The Forgotten Rural Landscapes of Central and Eastern Europe

Interactions between nature and man – the underlying forces in landscape – have over time caused diversity. Usually, geographers and landscape ecologists deal with spatial diversity; in this paper, we would like to also consider temporal diversity. We argue that Central and Eastern European landscapes (using the examples of Estonia, Hungary, Poland and Slovenia) are much more diverse in time (layers) than Western European ones. This difference requires the use of different indicators in order to measure and study landscapes and special problems, threats, and possibilities of management and future development – but most important is the consideration of different perceptions. We also show that this diversity reduces the readability of landscapes, creating miscommunication and a transformation of meanings. We further argue that the link between humans and landscape is lost in Central and Eastern European countries due to temporal diversity, and that this link will be created anew in a globalizing world. To overcome alienation, we need slightly different classifications/typologies for each country in this region, with the aim of a sound future management of cultural landscapes.     

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.

     

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.     

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.     

The effects of habitat resolution on models of avian diversity and distributions: a comparison of two land-cover classifications

Quantifying patterns is a key element of landscape analysis. One aspect of this quantification of particular importance to landscape ecologists is the classification of continuous variables to produce categorical variables such as land-cover type or elevation stratum. Although landscape ecologists are fully aware of the importance of spatial resolution in ecological investigations, the potential importance of the resolution of classifications has received little attention. Here we demonstrate the effects of using two different land-cover classifications to predict avian species richness and the occurrences of six individual species across the conterminous United States. We compared models built with a data set based on 14 coarsely resolved land-cover variables to models built with a data set based on 160 finely resolved land-cover variables. In general, comparable models built with the two data sets fit the data to similar degrees, but often produced strikingly different predictions in various parts of the country. By comparing the predictions made by pairs of models, we determined in which regions of the US predictions were most sensitive to differences in land-cover classification. In general, these sensitive areas were different for four of the individual species and for predictions of species richness, indicating that alternate classifications will have different effects in the analyses of different ecological phenomena and that these effects will likely vary geographically. Our results lead us to emphasize the importance of the resolution to which continuous variables are classified in the design of ecological studies.This revised version was published online in May 2005 with corrections to the Cover Date.     

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.     

Spatial patterns of Mediterranean land abandonment and related land cover transitions

In Mediterranean France, land abandonment is a widespread change. To understand and predict the land abandonment process and its consequences, land cover change models are used. An essential step in the development of a land cover change model is the identification and quantification of the factors controlling land cover change. In this paper we present a change detection study using aerial photographs in combination with an extensive dataset of field data and geographical data, to identify and quantify these factors for a study area in Mediterranean France, 60 km west of the city of Montpellier. We distinguished 11 land cover change classes and 7 associated “time since abandonment” classes at a detailed scale. Several environmental and non-environmental factors were found to be important variables for the land abandonment process. Differences in soil class explain a large part of the land abandonment pattern and the associated transition paths and transition rates. Most abandoned lands are located on regosols and lithosols, which are marginal soils with respect to water holding capacity. Within soil classes, we could recognise different transition paths and transition rates. However, within the 55 years covered by this dataset detailed transitions from pioneer vegetation to vegetation higher in the succession, as described by other authors, were only found for a limited number of vegetation/soil combinations. We relate these slow transitions for some areas to ongoing grazing and for some other areas to irreversible degradation.     

Key issues and research priorities in landscape ecology: An idiosyncratic synthesis

Landscape ecology has made tremendous progress in recent decades, but as a rapidly developing discipline it is faced with new problems and challenges. To identify the key issues and research priorities in landscape ecology, a special session entitled “Top 10 List for Landscape Ecology in the 21st Century” was organized at the 16th Annual Symposium of the US Regional Association of International Association of Landscape Ecology, held at Arizona State University (Tempe, Arizona, USA) during April 25–29, 2001. A group of leading landscape ecologists were invited to present their views. This paper is intended to be a synthesis, but not necessarily a consensus, of the special session. We have organized the diverse and wide-ranging perspectives into six general key issues and 10 priority research topics. The key issues are: (1) interdisciplinarity or transdisciplinarity, (2) integration between basic research and applications,(3) Conceptual and theoretical development, (4) education and training, (5)international scholarly communication and collaborations, and (6) outreach and communication with the public and decision makers. The top 10 research topics are: (1) ecological flows in landscape mosaics, (2) causes, processes, and consequences of land use and land cover change, (3) nonlinear dynamics and landscape complexity, (4) scaling, (5) methodological development, (6) relating landscape metrics to ecological processes, (7) integrating humans and their activities into landscape ecology, (8) optimization of landscape pattern, (9)landscape sustainability, and (10) data acquisition and accuracy assessment. We emphasize that, although this synthesis was based on the presentations at the“Top 10 List” session, it is not a document that has been agreed upon by each and every participant. Rather, we believe that it is reflective of the broad-scale vision of the collective as to where landscape ecology is now and where it may be going in future. This revised version was published online in July 2006 with corrections to the Cover Date.     

Evaluating effects of low quality habitats on regional population growth in <Emphasis Type="Italic">Peromyscus leucopus</Emphasis>: Insights from field-parameterized spatial matrix models

Due to complex population dynamics and source–sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive field-based analyses of demography and migration and spatial matrix models of white-footed mouse (Peromyscus leucopus) population dynamics. We interpret asymptotic population growth rates from these spatial models as fitness-based measures of habitat-quality and use elasticity analysis to further explore model behavior and the roles of migration. In addition, we compare population growth rates at the spatial scale of single habitats and the landscape-level scale at which these habitats are assembled. To this end, we employ emerging techniques in multi-scale estimation of demography and movement and recently described vec-permutation methods for spatial matrix notation and analysis. Our findings indicate that the loss of low quality habitats or reductions in movement from these habitats into higher quality areas could negatively affect landscape-level population fitness.     

Genetic isolation by distance and landscape connectivity in the American marten (Martes americana)

Empirical studies of landscape connectivity are limited by the difficulty of directly measuring animal movement. ‘Indirect’ approaches involving genetic analyses provide a complementary tool to ‘direct’ methods such as capture–recapture or radio-tracking. Here the effect of landscape on dispersal was investigated in a forest-dwelling species, the American marten (Martes americana) using the genetic model of isolation by distance (IBD). This model assumes isotropic dispersal in a homogeneous environment and is characterized by increasing genetic differentiation among individuals separated by increasing geographic distances. The effect of landscape features on this genetic pattern was used to test for a departure from spatially homogeneous dispersal. This study was conducted on two populations in homogeneous vs. heterogeneous habitat in a harvested boreal forest in Ontario (Canada). A pattern of IBD was evidenced in the homogeneous landscape whereas no such pattern was found in the near-by harvested forest. To test whether landscape structure may be accountable for this difference, we used effective distances that take into account the effect of landscape features on marten movement instead of Euclidean distances in the model of isolation by distance. Effective distances computed using least-cost modeling were better correlated to genetic distances in both landscapes, thereby showing that the interaction between landscape features and dispersal in Martes americana may be detected through individual-based analyses of spatial genetic structure. However, the simplifying assumptions of genetic models and the low proportions in genetic differentiation explained by these models may limit their utility in quantifying the effect of landscape structure.     

Determining an appropriate minimum mapping unit in vegetation mapping for ecosystem restoration: a case study from the Everglades,USA

This paper documents the analyses that were conducted with regards to investigating an appropriate Minimum Mapping Unit (MMU) to be used to capture the potential changes in vegetation patterns for a 10,924 square km restoration project being conducted in south Florida, USA. Spatial landscape and class metrics that were shown to change predictably with increasing grain size were adopted from previous studies and applied to a multi-scale analysis. Specifically, this study examines the effects of changing grain size on landscape metrics, utilizing empirical data from a real landscape encompassing 234,913 ha of south Florida’s Everglades. The objective was to identify critical thresholds within landscape metrics, which can be used to provide insight in determining an appropriate MMU for vegetation mapping. Results from this study demonstrate that vegetation heterogeneity will exhibit dissimilar patterns when investigating the loss of information within landscape and class metrics, as grain size is increased. These results also support previous findings that suggest that landscape metric “scalograms” (the response curves of landscape metrics to changing grain size), are more likely to be successful for linking landscape pattern to ecological processes as both pattern and process in ecological systems often operate on multiple scales. This study also incorporates an economic cost for various grain dependant vegetation mapping scales. A final selection of the 50 × 50 m grain size for mapping vegetation was based on this study’s investigation of the “scalograms”, the costs, and a composite best professional judgment of seasoned scientists having extensive experience within these ecosystems.     

Analysing land-cover changes in relation to environmental variables in Hesse,Germany

Land-use and land-cover changes affect ecological landscape functions and processes. Hence, landscape ecologists have a central interest in a comprehensive understanding of such changes. Our study focuses on the relationships between environmental conditions and agricultural land-cover changes. We present a method to (i) characterise the major spatial-temporal processes of land-cover changes, (ii) identify the correlations between environmental attributes and land-cover changes and (iii) derive potential environmental drivers of land-cover changes in a German marginal rural landscape. The method was applied to study land-cover dynamics from 1945 to 1998 in the districts of Erda, Steinbrücken and Eibelshausen, situated in the marginal rural landscape of the Lahn-Dill Highlands, Germany. We employed land-cover data gained by the interpretation of multi-temporal aerial photographs. Various environmental variables were introduced into the analyses. We identified physical landscape attributes (elevation, slope, aspect, available water capacity and soil texture) and structural landscape dimensions (patch size, patch shape and distance between patch and nearest settlement). With the aid of GIS, K-means partitioning and canonical correspondence analysis, we investigated land-cover trajectory types, land-cover transitions at individual time intervals and their relationships to these environmental variables. Our results show that, between 1945 and 1998, land-cover changes correlated with the physical attributes of the underlying landscape. On the other hand, the structural landscape dimensions correlated with land cover only in periods of minor land-cover changes (1972–98). Greater diversity of physical landscape attributes is correlated with greater land-cover dynamics. Besides the important influence of socio-economic factors, land-cover changes in the study areas took place within the relatively stable physical constraints of the underlying landscape.This revised version was published online in May 2005 with corrections to the Cover Date.     

Landscape ecology of <Emphasis Type="Italic">Phragmites australis</Emphasis> invasion in networks of linear wetlands

The interaction between landscape structure and spatial patterns of plant invasion has been little addressed by ecologists despite the new insights it can provide. Because of their spatial configuration as highly connected networks, linear wetlands such as roadside or agricultural ditches, can serve as corridors facilitating invasion at the landscape scale, but species dynamics in these important habitats are not well known. We conducted a landscape scale analysis of Phragmites australis invasion patterns (1985–2002 and 1987–2002) in two periurban areas of southern Québec (Canada) focusing on the interaction between the network of linear wetlands and the adjacent land-uses. Results show that, at the beginning of the reference period, the two landscapes were relatively non-invaded and populations occurred mostly in roadside habitats which then served as invasion foci into other parts of the landscape. The intrinsic rates of increase of P. australis populations in linear anthropogenic habitats were generally higher than those reported for natural wetlands. Riparian habitats along streams and rivers were little invaded compared to anthropogenic linear wetlands, except when they intersected transportation rights-of-way. Bivariate spatial point pattern analysis of colonization events using both Euclidian and network distances generally showed spatial dependence (association) to source populations. An autologistic regression model that included landscape and edaphic variables selected transportation rights-of-way as the best predictor of P. australis occurrence patterns in one of the landscapes. Given the high invasion rates observed, managers of linear wetlands should carefully monitor expansion patterns especially when roads intersect landscapes of conservation or economic value.     

Beyond the least-cost path: evaluating corridor redundancy using a graph-theoretic approach

The impact of the landscape matrix on patterns of animal movement and population dynamics has been widely recognized by ecologists. However, few tools are available to model the matrix’s influence on the length, relative quality, and redundancy of dispersal routes connecting habitat patches. Many GIS software packages can use land use/land cover maps to identify the route of least resistance between two points—the least-cost path. The limitation of this type of analysis is that only a single path is identified, even though alternative paths with comparable costs might exist. In this paper, we implemented two graph theory methods that extend the least-cost path approach: the Conditional Minimum Transit Cost (CMTC) tool and the Multiple Shortest Paths (MSPs) tool. Both methods enable the visualization of multiple dispersal routes that, together, are assumed to form a corridor. We show that corridors containing alternative dispersal routes emerge when favorable habitat is randomly distributed in space. As clusters of favorable habitat start forming, corridors become less redundant and dispersal bottlenecks become visible. Our approach is illustrated using data from a real landscape in the Brazilian Atlantic forest. We explored the effect of small, localized disturbance on dispersal routes linking conservation units. Simulated habitat destruction caused the appearance of alternative dispersal routes, or caused existing corridors to become narrower. These changes were observed even in the absence of significant differences in the length or cost of least-cost paths. Last, we discuss applications to animal movement studies and conservation initiatives.     

Incorporating biological information in local land-use decision making: designing a system for conservation planning

Human settlement is a formidable agent of change affecting fundamental ecological processes. Decisions governing these land-use changes occur almost exclusively at the local level and, as a result, they are made at many different locations and times. Consequently, it is difficult for ecologists to provide needed scientific support for these choices. We built an information system designed to support conservation decisions at local scales by offering data over the Internet. We collaborated with local stakeholders (e.g., developers, planners, politicians, land owners, environmental activists) to design the system. This collaboration produced several generalizations about effective design of information systems to support conservation. The most important of these is the idea that ecological data and analysis must be understood by those who will be affected by the decisions. Also, planning for conservation is a process that uses scientific data, but that ultimately depends on the expression of human values. A major challenge landscape ecologists face is to extend general landscape principles to provide specific scientific information needed for local land-use planning.     

How to define a patch: a spatial model for hierarchically delineating organism-specific habitat patches

Landscape analysis and delineation of habitat patches should take into account organism-specific behavioral and perceptual responses to landscape structure because different organisms perceive and respond to landscape features over different ranges of spatial scales. The commonly used methods for delineating habitat based on rules of contiguity do not account for organism-specific responses to landscape patch structure and have undesirable properties, such as being dependent on the scale of base map used for analysis. This paper presents an improved patch delineation algorithm, “PatchMorph,” which can delineate patches across a range of spatial scales based on three organism-specific thresholds: (1) land cover density threshold, (2) habitat gap maximum thickness (gap threshold), and (3) habitat patch minimum thickness (spur threshold). This algorithm was tested on an “idealized” landscape with landscape gaps and spurs of known size, and delineated patches as expected. It was then applied to delineate patches from a neutral random fractal landscape, which showed that as the input gap and spur thickness thresholds were increased, the number of patches decreased from 59 (low thresholds) patches to 1 (high thresholds). The algorithm was then applied to model western yellow-billed cuckoo (Coccyzus americanus occidentalis) nesting habitat patches based on spur and gap thresholds specific to this organism. Both these analyses showed that fewer patches were delineated by PatchMorph than by rules of contiguity, and those patches were larger, had smoother edges, and had fewer gaps within the patches. This algorithm has many applications beyond those presented in this paper, including habitat suitability analysis, spatially explicit population modeling, and habitat connectivity analysis.     

Population Dynamics of Songbirds in the Boreal Mixedwood Forests of Alberta,Canada: Estimating Minimum and Maximum Extents of Spatial Population Synchrony

Ecological phenomena vary over space and time and interpretation of these processes also varies depending on the measurement scale. As the spatial scale of observation increases and decreases, changes in population abundance will likely exhibit alternating patterns of asynchrony and synchrony. While the study of how and why population dynamics change with spatial scale of measurement is intrinsically interesting, most population ecologists seek to study mechanisms of population change on a discrete study area. Our study develops methods that population ecologists can use to determine spatially appropriate sampling designs, and demonstrates how such spatial scales can be determined for 25 species of songbirds using long-term data from the boreal mixedwood forest of Alberta, Canada. To determine minimum scales of synchrony in population dynamics, we calculated the average correlation of changes in population abundance over time across different numbers of fixed-radius point-count samples. We then used a randomization test to remove the effect of number of replicates from the determination of appropriate spatial scale. The maximum extent of synchrony was estimated as the distance where population dynamics were no longer correlated. Estimates of the minimum scale of synchrony differed between species, ranging from 3.1 to 18.6 ha. The maximum scale of synchrony was estimated to be greater than or equal to 8 km for 14 of the 25 species examined, and to be greater than or equal to 70 km for Tennessee Warbler (Vermivora peregrina). Maximum spatial extents were significantly correlated with body mass and territory size.     

What is soundscape ecology? An introduction and overview of an emerging new science

We summarize the foundational elements of a new area of research we call soundscape ecology. The study of sound in landscapes is based on an understanding of how sound, from various sources—biological, geophysical and anthropogenic—can be used to understand coupled natural-human dynamics across different spatial and temporal scales. Useful terms, such as soundscapes, biophony, geophony and anthrophony, are introduced and defined. The intellectual foundations of soundscape ecology are described—those of spatial ecology, bioacoustics, urban environmental acoustics and acoustic ecology. We argue that soundscape ecology differs from the humanities driven focus of acoustic ecology although soundscape ecology will likely need its rich vocabulary and conservation ethic. An integrative framework is presented that describes how climate, land transformations, biodiversity patterns, timing of life history events and human activities create the dynamic soundscape. We also summarize what is currently known about factors that control temporal soundscape dynamics and variability across spatial gradients. Several different phonic interactions (e.g., how anthrophony affects biophony) are also described. Soundscape ecology tools that will be needed are also discussed along with the several ways in which soundscapes need to be managed. This summary article helps frame the other more application-oriented papers that appear in this special issue.     

Accessibility as a determinant of landscape transformation in western Honduras: linking pattern and process

This study evaluates the relationship between landscape accessibility and land cover change in Western Honduras, and demonstrates how these relationships are influenced by social and economic processes of land use change in the region. The study area presents a complex mosaic of land cover change processes that involve approximately equal amounts of reforestation and deforestation. Landsat Thematic Mapper (TM) satellite imagery of 1987, 1991 and 1996 was used to create three single date classifications and a land cover change image depicting the sequence of changes in land cover between 1987–1991–1996. An accessibility analysis examined land cover change and landscape fragmentation relative to elevation and distance from roads. Between 1987 and 1991, results follow ‘expected’ trends, with more accessible areas experiencing greater deforestation and fragmentation. Between 1991 and 1996 this trend reverses. Increased deforestation is found in areas distant from roads, and at higher elevations; a result of government policies promoting expansion of mountain coffee production for export. A ban on logging, and abandonment of marginally productive agricultural fields due to agricultural intensification in other parts of the landscape, has led to increased regrowth in accessible regions of the landscape. Roads and elevation also present different obstacles in terms of their accessibility, with the smallest patches of cyclical clearing and regrowth, relating mostly to the agricultural fallow cycle, found at the highest elevations but located close to roads. This research highlights the need to locate analyses of land cover change within the context of local socio-economic policies and land use processes. This revised version was published online in August 2006 with corrections to the Cover Date.     

Mapping urban landscape heterogeneity: agreement between visual interpretation and digital classification approaches

Visual interpretation of remotely sensed imagery has long been used for landscape pattern analysis. Few studies, however, have investigated human variation in estimates of within-patch composition for classification of those patches, particularly in urban settings. This paper compares the agreement of two approaches—visual interpretation and object-based—to estimate the proportion cover of landscape features within delineated patches, and investigates the spatial patterns of patches with large disagreement between the two approaches. The two approaches were compared for the Gwynns Falls watershed, Maryland, USA. Three methods were used to assess agreement: a traditional error matrix based procedure and two fuzzy methods, a plus-one modification of the traditional procedure, and a fuzzy set theory method. We found that while visual interpretation does not work effectively when patches contain a mix of different types of features, accuracy increases with patches that are either dominated by a specific feature, or do not contain a specific feature. The overall accuracies of estimates by visual interpretation also vary by features, ranging from 63.3% for pavement to 93.8% for bare soil. Patches with large disagreement between the two approaches cluster spatially at locations where the urban landscape is more structurally complex, suggesting the accuracy of visual interpretation may be affected by patch shape complexity, and the spatial configuration of the landscape features within the patches. These results provide important insights into the accuracy of thematic maps based on visual interpretation, not only for ecologists and managers who are using the maps, but also for those who produce the maps.