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.     

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.     

Forty-eight years of landscape change on two contiguous Ohio landscapes

This study analyzes the current and historic structure of two contiguous, rural landscapes covering approximately 242 km² in central Ohio, USA: a till plain landscape with relatively homogeneous topography and soils, and a moraine landscape with greater geomorphological diversity and heterogeneity. These landscapes were chosen because they were both heavily dominated by agriculture during 1900–1940 and were both initially surveyed by the metes-and-bounds system. They differed, however, in the temporal pattern of settlement and development and in the inherent agricultural capability of their soils. We combined analysis of aerial photographs from 1940, 1957, 1971, and 1988 with historical archives and other available mapped data in a GIS data base to facilitate analysis of both spatial and temporal patterns of change. On the moraine, the agricultural matrix decreased over time as forest, urban/suburban areas, and industry increased. In contrast, on the till plain agricultural landcover increased through 1988, with concommitant decreases in upland forest and oak savanna. The moraine landscape exhibited greater diversity and equitability than the till plain on each date. The till plain had its greatest diversity and equitability in 1940, whereas the moraine increased in diversity and equitability during each time period. The undulating topography of the moraine encouraged landcover dynamism rather than stability, whereas the more homogeneous till plain exhibited considerable inertia. Patch and matrix shape remained constant and predominantly angular over the 48 year study period. Differences in the physical environment, especially topography and soil capability, and the socioeconomic environment, especially agricultural policies and patterns of urbanization, resulted in these two contiguous landscapes having different trajectories of change. It is clear from this study that socioeconomic factors must be combined with the physical setting to fully understand patterns of change in human-dominated landscapes.     

Landscape heterogeneity and fire behavior: scale-dependent feedback between fire and grazing processes

Fire and grazing are ecological processes that frequently interact to modify landscape patterns of vegetation. There is empirical and theoretical evidence that response of herbivores to heterogeneity is scale-dependent however the relationship between fire and scale of heterogeneity is not well defined. We examined the relationship between fire behavior and spatial scale (i.e., patch grain) of fuel heterogeneity. We created four heterogeneous landscapes modeled after those created by a fire–grazing interaction that differed in grain size of fuel patches. Fire spread was simulated through each model landscape from 80 independent, randomly located ignition points. Burn area, burn shape complexity and the proportion of area burnt by different fire types (headfire, backfire and flankfire) were all affected by the grain of fuel patch. The area fires burned in heterogeneous landscapes interacted with the fuel load present in the patch where ignition occurred. Burn complexity was greater in landscapes with small patch grain than in landscapes with large patch grain. The proportion of each fire type (backfire, flankfire and headfire) was similar among all landscapes regardless of patch grain but the variance of burned area within each of the three fire types differed among treatments of patch grain. Our landscape fire simulation supports the supposition that feedbacks between landscape patterns and ecological processes are scale-dependent, in this case spatial scale of fuel loading altering fire spread through the landscape.     

Structural dynamic of a hedgerow network landscape in Brittany France

Changes in agricultural systems since the 50's led to considerable changes in rural hedgerow network landscapes. In these landscapes, ecological processes depend on the spatial structure of the network (length of hedgerows, connectedness, grain size). This paper reports on a study of the dynamics of such a landscape at four periods of time (1952, 1961, 1972, 1985) done on 26 contiguous 16 ha quadrats. A correspondence analysis of the data matrix yields a gradient of change from dense highly connected networks to heterogeneous landscapes with few hedgerows. The study of individual trajectories of the quadrats allowed them to be regrouped in various types of changes. It is possible for a quadrat to go through several pathways. Rates of change varied through time, the 1961–1972 period had most changes. The use of supplementary elements in correspondence analysis proves to be a useful way to approach spatial hierarchy and allows a better understanding of the differentiation of landscape units.     

Landscape changes and ecological studies in agricultural regions,Québec,Canada

Most landscape definitions in the western world are based on soil, climatic, or physiographic features and do not integrate humans as an integral part of the landscape. We present an approach where landscape types have been delineated in southern Québec, Canada based on current land use where anthropogenic and agricultural activities are concentrated as a practical application of the holistic approach in landscape definition. Landsat-TM satellite images were classified and the 27 habitat classes were regrouped into 5 general land cover classes (cash crop, dairy farming, forest, anthropogenic, wetlands) and overlaid onto soil landscape polygons to characterize natural boundary units. Cluster analyses were used to aggregate these polygons into seven agricultural types of land scape forming a gradient from urban and high-intensity cash crop farming activities to landscapes dominated by a mosaic of agriculture and forested areas. Multivariate analyses of raw data and of socio-economic and farming practices variables were used to describe the defined types of landscape and these were projected over three established land classification systems of southern Québec (Canadian ecoregions, North American Bird Conservation Initiative regions and Corn Heat Unit regions) to compare their similarity in terms of land cover and for planning of future ecological studies. Because agricultural landscapes are highly dynamic, they are bound to undergo changes in the near future. Our landscape delineation may serve as an experimental setup where land scape dynamics and wildlife populations and community structures could be monitored. Because the information we used to delineate and characterize agricultural landscape types is readily available in other countries, our approach could easily be adapted to similar data sources under and a wide variety of landscape types. This revised version was published online in July 2006 with corrections to the Cover Date.     

Information theory as a consistent framework for quantification and classification of landscape patterns

Context

Quantitative grouping of similar landscape patterns is an important part of landscape ecology due to the relationship between a pattern and an underlying ecological process. One of the priorities in landscape ecology is a development of the theoretically consistent framework for quantifying, ordering and classifying landscape patterns.

Objective

To demonstrate that the information theory as applied to a bivariate random variable provides a consistent framework for quantifying, ordering, and classifying landscape patterns.

Methods

After presenting information theory in the context of landscapes, information-theoretical metrics were calculated for an exemplar set of landscapes embodying all feasible configurations of land cover patterns. Sequences and 2D parametrization of patterns in this set were performed to demonstrate the feasibility of information theory for the analysis of landscape patterns.

Results

Universal classification of landscape into pattern configuration types was achieved by transforming landscapes into a 2D space of weakly correlated information-theoretical metrics. An ordering of landscapes by any single metric cannot produce a sequence of continuously changing patterns. In real-life patterns, diversity induces complexity—increasingly diverse patterns are increasingly complex.

Conclusions

Information theory provides a consistent, theory-based framework for the analysis of landscape patterns. Information-theoretical parametrization of landscapes offers a method for their classification.

     

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.     

Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation

Woody invasive plants are an increasing component of the New England flora. Their success and geographic spread are mediated in part by landscape characteristics. We tested whether woody invasive plant richness was higher in landscapes with many forest edges relative to other forest types and explained land use/land cover and forest fragmentation patterns using socioeconomic and physical variables. Our models demonstrated that woody invasive plant richness was higher in landscapes with more edge forest relative to patch, perforated, and especially core forest types. Using spatially-explicit, hierarchical Bayesian, compositional data models we showed that infrastructure and physical factors, including road length and elevation range, and time-lagged socioeconomic factors, primarily population, help to explain development and forest fragmentation patterns. Our social–ecological approach identified landscape patterns driven by human development and linked them to increased woody plant invasions. Identifying these landscape patterns will aid ongoing efforts to use current distribution patterns to better predict where invasive species may occur in unsampled regions under current and future conditions.     

A landscape-geochemical approach in insular studies as exemplified by islets of the eastern Baltic Sea

The main objective of our investigations is to find out the primary geochemical properties of insular landscapes in order to ascertain the landscape stability on an area of land uplifting in the conditions of a regressive sea. Therefore we focus our study on the landscapes of Kolga Bay islets, which are located near the Estonian coast in the Gulf of Finland. A landscape-geochemical approach of landscape study improves the mapping of insular landscapes and understanding of processes of landscape development. Besides land use changes, land uplift and marine influence shape the landscape patterns of island through topography and subsurface water. We propose geochemical typology of landscapes based on substance movement (eluvial, superwatery, subwatery), field studies on islands, and chemical analysis of soil and water samples. From a landscape geochemical perspective, types of matter fluxes mainly control stability of an insular landscape. Interactions between geochemical, ecosystem and geomorphic processes reveal that islands behave as systems, rather than merely a sequence of interdependent soil-vegetation complexes along topographic gradients. This revised version was published online in August 2006 with corrections to the Cover Date.     

A comparison of quantitative methods for examining landscape pattern and scale

Ecologists have long recognized the importance of spatial and temporal patterns that characterize heterogeneity in landscapes. However, despite the realization that inferences about ecological phenomena are scale dependent, little attention has been paid to determining appropriate scales of measurement (e.g., plot or grain size) in studies of landscape dynamics or ecosystem change. This paper compares the results from three data sets using several quantitative methods available for characterizing landscape heterogeneity and/or for determining scale of measurement. Methods evaluated include tests of non-randomness, estimation of patch size, spectral analysis, fractals, variance ratio analysis, and correlation analysis. The results showed that no one method provides consistently good estimates of scale. Thus, sampling strategies for landscape studies should be derived from estimates of patch size and/or scale of pattern obtained from more than one of these methods.     

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.     

Spatio-temporal variability in human and natural sounds in a rural landscape

The study of landscape structure and functions, including the underlying ecological and anthropogenic processes has traditionally relied on visual aspects without considering information of non-visionary cues, e.g. auditory. In this work we applied a complementary approach for the study of landscapes using qualitative information for the sonic environment. In particular we studied the qualitative linkages between landscape structure and functions and daily sound patterns. The main objectives were the investigation of the spatial and temporal variability in sound perception, and the identification of the dominant sound categories (anthropogenic, biological, geophysical originated sounds) in relation to landscape characteristics. Our results showed significant spatio-temporal variability in the intensity of different sound categories, which reflects distinct soundscape patterns. Temporal sound variability reflected the daily cycle of anthropogenic activities and biological processes, whereas the spatial sound viability was mainly shaped by landscape attributes. The combination of the visual landscape information and its emergent acoustic profile enhances our perception and understanding of nature and this integrated approach may have many practical applications in landscape management, monitoring and planning.     

Temporal variation of characteristic scales in urban landscapes: an insight into the evolving internal structures of China’s two largest cities

Urbanization has induced profound landscape changes. While the spatiotemporal patterns of urban landscapes have been extensively studied, the manner by which the internal structures of already urbanized areas change remains little understood. Characteristic scales are an important measure of landscape structure, and they represent the typical spatial extents of landscape elements in hierarchies. In this study, we quantified temporal variations of the characteristic scales in the central urban landscapes of Beijing and Shanghai over an 18?year period. Using transect data from Landsat images, characteristic scales were identified through wavelet analysis and then classified into several discrete domains using the k-means clustering method. These characteristic scale domains appeared to correspond with the typical extents of the blocks and block clusters in the study areas. Results showed that the number of the characteristic scale domains changed within a small range of 3?C5 while the mean values of the characteristic scales within the domains showed substantial temporal variation. Larger characteristic scales were more variable than smaller ones in both cities. Distinguishing relative change rates of building forms, land use and street layout of urban landscapes allowed us to interpret these differences. The street layout of urban landscapes usually reacts slowly to the force of change, acting as the skeleton of the urban landscape. As a result, block sizes can remain relatively stable and corresponding characteristic scales present inheritance features. Land use and building forms are more susceptible to changes. Block clusters with flexible extents could result in significant variation of characteristic scales.     

Analysis of landscape pattern change trajectories within areas of intensive agricultural use: case study in a watershed of southern Québec, Canada

This study aimed at capturing the spatial variability of landscape patterns and their trajectories of change from 1950 to 2000 within a watershed, which is representative of areas of intensive agricultural use. After an analysis of landscape features changes for the entire watershed based on aerial photographs, hierarchical clustering analysis provided a typology of landscape patterns for the cadastral lots. Following that, the trajectory of change of each lot was characterized (nature, importance, direction, rate of change). Seven types of landscape patterns are distinguished by the relative importance of different classes of landscape features and 51 trajectories of change were identified for the lots. The analysis shows that although the majority of lots were subjected to a homogenization of their landscape patterns since 1950, this trend is not entirely uniform and that since 2000 it occurs alongside trends towards diversification of certain landscape features on some lots. Furthermore, nearly a third of the lots are not following the main trajectories of change detected. Thus, the results suggest that extrinsic forces (policies, technologies) that are directing main changes in areas of intensive agricultural use toward uniformity could be modulated by internal forces (uses and values of the population). A better understanding of theses internal forces seems crucial to manage landscapes. From a methodology standpoint, although the hierarchical clustering analyses appear useful for understanding the spatial and temporal variability of landscape patterns, particular attention must be given to validating the typology chosen to characterize them.     

Landscape agronomy: a new field for addressing agricultural landscape dynamics

Landscape dynamics increasingly challenge agronomists to explain how and why agricultural landscapes are designed and managed by farmers. Nevertheless, agronomy is rarely included in the wide range of disciplines involved in landscape research. In this paper, we describe how landscape agronomy can help explain the relationship between farming systems and agricultural landscape dynamics. For this, we propose a conceptual model of agricultural landscape dynamics that illustrates the specific contribution of agronomy to landscape research. This model describes the relationship between three elements: farming practices, landscape patterns and natural resources. It can stimulate agronomists to deal with research issues in agricultural landscape dynamics and enhance the interdisciplinary integration of farming systems in wider landscape research. On these premises, we discuss the main research issues that will benefit from an active involvement of agronomy, to understand, but also to assess landscape dynamics and to design relevant decision support systems.