism. Despite significant spatial heterogeneity in the three landscapes sampled, only the high hedgerow density landscape showed a significant spatial structuring of shell polymorphism. In order to understand this result, an investigation of daily movement patterns in relation to habitat form was carried out on a mark-release experiment under semi-artificial conditions. This experiment revealed a strong influence of a linear corridor on snail dispersal. In the field, spatial heterogeneity of shell polymorphism, related to the effects of genetic drift, was shaped by restricted dispersal in narrow corridors. In the more enclosed one, i.e. where hedgerow density was the highest, the significant spatial structure we detected involved a balance between local genetic drift and environmentally mediated gene flow. This isolation-by-distance pattern resulted from direct gene exchange through fields between neighbouring populations. When applying landscape distances based on hedgerow length, no significant spatial correlation with polychromatism was found. In the more fragmented sites, random genetic drift seemed to be the prevailing force and, at the scale of the whole sampled area, selective pressures potentially interfere with these genetic drift-dispersal events.     

Changing patterns in the urbanized countryside of Western Europe

Urbanization refers to the complex interaction of different processes which transform landscapes formed by rural life styles into urban like ones. Urbanization causes profound changes in the ecological functioning of the landscape and gradually results in a changing spatial structure, i.e. forms new landscape patterns. The existing cities and urban network form the framework for this change, which is affecting increasingly larger areas in the countryside. Urbanization is mainly studied from social and economical viewpoints. Urban planners think about optimization of the land use and about aesthetics when reshaping the environment. Landscape ecology is lacking in urban planning because of different goals and concepts, but mostly because of missing significant information about these highly dynamical landscapes.     

Combining farmers’ decision rules and landscape stochastic regularities for landscape modelling

Landscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called “landscape agronomy”, aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.     

The shared landscape: what does aesthetics have to do with ecology?

This collaborative essay grows out of a debate about the relationship between aesthetics and ecology and the possibility of an “ecological aesthetic” that affects landscape planning, design, and management. We describe our common understandings and unresolved questions about this relationship, including the importance of aesthetics in understanding and affecting landscape change and the ways in which aesthetics and ecology may have either complementary or contradictory implications for a landscape. To help understand these issues, we first outline a conceptual model of the aesthetics–ecology relationship. We posit that: 1. While human and environmental phenomena occur at widely varying scales, humans engage with environmental phenomena at a particular scale: that of human experience of our landscape surroundings. That is the human “perceptible realm.” 2. Interactions within this realm give rise to aesthetic experiences, which can lead to changes affecting humans and the landscape, and thus ecosystems. 3. Context affects aesthetic experience of landscapes. Context includes both effects of different landscape types (wild, agricultural, cultural, and metropolitan landscapes) and effects of different personal–social situational activities or concerns. We argue that some contexts elicit aesthetic experiences that have traditionally been called “scenic beauty,” while other contexts elicit different aesthetic experiences, such as perceived care, attachment, and identity. Last, we discuss how interventions through landscape planning, design, and management; or through enhanced knowledge might establish desirable relationships between aesthetics and ecology, and we examine the controversial characteristics of such ecological aesthetics. While these interventions may help sustain beneficial landscape patterns and practices, they are inherently normative, and we consider their ethical implications.     

Spatial and temporal analysis of landscape patterns

A variety of ecological questions now require the study of large regions and the understanding of spatial heterogeneity. Methods for spatial-temporal analyses are becoming increasingly important for ecological studies. A grid cell based spatial analysis program (SPAN) is described and results of landscape pattern analysis using SPAN are presentedd. Several ecological topics in which geographic information systems (GIS) can play an important role (landscape pattern analysis, neutral models of pattern and process, and extrapolation across spatial scales) are reviewed. To study the relationship between observed landscape patterns and ecological processes, a neutral model approach is recommended. For example, the expected pattern (i.e., neutral model) of the spread of disturbance across a landscape can be generated and then tested using actual landscape data that are stored in a GIS. Observed spatial or temporal patterns in ecological data may also be influenced by scale. Creating a spatial data base frequently requires integrating data at different scales. Spatial is shown to influence landscape pattern analyses, but extrapolation of data across spatial scales may be possible if the grain and extent of the data are specified. The continued development and testing of new methods for spatial-temporal analysis will contribute to a general understanding of landscape dynamics.     

Non-linear effects of landscape properties on mistletoe parasitism in fragmented agricultural landscapes

Ecological processes such as plant–animal interactions have a critical role in shaping the structure and function of ecosystems, but little is known of how such processes are modified by changes in landscape structure. We investigated the effect of landscape change on mistletoe parasitism in fragmented agricultural environments by surveying mistletoes on eucalypt host trees in 24 landscapes, each 100 km² in size, in south-eastern Australia. Landscapes were selected to represent a gradient in extent (from 60% to 2% cover) and spatial pattern of remnant wooded vegetation. Mistletoes were surveyed at 15 sites in each landscape, stratified to sample five types of wooded elements in proportion to their relative cover. The incidence per landscape of box mistletoe (Amyema miquelii), the most common species, was best explained by the extent of wooded cover (non-linear relationship) and mean annual rainfall. Higher incidence occurred in landscapes with intermediate levels of cover (15–30%) and higher rainfall (>500 mm). Importantly, a marked non-linear decline in the incidence of A. miquelii in low-cover landscapes implies a disproportionate loss of this species in remaining wooded vegetation, greater than that attributable to decreasing forest cover. The most likely mechanism is the effect of landscape change on the mistletoebird (Dicaeum hirundinaceum), the primary seed-dispersal vector for A. miquelii. Our results are consistent with observations that habitat fragmentation initially enhances mistletoe occurrence in agricultural environments; but in this region, when wooded vegetation fell below a threshold of ~15% landscape cover, the incidence of A. miquelii declined precipitously. Conservation management will benefit from greater understanding of the components of landscape structure that most influence ecological processes, such as mistletoe parasitism and other plant–animal mutualisms, and the critical stages in such relationships. This will facilitate action before critical thresholds are crossed and cascading effects extend to other aspects of ecosystem function.     

Predicting the assembly of novel communities in urban ecosystems

Context

Ecological communities in urban ecosystems are assembled through ecological processes, such as species interactions, dispersal, and environmental filtering, but also through human factors that create and modify the landscape. These complex interactions make it difficult to untangle the relationships between social–ecological dynamics and urban biodiversity.

Objectives

As a result, there has been a call for research to address how human activities influence the processes by which ecological communities are structured in urban ecosystems. We address this research challenge using core concepts from landscape ecology to develop a framework that links social-ecological dynamics to ecological communities using the metacommunity perspective.

Methods

The metacommunity perspective is a useful framework to explore the assembly of novel communities because it distinguishes between the effects of local environmental heterogeneity and regional spatial processes in structuring ecological communities. Both are shaped by social–ecological dynamics in urban ecosystems.

Results

In this paper, we define social, environmental, and spatial processes that structure metacommunities, and ultimately biodiversity, in cities. We then address how our framework could be applied in urban ecosystem research to understand multi-scalar biodiversity patterns.

Conclusions

Our framework provides a theoretical and empirical foundation for transdisciplinary research to examine how social-ecological dynamics mediate the assembly of novel communities in urban ecosystems.

     

Associations between soil carbon and ecological landscape variables at escalating spatial scales in Florida,USA

The spatial distribution of soil carbon (C) is controlled by ecological processes that evolve and interact over a range of spatial scales across the landscape. The relationships between hydrologic and biotic processes and soil C patterns and spatial behavior are still poorly understood. Our objectives were to (i) identify the appropriate spatial scale to observe soil total C (TC) in a subtropical landscape with pronounced hydrologic and biotic variation, and (ii) investigate the spatial behavior and relationships between TC and ecological landscape variables which aggregate various hydrologic and biotic processes. The study was conducted in Florida, USA, characterized by extreme hydrologic (poorly to excessively drained soils), and vegetation/land use gradients ranging from natural uplands and wetlands to intensively managed forest, agricultural, and urban systems. We used semivariogram and landscape indices to compare the spatial dependence structures of TC and 19 ecological landscape variables, identifying similarities and establishing pattern–process relationships. Soil, hydrologic, and biotic ecological variables mirrored the spatial behavior of TC at fine (few kilometers), and coarse (hundreds of kilometers) spatial scales. Specifically, soil available water capacity resembled the spatial dependence structure of TC at escalating scales, supporting a multi-scale soil hydrology-soil C process–pattern relationship in Florida. Our findings suggest two appropriate scales to observe TC, one at a short range (autocorrelation range of 5.6 km), representing local soil-landscape variation, and another at a longer range (119 km), accounting for regional variation. Moreover, our results provide further guidance to measure ecological variables influencing C dynamics.     

Culture and changing landscape structure

Culture changes landscapes and culture is embodied by landscapes. Both aspects of this dynamic are encompassed by landscape ecology, but neither has been examined sufficiently to produce cultural theory within the field. This paper describes four broad cultural principles for landscape ecology, under which more precise principles might be organized. A central underlying premise is that culture and landscape interact in a feedback loop in which culture structures landscapes and landscapes inculcate culture. The following broad principles are proposed:

1. Human landscape perception, cognition, and values directly affect the landscape and are affected by the landscape.
2. Cultural conventions powerfully influence landscape pattern in both inhabited and apparently natural landscapes.
3. Cultural concepts of nature are different from scientific concepts of ecological function.
4. The appearance of landscapes communicates cultural values.

Both the study of landscapes at a human scale and experimentation with possible landscapes, landscape patterns invented to accommodate ecological function, are recommended as means of achieving more precise cultural principles.     

Designing agricultural landscapes for natural pest control: a transdisciplinary approach in the Hoeksche Waard (The Netherlands)

The green–blue network of semi-natural non-crop landscape elements in agricultural landscapes has the potential to enhance natural pest control by providing various resources for the survival of beneficial insects that suppress crop pests. A study was done in the Hoeksche Waard to explore how generic scientific knowledge about the relationship between the spatial structure of the green–blue network and enhancement of natural pest control can be applied by stakeholders. The Hoeksche Waard is an agricultural area in the Netherlands, characterized by arable fields and an extensive network of dikes, creeks, ditches and field margins. Together with stakeholders from the area the research team developed spatial norms and design rules for the design of a green–blue network that supports natural pest control. The stakeholders represented different interests in the area: farmers, nature and landscape conservationists, water managers, and local and regional politicians. Knowledge about the spatial relationship among beneficial insects, pests and landscape structure is incomplete. We conclude that to apply scientific knowledge about natural pest control and the role of green–blue networks to stakeholders so that they can apply it in landscape change, knowledge transfer has to be transparent, area specific, understandable, practical and incorporate local knowledge.     

Connectivity in Heterogeneous Landscapes: Analyzing the Effect of Topography

Animal response to landscape heterogeneity directs dispersal and affects connectivity between populations. Topographical heterogeneity is a major source of landscape heterogeneity, which is rarely studied in the contexts of movement, dispersal, or connectivity. The current study aims at characterizing and quantifying the impacts of topography on landscape connectivity. We focus on ‘hilltopping’ behavior in butterflies, a dispersal-like behavior where males and virgin females ascend to mountain summits and mate there. Our approach integrates three elements: an individual-based model for simulating animal movements across topographically heterogeneous landscapes; a formula for the accessibility of patches in homogenous landscapes; and a graphical analysis of the plots of the simulation-based vs. the formula-based accessibility values. We characterize the functional relationship between accessibility values and landscape structure (referred to as ‘accessibility patterns’) and analyze the influence of two factors: the intensity of the individuals’ response to topography, and the level of topographical noise. We show that, despite the diversity of topographical landscapes, animal response to topography results in the formation of two, quantifiable accessibility patterns. We term them ‘effectively homogeneous’ and ‘effectively channeled’. The latter, in which individuals move toward a single summit, prevails over a wide range of behavioral and spatial parameters. Therefore, ‘channeled’ accessibilities may occur in a variety of landscapes and contexts. Our work provides novel tools for understanding and predicting accessibility patterns in heterogeneous landscapes. These tools are essential for linking movement behavior, movement patterns and connectivity. We also present new insights into the practical value of ecologically scaled landscape indices.     

Optimizing landscape selection for estimating relative effects of landscape variables on ecological responses

Empirical studies of the relative effects of landscape variables may compromise inferential strength with common approaches to landscape selection. We propose a methodology for landscape sample selection that is designed to overcome some common statistical pitfalls that may hamper estimates of relative effects of landscape variables on ecological responses. We illustrate our proposed methodology through an application aimed at quantifying the relationships between farmland heterogeneity and biodiversity. For this project, we required 100 study landscapes that represented the widest possible ranges of compositional and configurational farmland heterogeneity, where these two aspects of heterogeneity were quantified as crop cover diversity (Shannon diversity index) and mean crop field size, respectively. These were calculated at multiple spatial extents from a detailed map of the region derived through satellite image segmentation and classification. Potential study landscapes were then selected in a structured approach such that: (1) they represented the widest possible range of both heterogeneity variables, (2) they were not spatially autocorrelated, and (3) there was independence (no correlation) between the two heterogeneity variables, allowing for more precise estimates of the regression coefficients that reflect their independent effects. All selection criteria were satisfied at multiple extents surrounding the study landscapes, to allow for multi-scale analysis. Our approach to landscape selection should improve the inferential strength of studies estimating the relative effects of landscape variables, particularly those with a view to developing land management guidelines.     

The modifiable areal unit problem and implications for landscape ecology

Landscape ecologists often deal with aggregated data and multiscaled spatial phenomena. Recognizing the sensitivity of the results of spatial analyses to the definition of units for which data are collected is critical to characterizing landscapes with minimal bias and avoidance of spurious relationships. We introduce and examine the effect of data aggregation on analysis of landscape structure as exemplified through what has become known, in the statistical and geographical literature, as theModifiable Areal Unit Problem (MAUP). The MAUP applies to two separate, but interrelated, problems with spatial data analysis. The first is the “scale problem”, where the same set of areal data is aggregated into several sets of larger areal units, with each combination leading to different data values and inferences. The second aspect of the MAUP is the “zoning problem”, where a given set of areal units is recombined into zones that are of the same size but located differently, again resulting in variation in data values and, consequently, different conclusions. We conduct a series of spatial autocorrelation analyses based on NDVI (Normalized Difference Vegetation Index) to demonstrate how the MAUP may affect the results of landscape analysis. We conclude with a discussion of the broader-scale implications for the MAUP in landscape ecology and suggest approaches for dealing with this issue.