Ontologies for transparent integrated human-natural system modelling

We propose an approach to modular agent-based land use modelling, based on ontologies in their computer science sense: formal representations of conceptualisations. The approach is primarily aimed at addressing the issue of model transparency. Human-natural systems models involve large numbers of submodels, making them difficult to understand for those not involved in their construction. We show that using ontologies to represent the structure and state of a simulation model improves transparency in two ways: First, the information about the structure and state is decoupled from the simulation software and can be independently processed. Second, the logics on which ontologies are based reflect more commonsense understandings of the relationships among concepts than those of computer programming languages.     

Molecular fingerprinting of a new Kiwifruit cultivar (cv. Tsehelidis) and comparative analysis with cv. Hayward according to physicochemical properties

“Tsechelidis” is a new kiwifruit cultivar of Actinidia deliciosa species that was developed in North Greece (Episkopi, Imathia) through collaboration between Farmaplant S.A and Department of Agriculture Crop Production and Rural Environment, University of Thessaly.     

How to promote residents’ use of green space: An empirically grounded agent-based modeling approach

One focus of those responsible for making urban policies has been the improvement of green space effectiveness, including environmental plans and eco-city initiatives. In the evaluation of policy effectiveness, residents’ needs, values and preferences are critical but often overlooked. This study proposes an agent-based model (ABM) for simulating the effectiveness of policy measures on residents’ decision making with regard to the use of green space. Using a residential questionnaire survey conducted in Shanghai, China, we model individual decision making with artificial neural networks that account for the heterogeneous characteristics and imperfect rationality in the decision-making process, and compare three policy scenarios in local green space provision. The results of the model illustrate the unequal effectiveness of green space policies among different social groups and different types of green space (i.e., urban parks, neighborhood parks, and community gardens), and the sensitivity analysis suggests the key factors in different stages of green space provision. Based on the results, we argue that tailored policies are needed in order to meet residents’ heterogeneous needs; in fact, relatively “soft” policies, particularly those that promote social interaction and participation, play a significant role in the appeal of green space use. Finally, policy suggestions are provided for the optimization of green space provision.     

An agent-based approach to model land-use change at a regional scale

Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local scales, while its application in regional studies is limited. This paper describes first a conceptual framework for ABM to analyse and explore regional LUCC processes. Second, the conceptual framework is represented by combining different concepts including agent typologies, farm trajectories and probabilistic decision-making processes. Finally, the framework is illustrated through a case study in the Netherlands, where processes of farm cessation, farm expansion and farm diversification are shaping the structure of the landscape. The framework is a generic, straightforward approach to analyse and explore regional LUCC with an explicit link to empirical approaches for parameterization of ABM.     

Improving land change detection based on uncertain survey maps using fuzzy sets

In this paper we present a method for correcting inherent classification bias in historical survey maps with which subsequent land cover change analysis can be improved. We linked generalized linear modelling techniques for spatial uncertainty prediction to fuzzy set based operations. The predicted uncertainty information was used to compute fuzzy memberships of forest and non-forest classes at each location. These memberships were used to reclassify the original map based on decision rules, which take into consideration the differences in identification likelihood during the historical mapping. Since the forest area was underestimated in the original mapping, the process allows to correct this bias by favouring forest, especially where uncertainty was high. The analyses were performed in a cross-wise manner between two study areas in order to examine whether the bias correction algorithm would still hold in an independent test area. Our approach resulted in a significant improvement of the original map as indicated by an increase of the Normalized Mutual Information from 0.26 and 0.36 to 0.38 and 0.45 for the cross-wise test against reference maps in Pontresina and St. Moritz, respectively. Consequently subsequent land cover change assessments could be considerably improved by reducing the deviations from a reference change by almost 50 percent. We concluded that the use of logistic regression techniques for uncertainty modelling based on topographic gradients and fuzzy set operations are useful tools for predictively reducing uncertainty in maps and land cover change models. The procedure allows to get more reliable area estimates of crisp classes and it improves the computation of the fuzzy areas of classes. The approach has limitations when the original map shows high initial accuracy.     

2021年河北省主要蔬菜价格波动分析

依据河北省农业农村厅和全国农产品商务信息公共服务平台对河北省蔬菜价格的实时监控数据,以河北省2021年15种主要蔬菜价格为研究对象,对其进行横向、纵向比较,并分析影响蔬菜价格波动的因素.结果显示:2021年河北省蔬菜价格整体先降后升,价格明显低于山东省、江苏省和全国平均水平;第四季度价格走势与往年同期相比差异较大,茄果...     

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.     

Landscapes Toolkit: an integrated modelling framework to assist stakeholders in exploring options for sustainable landscape development

At present, stakeholders wishing to develop land use and management change scenarios at the landscape scale and to assess their corresponding impacts on water quality, biodiversity and economic performance, must examine the output of a suite of separate models. The process is not simple and presents a considerable deterrent to making such comparisons and impedes the development of more sustainable, multifunctional landscapes. To remedy this problem, we developed the Landscapes Toolkit, an integrated modelling framework that assists natural resource managers, policy-makers, planners and local communities explore options for sustainable landscape development. The Landscapes Toolkit links spatially-explicit disciplinary models, to enable integrated assessment of the water quality, biodiversity and economic outcomes of stakeholder-defined land use and management change scenarios. We use the Tully–Murray catchment in the Great Barrier Reef region of Australia as a case study to illustrate the development and application of the Landscapes Toolkit. Results show that the Landscapes Toolkit strikes a satisfactory balance between the inclusion of component models that sufficiently capture the richness of some key aspects of social-ecological system processes and the need for stakeholders to understand and compare the results of the different models. The latter is a prerequisite to making more informed decisions about sustainable landscape development. The flexibility of being able to add additional models and to update existing models is a particular strength of the Landscapes Toolkit design. Hence, the Landscapes Toolkit offers a promising modelling framework for supporting social learning and adaptive management through participatory scenario development and evaluation as well as being a tool to guide planning and policy discussions at the landscape scale.     

Exploring subtle land use and land cover changes: a framework for future landscape studies

Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.     

Predicting land use change: comparison of models based on landowner surveys and historical land cover trends

To make informed planning decisions, community leaders, elected officials, scientists, and natural resource managers must be able to evaluate potential effects of policies on land use change. Many land use change models use remotely-sensed images to make predictions based on historical trends. One alternative is a survey-based approach in which landowners’ stated intentions are modeled. The objectives of our research were to: (1) develop a survey-based landowner decision model (SBM) to simulate future land use changes, (2) compare projections from the SBM with those from a trend-based model (TBM), and (3) demonstrate how two alternative policy scenarios can be incorporated into the SBM and compared. We modeled relationships between land management decisions, collected from a mail survey of private landowners, and the landscape, using remotely-sensed imagery and ownership parcel data. We found that SBM projections were within the range of TBM projections and that the SBM was less affected by errors in image classification. Our analysis of alternative policies demonstrates the importance of understanding potential effects of targeted land use policies. While policies oriented toward increasing enrollment in the Conservation Reserve Program (CRP) resulted in a large (11–13%) increase in CRP lands, policies targeting increased forest thinning on private non-industrial lands increased low-density forest projections by only 1%. The SBM approach is particularly appropriate for landscapes including many landowners, because it reflects the decision-making of the landowners whose individual actions will result in collective landscape change.     

Modeling black carbon removal by city trees: Implications for urban forest planning

Urban forests provide multiple ecosystem services, including particulate matter (PM) air pollution removal. While previous studies have assessed relationships between atmospheric PM concentrations and urban land use and land cover, few studies have modeled PM removal by trees in relation to urban form (e.g., topography, land use, land cover, and proximity to emission sources). Particulate matter is a mixture of particles, including black carbon (BC), a byproduct of incomplete fossil fuel and biomass combustion with strong warming potential and linked to adverse health outcomes. We coupled empirical BC deposition data, collected from urban trees in Denton, Texas, with 226 urban form variables to generate land use regression models of annual and seasonal BC removal. Annual and seasonal models revealed emission source proxies, terrain exposure towards emission sources, and topographic exposure as influential to BC removal by trees. Regression equations were applied at one-meter resolution to estimate the BC removal potential of tree planting across the city. The resultant maps, which show regions of probable high and low BC removal by trees, can be used by arborists, urban foresters, landscape architects, and urban planners to inform urban forest design, planning, and decision-making.     

Dynamical coupling of multiscale land change models

No single model or scale can fully capture the causes of land change. For a given region, land changes may have different impacts at different places. Limits and opportunities imposed by biophysical and socio-economic conditions, such as local policies and accessibility, may induce distinct land change trajectories. These local land change trajectories may, in turn, indirectly affect other places, as local actions interact with higher-level driving forces. Such intraregional interdependencies cannot be captured by studies at a single scale, calling for multiscale and multilocality studies. This paper proposes a software organization for building computational models that support dynamical linking of multiple scales. This structure couples different types of models, such as cell-space models with agent-based models. We show how results in multiscale models can flow both in bottom-up and top-down directions, thus allowing feedback from local actors to regional scales. The proposal is general and independent of specific software, and it is effective to model intraregional, bottom-up and top-down interactions in land change models. To show the model’s potential, we develop a case study that shows how a multiscale model for the Brazilian Amazonia can include feedbacks between local to regional scales.     

A review of models of landscape change

Models of landscape change may serve a variety of purposes, from exploring the interaction of natural processes to evaluating proposed management treatments. These models can be categorized as either whole landscape models, distributional landscape models, or spatial landscape models, depending on the amount of detail included in the models. Distributional models, while widely used, exclude spatial detail important for most landscape ecological research. Spatial models require substantial data, now more readily available, via remote sensing, and more easily manipulated, in geographical information systems. In spite of these technical advances, spatial modelling is poorly developed, largely because landscape change itself is poorly understood.To facilitate further development of landscape models I suggest (1) empirical multivariate studies of landscape change, (2) modelling of individual landscape processes, (3) explicit study of the effect of model scale on model behavior, and (4) scaling-up results of studies, on smaller land areas, that have landscape relevance.     

Twenty-five years into “our common future”: are we heading in the right direction?

For a quarter of a century, sustainable development has been on the political and research agendas. Within the field of landscape ecology, a wide array of research has documented the effects of alternative land uses, analysed driving forces of land use change and developed tools for measuring such changes, to mention but a few developments. There have also been great advances in technology and data management. Nevertheless, unsustainable land use continues to occur and the science of landscape ecology has had less influence on landscape change than aimed for. In this paper we use Norwegian examples to discuss some of the reasons for this. We examine mismatches in the spatial and temporal scales considered by scientists, decision-makers and those who carry out land use change, consider how this and other factors hinder effective communication between scientists and practitioners, and urge for a stronger focus on what it is that motivates people to action. We suggest that the concept of landscape services can be useful not only for researchers but also provide valuable communication and planning tools. Finally, we suggest more emphasis on applying adaptive management in landscape ecology to help close the gaps, both between researchers and policy and, even more crucially, between researchers and practitioners.     

A systematic quantitative review of urban tree benefits,costs, and assessment methods across cities in different climatic zones

Urban trees can potentially mitigate environmental degradation accompanying rapid urbanisation via a range of tree benefits and services. But uncertainty exists about the extent of tree benefits and services because urban trees also impose costs (e.g. asthma) and may create hazards (e.g. windthrow). Few researchers have systematically assessed how urban tree benefits and costs vary across different cities, geographic scales and climates. This paper provides a quantitative review of 115 original urban tree studies, examining: (i) research locations, (ii) research methods, and (iii) assessment techniques for tree services and disservices. Researchers published findings in 33 journals from diverse disciplines including: forestry, land use planning, ecology, and economics. Research has been geographically concentrated (64% of studies were conducted in North America). Nearly all studies (91.3%) used quantitative research, and most studies (60%) employed natural science methods. Demonstrated tree benefits include: economic, social, health, visual and aesthetic benefits; identified ecosystem services include: carbon sequestration, air quality improvement, storm water attenuation, and energy conservation. Disservices include: maintenance costs, light attenuation, infrastructure damage and health problems, among others. Additional research is required to better inform public policy, including comparative assessment of tree services and disservices, and assessment of urban residents and land managers’ understanding of tree benefits and costs.     

Urban forests and social inequality in the Pacific Northwest

Research has shown there is a positive relationship between urban greenness and the well-being of city residents. But greenness is often unevenly distributed across a city, raising environmental justice issues. In 2011 and 2012 the USDA Forest Service, Forest Inventory and Analysis program installed ground plots in the urbanized areas of Oregon and Washington. We analyze these data for the urban areas west of the Cascade Mountains, linking it with demographic data from the U.S. Census to examine the relationship between greenness and socioeconomic status at a sub-regional scale. To explore some relations between urban forest measures and socioeconomic conditions and measures we developed four models: presence of tree canopy cover with a logistic mixed model, and on a subset of the data, percent tree canopy cover with a linear mixed model and tree count and tree species count with Poisson mixed models. We found that median household income, house value, land use, and years in the Tree City USA program contributed to explaining measures of greenness, such as canopy cover presence, percent canopy cover, tree counts, and tree species counts. This agrees with other studies, but does so at a broad scale covering the most densely populated areas in the Pacific Northwest.     

Communication between science, policy and citizens in public participation in urban forestry—Experiences from the Neighbourwoods project

The demand for sound scientific information and public participation is particularly great in urban forestry. Urban society's manifold perceptions, preferences and demands for urban forest goods and services need to be considered, indicating the necessity for socially inclusive planning processes. Successful policies can only be formulated by establishing close links with, for example, urban planning and municipal policies. Inherently, this means that close ties between research and policy are required. This article discusses the outcomes of the NeighbourWoods research and development project in which a wide range of tools for public participation were tested in six urban woodland case-studies across Europe. A distinction was made between characteristics of the specific participatory tools and those of the communication process between the facilitators (scientists) of the participation process and the end-users of information (local policy-makers). Public willingness to participate depends on factors such as existing controversy, emotions attached to the forest, and perceived dangers, e.g., in terms of threats to the status quo. Policy makers’ willingness to involve themselves depends on political interests, on prior experience with public participation processes, and on their trust in the facilitators of the public participation process. Findings confirm that a set of tools comprising a step-wise process from informing the public in an attractive way, collecting information on public opinion, towards fully participatory approaches such as direct involvement in decision-making is most likely to ensure socially inclusive planning. Communication with policy-makers requires a high degree of openness, clearly explaining every phase of the process, being open about each other's expectations, in short, by developing relationships based on mutual trust.     

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.