How managers and city dwellers relate to spontaneous vegetation in cities: Towards an integrative approach

The promotion of spontaneous vegetation is recognized as a promising way to develop urban biodiversity at multiple scales. However, enhancing spontaneous vegetation in highly anthropized spaces such as cities can lead to resistance from the various urban actors who plan, manage, and use the city. An integrated approach analyzing the links between ecological, psychosocial, governance, and management issues is thus required. Here we used complementary methods (focus groups, interviews) to analyze the relationships of municipal field operatives and city dwellers to spontaneous vegetation in the streets of a French medium-sized city. We show that municipal elected officials and service director move towards a biodiversity-friendly strategy, but that the management system at all hierarchical levels must be engaged with to achieve a shared and collaborative transition to sustainability. While field operatives are rather favorable to spontaneous vegetation, their practices and their ability to change are highly dependent on psychosocial, organizational, and technical parameters that have to be aligned with ecological objectives. Concerning city dwellers, the majority holds a positive view of spontaneous vegetation, yet a considerable proportion of them seem indifferent to this vegetation. The provisioning of ecological information in situ (i.e., stickers with plant information on pavements) moderately improves their perceptions of spontaneous street vegetation. This educational approach should be accompanied by other approaches to amplify the effect for changing attitudes. These differing results are of timely interest to help devise and build an integrated socio-ecological system, and to find social and organizational levers to improve people–nature relationships in the city.     

Regime shifts in a socio-ecological model of farmland abandonment

We developed a mathematical model with two-way linked socio-ecological dynamics to study farmland abandonment and to understand the regimes shifts of this socio-ecological system. The model considers that migration is a collective behavior socio-economically driven and that the ecosystem is dynamic. The model identifies equilibria that vary from mass migration, farmland abandonment, and forest regeneration, to no migration and forest eradication; partial migration and/or coexistence of farmland and forest also constitute possible equilibria. Overall, the model reflects farmland abandonment processes observed in the field and illustrates the importance of the complex interlinked mechanisms between the social and ecological systems determining farmland abandonment, that are not evident when approached independently. The model dynamics show that the hysteresis on the social dynamics renders regimes shifts difficult to reverse, and that this difficulty is accentuated when considering the ecological system dynamic. Similar models could be applied to other socio-ecological systems to help their management.     

Wetland effects on lake water quality in the Minneapolis/St. Paul metropolitan area

A method developed to evaluate the cumulative effect of wetland mosaics on water quality was applied to 33 lake watersheds in the seven-county region surrounding Minneapolis-St. Paul, Minnesota. A geographic information system (GIS) was used to record and measure landscape variables derived from aerial photos. Twenty-seven watershed land-use and land-cover variables were reduced to eight principal components which described 85% of the variance among watersheds. Relationships between lake water quality variables and the first six principal components plus an index of lake mixis were analyzed through stepwise multiple regression analysis. A combination of three landscape components (wetland/watershed area, agriculture/wetlands, and forest/soils components) explained 49% of the variance in a trophic state index, even though most of the lakes examined were already highly eutrophic, and thus were influenced by internal loading. The regression equations explained a range of 14 to 76% of the variation in individual water quality variables. Forested land-use was associated with lower lake trophic state, chloride, and lead. High lake trophic state was associated with agricultural land-use and with wetland distance from the lake of interest. The extent of wetlands was associated with low total lead and high color in lakes downstream. Wet meadows or herbaceous, seasonally-flooded wetlands contributed more to lake water color than did cattail marshes.     

An agent-based approach to model future residential pressure on a regional landscape

This paper presents a framework to model future residential demand for housing in a polycentric region. The model, called HI-LIFE (Household Interactions through LIFE cycle stages), builds on Agent-Based Modelling (ABM) paradigms. In contrast to traditional equilibrium-based urban economics models that assume a homogenous population of rational actors, ABM focuses on the diversity of heterogeneous household agents and their behaviour in time and in space. The model simulates land-use patterns at the regional scale by integrating qualitative knowledge of agent location preferences with quantitative analysis of urban growth dynamics within a high resolution spatial modelling framework. The model was calibrated for the region of East Anglia in the UK using a semi-quantitative procedure. Simulation of urban dynamics for the future was undertaken for a 25 year period with the assumption of a continuation of baseline behavioural trends. The results demonstrated non-uniform, spatial patterns of urban sprawl with some locations experiencing greater urban development pressure than others. The town of Brundall, in particular, has a large potential demand for residential housing because of its proximity to the principle city, Norwich. As Brundall is also located close to a national park and a river, new housing development in this area would increase the risk of ecological impacts and flood damage. By modelling explicitly agent behaviour and interactions, ABM can simulate the response and adaptation strategies of a population to changing circumstances. This makes ABM especially well suited to the analysis of environmental change and landscape ecology pressures through scenario modelling.     

Forest fragmentation, climate change and understory fire regimes on the Amazonian landscapes of the Xingu headwaters

Understory fire modeling is a key tool to investigate the cornerstone concept of landscape ecology, i.e. how ecological processes relate to landscape structure and dynamics. Within this context, we developed FISC??a model that simulates fire ignition and spread and its effects on the forest carbon balance. FISC is dynamically coupled to a land-use change model to simulate fire regimes on the Amazonian landscapes of the Xingu Headwaters under deforestation, climate change, and land-use management scenarios. FISC incorporates a stochastic cellular automata approach to simulate fire spread across agricultural and forested lands. CARLUC, nested in FISC, simulates fuel dynamics, forest regrowth, and carbon emissions. Simulations of fire regimes under modeled scenarios revealed that the major current and future driver of understory fires is forest fragmentation rather than climate change. Fire intensity proved closely related to the landscape structure of the remaining forest. While climate change may increase the percentage of forest burned outside protected areas by 30% over the next four decades, deforestation alone may double it. Nevertheless, a scenario of forest recovery and better land-use management would abate fire intensity by 18% even in the face of climate change. Over this time period, the total carbon balance of the Xingu??s forests varies from an average net sink of 1.6?ton?ha^?1?year^?1 in the absence of climate change, fire and deforestation to a source of ?0.1?ton?ha^?1?year^?1 in a scenario that incorporates these three processes.     

Land-use and land-cover dynamics in response to changes in climatic,biological and socio-political forces: the case of southwestern Ethiopia

Few studies of land-use/land-cover change provide an integrated assessment of the driving forces and consequences of that change, particularly in Africa. Our objectives were to determine how driving forces at different scales change over time, how these forces affect the dynamics and patterns of land use/land cover, and how land-use/land-cover change affects ecological properties at the landscape scale. To accomplish these objectives, we first developed a way to identify the causes and consequences of change at a landscape scale by integrating tools from ecology and the social sciences and then applied these methods to a case study in Ghibe Valley, southwestern Ethiopia. Maps of land-use/land-cover change were created from aerial photography and Landsat TM imagery for the period, 1957–1993. A method called `ecological time lines' was developed to elicit landscape-scale explanations for changes from long-term residents. Cropland expanded at twice the speed recently (1987–1993) than two decades ago (1957–1973), but also contracted rapidly between 1973–1987. Rapid land-use/land cover change was caused by the combined effects of drought and migration, changes in settlement and land tenure policy, and changes in the severity of the livestock disease, trypanosomosis, which is transmitted by the tsetse fly. The scale of the causes and consequences of land-use/land-cover change varied from local to sub-national (regional) to international and the links between causes and consequences crossed scales. At the landscape scale, each cause affected the location and pattern of land use/land cover differently. The contraction of cropland increased grass biomass and cover, woody plant cover, the frequency and extent of savanna burning, and the abundance of wildlife. With recent control of the tsetse fly, these ecological changes are being reversed. These complex patterns are discussed in the context of scaling issues and current conceptual models of land-use/land-cover change.     

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.     

Modeling the spatially dynamic distribution of humans in the Oregon (USA) Coast Range

A common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the socioeconomic and ecological processes under study are sensitive to a range of human habitation. In this paper, we characterize the spatial dynamic distribution of humans throughout the forest landscape of western Oregon (USA). We develop an empirical model describing the spatial distribution and rate of change in historic building densities as a function of a gravity index of development pressure, existing building densities, slope, elevation, and existing land use zoning. We use the empirical model to project changes in building densities that are applied to a 1995 base map of building density to describe future spatial distributions of buildings over time. The projected building density maps serve as inputs into a multidisciplinary landscape-level analysis of socioeconomic and ecological processes in Oregon's Coast Range Mountains. This revised version was published online in July 2006 with corrections to the Cover Date.     

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.     

Landscape regularity modelling for environmental challenges in agriculture

In agricultural landscapes, methods to identify and describe meaningful landscape patterns play an important role to understand the interaction between landscape organization and ecological processes. We propose an innovative stochastic modelling method of agricultural landscape organization where the temporal regularities in land-use are first identified through recognized Land-Use Successions before locating these successions in landscapes. These time–space regularities within landscapes are extracted using a new data mining method based on Hidden Markov Models. We applied this methodological proposal to the Niort Plain (West of France). We built a temporo-spatial analysis for this case study through spatially explicit analysis of Land-Use Succession dynamics. Implications and perspectives of such an approach, which links together the temporal and the spatial dimensions of the agricultural organization, are discussed by assessing the relationship between the agricultural landscape patterns defined using this approach and ecological data through an illustrative example of bird nests.     

Drivers of the dynamics in net primary productivity across ecological zones on the Mongolian Plateau

Understanding the drivers and mechanisms of the dynamics in grassland productivity is prerequisite for studying effective resource institutions and policies that can be used to govern grassland resources sustainably. We present a diagnostic analysis of the major drivers of the dynamics in grassland net primary productivity (NPP) across ecological zones on the Mongolian Plateau. We estimated a spatial panel data model for NPP (1986–2009) as a function of climatic and socioeconomic variables. Static and dynamic spatial panel models were estimated in each of the sub-regions, which were classified based on rural livelihoods and ecological models of grassland dynamics, to identify the major drivers of NPP dynamics. The statistical modeling results indicated that the major drivers of NPP dynamics vary across the six sub-regions. Grain output was the major predictor of NPP dynamics in the farming and farming-grazing zones of Inner Mongolia. Precipitation and livestock populations both had significantly positive relationships with NPP in the two grazing zones of Inner Mongolia. However, in Mongolia, livestock populations was the only significant predictor of NPP in the grazing zone with relatively stable climate, and precipitation was the only significant predictor of NPP in the grazing zone with highly variable climate. Human land-use activities and livestock management behaviors and the bidirectional causal relationships between livestock populations and NPP could explain the positive relationships between livestock population and grassland NPP. The heterogeneous drivers of NPP dynamics across space indicated the necessity of diverse resource polices and institutions for sustainable governance of grassland resources.     

The influences of land-use changes on hydrology and riparian environment in a northern Japanese landscape

Temporal changes in a hydrological system and riparian ecosystem were examined with reference to land-use conversion in order to clarify the linkages between these two systems. First, the hydrological system of the Toikanbetsu River basin was divided into three components that measure water retention, inundation and conveyance. Variation in the hydrological system was expressed as a basis of delineating the three components and estimating their functions. The rainfall-runoff system was also examined using a model which can predict responses of surface-, subsurface- and base flows on rainfall intensity. Second, areas and fragmentation of the riparian forests, maximum stream temperature in summer and amount of coarse woody debris (CWD) were selected as parameters indicating the condition of the riparian ecosystem. Temporal changes in stream temperature and amount of CWD were estimated using multiple regression analysis and analysis of variance, respectively. The results indicated that the hydrological system has been altered since the 1970s, increasing flood peaks by 1.5–2.5 times and shortening peak appearance by 7 hours. Riparian forests have been disappearing since the 1960s due to extensive development of agricultural lands and river channelization. The summer maximum stream temperature increased from 22 °C in 1947 to 28 °C at present. The amount of CWD should substantially decrease with river channelization and associated forest cutting. Fish favoring cool water, such as masu salmon, could survive in 1947 although they are forced to migrate to cooler forested upstream tributaries now. The ecological systems were closely related to and distinctly altered by land-use. Finally, we propose a new perspective for understanding the two interrelated systems. Riparian ecosystems can be restored by restoring water retention and inundation functions, which also reduce the flood hazard generated by elevated flood peaks.     

Assessing land-use impacts on biodiversity using an expert systems tool

Habitat alteration, in the form of land-use development, is a leading cause of biodiversity loss in the U.S. and elsewhere. Although statutes in the U.S. may require consideration of biodiversity in local land-use planning and regulation, local governments lack the data, resources, and expertise to routinely consider biotic impacts that result from permitted land uses. We hypothesized that decision support systems could aid solution of this problem. We developed a pilot biodiversity expert systems tool (BEST) to test that hypothesis and learn what additional scientific and technological advancements are required for broad implementation of such a system. BEST uses data from the U.S. Geological Survey's Gap Analysis Program (GAP) and other data in a desktop GIS environment. The system provides predictions of conflict between proposed land uses and biotic elements and is intended for use at the start of the development review process. Key challenges were the development of categorization systems that relate named land-use types to ecological impacts, and relate sensitivities of biota to ecological impact levels. Although the advent of GAP and sophisticated desktop GIS make such a system feasible for broad implementation, considerable ongoing research is required to make the results of such a system scientifically sound, informative, and reliable for the regulatory process. We define a role for local government involvement in biodiversity impact assessment, the need for a biodiversity decision support system, the development of a prototype system, and scientific needs for broad implementation of a robust and reliable system.     

Public satisfaction with urban trees and their management in Australia: The roles of values,beliefs, knowledge,and trust

The success of urban forest management strategies is dependent on public support for and engagement with urban trees. Satisfaction with urban trees and their management, and the level of trust people have in urban tree managers, are useful for understanding public opinions. Yet these concepts, and the mechanisms leading to the formation of public opinions remain poorly explored in the literature. Here we explore how satisfaction with urban trees and with urban tree management, and trust in the agencies responsible for urban tree management, are explained by cognitive factors (values, beliefs, and knowledge) and socio-ecological contextual factors (tree presence/canopy cover, cultural diversity, and socioeconomic status) using an online survey of 16 local government areas in south-eastern Australia. Analyses of 2367 responses revealed that people’s opinions about trees in general (values and beliefs) were overwhelmingly positive, while their opinions about more contextualised measures such as satisfaction and trust were more mixed. Two distinct pathways that influence satisfaction were identified: one linked to beliefs about having trees in cities, and another one linked to trust in urban tree management. At the local government level, satisfaction was negatively associated with a measure of cultural diversity and very low levels of tree canopy cover, but not with socioeconomic disadvantage. Satisfaction with local trees could be improved by increasing the quality of ecological function of trees, such as habitat provision and tree diversity. Community engagement could also improve satisfaction and trust, particularly perceived procedural fairness of decision-making, reinforce positive beliefs about the outcomes of having trees in cities, and dispel negative beliefs. Engagement processes should recognise that people hold complex and diverse opinions about urban trees, and by incorporating these opinions into decision-making we can meet the increasingly complex and diverse expectations being placed on urban forests.     

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.     

Evaluating the role of ecosystem services in participatory land use planning: proposing a balanced score card

The application of the ecosystem services (ES) concept in land use planning has great potential to enhance the awareness of planning actors on their interactions. At the same time it can contribute to improve the linkage between the role of land use patterns and the understanding of land system functioning and its contribution to human well-being. The concept should be developed in a way that can be applicable in socio-ecological systems where nature and society are capable of enhancing their roles mutually. The objective of this paper is to suggest a standardized scheme and generalizable criteria to assess how successful the application of the ES concept contributed to facilitate participatory planning. We consider three potential advantages and three critical aspects for how to improve the applicability and relevance of the ES concept in planning. Hereon based, we present a balanced score card tool for which we broke down to advantages and risks into concrete questions. We illustrate the application of this approach with two case studies, representatives of two major governance schemes in relation to land use planning. We demonstrate that the balanced score card approach helps to reveal potential imbalances regarding the consideration of different ES groups. It supports testing the potential of the ES concept to enhance or not interactions of local and regional actors. We conclude that the framework should be reconsidered after a set of case studies to be developed into a monitoring tool for supporting planning practices.     

Land-use changes and sustainable development in mountain areas: a case study in the Spanish Pyrenees

Land-use changes affecting Mediterranean mountains represent the intensification of use in valley bottoms, accompanied by land-use conflicts, and a generalized abandonment of the hillslopes, which in the past were perfectly integrated in the system of land management. Farmland abandonment, reforestation, diminution of the livestock pressure and substitution of cereal crops by meadows are the most outstanding features of the recent land-use changes. The question is whether the new spatial organisation is in accordance with a longterm policy of sustainable development in mountain areas. The results obtained confirm that farmland abandonment on steep slopes — and the resulting colonization of old fields by a dense shrub cover — and afforestation contribute to control both soil erosion and surface runoff. As a result some of the most important rivers and alluvial fans have recently stabilized their sedimentary structures.     

Cropland change in southern Romania: a comparison of logistic regressions and artificial neural networks

Changes in cropland have been the dominating land use changes in Central and Eastern Europe, with cropland abandonment frequently exceeding cropland expansion. However, surprisingly little is known about the rates, spatial patterns, and determinants of cropland change in Eastern Europe. We study cropland changes between 1995 and 2005 in Argeş County in Southern Romania with two distinct modeling techniques. We apply and compare spatially explicit logistic regressions with artificial neural networks (ANN) using an integrated socioeconomic and environmental dataset. The logistic regressions allow identifying the determinants of cropland changes, but cannot deal with non-linear and complex functional relationships nor with collinearity between variables. ANNs relax some of these rigorous assumptions inherent in conventional statistical modeling, but likewise have drawbacks such as the unknown contribution of the parameters to the outcome of interest. We compare the outcomes of both modeling techniques quantitatively using several goodness-of-fit statistics. The resulting spatial predictions serve to delineate hotspots of change that indicate areas that are under more eminent threat of future abandonment. The two modeling techniques address two controversial issues of concern for land-change scientists: (1) to identify the spatial determinants that conditioned the observed changes and (2) to deal with complex functional relationships between influencing variables and land use processes. The spatially explicit insights into patterns of cropland change and in particular into hotspots of change derived from multiple methods provide useful information for decision-makers.     

Land-use and land-cover change processes in the Upper Uruguay Basin: linking environmental and socioeconomic variables

Landscape Ecology - Land-use and land-cover change affects both ecological and socioeconomic processes, motivating the integration of environmental and socioeconomic data to help understand this...