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With the deterioration of human-terrestrial relations and the intensification of global warming, development in all countries is facing difficulties. Whether in highly urbanized countries or in rapidly urbanizing developing countries such as China, the research on ecosystem services (ES) and land use management has attracted increasing attention. The general management of land use unilaterally pursues economic benefits and neglects ecological benefits, which aggravates the disparity between ecological development and the economic benefits of land resources. How to strike up a balance between ecologic protection and economic development remains a difficult problem during urbanization. It may be a better choice to formulate regional development strategies by combining natural conditions with humanistic and social tendencies. Identifying regional cultural ecosystem services (CES) and other important ES while performing zoning planning for regional land use can be a viable approach in land use management. Here, our study quantitatively evaluates the tourism experience of Xiaohuangshan Mountain (XHSM) and various ES, including recreation, biodiversity, history, aesthetics, soil conservation, surface water regulation, and soil nutrition. All ES were classified into four bundles for XHSM. Different ES bundles generated are suitable for different land use management methods and development forms according to their outstanding ES. The results show that quantifying and mapping regional ES bundles can provide the necessary information to support a win-win solution and provide decision support for land and spatial planning in areas with different social and ecological characteristics.

While considerable progress has been made in understanding land use change, land system science continues to face a number of grand challenges. This paper discusses these challenges with a focus on empirical land system studies, land system modelling and the analysis of future visions of land system change. Contemporary landscapes are contingent outcomes of past and present patterns, processes and decisions. Thus, empirical analysis of past and present land-use change has an important role in providing insights into the socio-economic and ecological processes that shape land use transitions. This is especially important with respect to gradual versus rapid land system dynamics and in understanding changes in land use intensity. Combining the strengths of empirical analysis with multi-scale modelling will lead to new insights into the processes driving land system change. New modelling methods that combine complex systems thinking at a local level with macro-level economic analysis of the land system would reconcile the multi-scale dynamics currently encapsulated in bottom-up and top-down modelling approaches. Developments in land use futures analysis could focus on integrating explorative scenarios that reflect possible outcomes with normative visions that identify desired outcomes. Such an approach would benefit from the broad and in-depth involvement of stakeholders in order to link scientific findings to political and societal decision-making culminating in a set of key choices and consequences. Land system models have an important role in supporting future land use policy, but model outputs require scientific interpretation rather than being presented as predictions. The future of land system science is strongly dependent on the research community's capacity to bring together the elements of research discussed in the paper, via empirical data collection and analysis of observed processes, computer simulation across scale levels and futures analysis of alternative, normative visions through stakeholder engagement. © 2012 Elsevier Ltd.

Historic land-cover/use change is important for studies on climate change, soil carbon, and biodiversity assessments. Available reconstructions focus on the net area difference between two time steps (net changes) instead of accounting for all area gains and losses (gross changes). This leads to a serious underestimation of land-cover/use dynamics with impacts on the biogeochemical and environmental assessments based on these reconstructions. In this study, we quantified to what extent land-cover/use reconstructions underestimate land-cover/use changes in Europe for the 1900-2010 period by accounting for net changes only. We empirically analyzed available historic land-change data, quantified their uncertainty, corrected for spatial-temporal effects and identified underlying processes causing differences between gross and net changes. Gross changes varied for different land classes (largest for forest and grassland) and led to two to four times the amount of net changes. We applied the empirical results of gross change quantities in a spatially explicit reconstruction of historic land change to reconstruct gross changes for the EU27 plus Switzerland at 1 km spatial resolution between 1950 and 2010. In addition, the reconstruction was extended back to 1900 to explore the effects of accounting for gross changes on longer time scales. We created a land-change reconstruction that only accounted for net changes for comparison. Our two model outputs were compared with five commonly used global reconstructions for the same period and area. In our reconstruction, gross changes led in total to a 56% area change (ca. 0.5% yr(-1)) between 1900 and 2010 and cover twice the area of net changes. All global reconstructions used for comparison estimated fewer changes than our gross change reconstruction. Main land-change processes were cropland/grassland dynamics and afforestation, and also deforestation and urbanization.

Land use change modelling, especially if done in a spatially-explicit, integrated and multi-scale manner, is an important technique for the projection of alternative pathways into the future, for conducting experiments that test our understanding of key processes in land use changes. Land-use change models should represent part of the complexity of land use systems. They offer the possibility to test the sensitivity of land use patterns to changes in selected variables. They also allow testing of the stability of linked social and ecological systems, through scenario building. To assess current progress in this field, a workshop on spatially explicit land-use/land-cover models was organised within the scope of the Land-Use and Land Cover Change project (LUCC). The main developments presented in this special issue concern progress in: 1) Modelling of drivers of land-use change; 2) modelling of scale dependency of drivers of land use change; 3) modelling progress in predicting location versus quantity of land-use change; 4) the incorporation of biophysical feedbacks in land-use change models. © 2001 Elsevier Science B.V. All rights reserved.

This paper introduces a data-driven agent-based simulation model of rural land exchange in the Netherlands. The model development process is part of an ongoing research program aiming at understanding the effects of climate change and socioeconomic drivers on agriculture land use and nature conservation. The first model version reported in this paper, is being developed for the Baakse Beek region in the Netherlands and is empirically grounded. The general framework described in this paper will be applied to another case study area in the Netherlands in the second phase of our research program and compare the projected land use patterns in the two case studies region.

Exploring how land use and the management of agro-ecosystems may evolve in the future is important for advancing scientific understanding and for informing policy makers and land managers of ways to respond and adapt sustainably to future change. In this paper, we investigate the future land-use trajectories of a semi-arid Mediterranean agro-ecosystem in south-eastern Spain using two different approaches: Markovian cellular automata and an agent-based approach. Methodologically, the paper offers a systematic method for agent parameterization to facilitate the development of an empirical agent-based scenario analysis. This approach is achieved by integrating information from cadastral and recent land-use maps, agricultural statistics, and sampled survey data. Through this integration, an effective approach is provided for up-scaling an agent typology from the sampled survey to the landscape scale. The output of the up-scaling provides a basis for modeling the aggregate effect of the responses of different types of farmers to environmental and policy changes across the study region. Empirically, the paper highlights the contrasting futures that the studied agro-ecosystem could have depending on the direction and intensity of the changes in environmental and policy conditions. The Markovian-CA land-use projection indicates further decline of rain-fed agriculture and describes the scope of the expansion of irrigated agriculture. The agent-based scenario analysis shows that the future of irrigated agriculture is highly sensitive to the expected future water scarcity. The analysis also reveals that the way that the future environmental and policy changes are conceptualized and presented to farmers and the range of different farmers in the agro-ecosystem determine the extent of the resulting aggregate effects of individual farmer reactions to future changes at the landscape scale. The empirical evidence of this research emphasizes the need for policy makers to consider multiple and interacting factors, including the design of interventions and likely farmer responses, which shape future agricultural land-use trajectories.

"The conflict between the conservation of biodiversity and recreation activities in the European landscape is intensifying. Managers of large nature areas are confronted with increasing numbers of visitors and decreasing biodiversity values. To accommodate the visitors while simultaneously protecting the biodiversity values they need to make changes in the landscape. Current legislation, a lack of knowledge on the recreation-biodiversity relationship, and the diverging point of view of stakeholders make it difficult to find consensual solutions. New approaches such as adaptive management and boundary management can help managers and stakeholders in the process of decision making. In these approaches the role of scientists has changed, as has the use of their tools. Using two research projects in Europe we explore how scientific tools are used in this new context. We argue that such tools (1) should be built on the interactions between recreation and biodiversity functions, (2) can be used interactively to encourage stakeholders to engage in a learning process, (3) allow local knowledge and data to be incorporated into them, and (4) generate output in the form of a map showing where the conflict areas and opportunities are located. These four key features will help managers to improve communication between themselves, stakeholders, and scientists, increase consensus between stakeholders on how the conflict should be perceived, explore solutions, and generate new knowledge. For future research we suggest investigating how adaptive management and boundary management can be used in a stepwise learning strategy and how uncertainties in the tools affect the learning process."

Degradation of natural and semi-natural landscapes has become a matter of global concern including for habitats in Western and Central Europe. For maintenance and restoration of grasslands belonging to the most species-rich biotopes in Central Europe, elaborate manage-ment is crucial. The Eifel National Park contains vast areas of semi-natural grasslands on the plateau Dreiborner Hochfläche in the area of the former military training site Vogelsang. To support decision-making for the management of this area, we built the GraS-Model (Grassland Succession Model), which mechanistically simulates the dynamics of grassland vegetation depending on the form of land use. When dealing with a complex landscape, entities acting at different scales have to be considered. While trees can be distinguished as single individuals, grasses and herbs are rather perceived as the sum of plants building up a certain cover. To cope with these unequal plant types, the GraS-Model is set up using a multimodeling approach. Representative species and plant functional groups of the herbaceous layer are modeled as compartments; their abundance is expressed as cover and only vegetative spread is considered. Difference equations are used to simulate their growth, which is adjusted using Briemle’s utilization numbers for cutting, grazing and trampling. Competitive power arises from the growth rate of each species in relation to that of the others. Herbaceous species growth was calibrated based on an extensive community data set of the study site. Trees, in contrast, are modeled using an individual-based approach. Each individual tree germinates, grows, disperses seeds, and ages in a spatially-explicit environment. As factors determining wood encroachment, inhibition by the grasslayer, interference of wild boar (Sus scrofa) and of ungulate browsers is considered. The plants are embedded in a landscape that is simulated as a detailed grid (100 m² cells), which allows inserting spatially-explicit input data from a GIS (geographic information system) so that the model can be easily connected to data of an existing landscape. Due to this raster-based approach, neighborhood relationships can be accounted for and different management regimes can be applied to distinct areas of the landscape. Pattern-oriented model evaluation revealed that the model produces results that are in line with general literature and experiences of local experts, and emulates observed successional pathways on the Dreiborner Hochfläche on the spatial as well as the temporal scale. After successful evaluation, the GraS-Model was used to predict the landscape developments of the Dreiborner Hochfläche under different management regimes for up to 100 years. It provides a highly detailed, spatially explicit prognosis integrating the initial vegetation composition and resulting neighborhood interactions which would not have been possible without the model. Forest encroachment on the Dreiborner Hochfläche was most strongly delayed by non-interference with the given high abundance of red deer (apart from mowing), whereas grazing by bison promoted a diverse landscape mosaic. Due to its high complexity, the GraS-Model initially exceeded the available computer main memory of current workstations when applied to the modeled Dreiborner Hochfläche (ca. 1500 ha). The landscape had to be fragmented and modeled separately. Therefore, the model was parallelized so that it can be run on a cluster, improving practicability and enhancing the ecological accuracy of the simulation results. The benefits of using the GraS-Model as decision support system are multifaceted: It gives highly detailed spatially explicit prognoses providing a strong basis for decision support and facilitating effectiveness and efficiency control; also it combines knowledge of different disciplines and enhances communication between scientists and stakeholders. Due to its modular design, the model can be continuously updated by integrating latest scientific knowledge, which can then be easily communicated. In the future, light, nutrients or moisture as environmental factors could be added in. Furthermore, other raster-based dynamic models (e.g. models of forest succession, nitrogen cycling, climate change, or animal mmovement) could be coupled.

[1] Coastal eutrophication is a worldwide problem [Diaz and Rosenberg, 2008; Selman et al., 2008]. It is largely caused by increased river transport of nutrients such as nitrogen (N), phosphorus (P), and carbon (C). Further distortion of coastal marine ecosystems is related to changing element ratios as a result of increasing N and P loading and decreasing river export of silica (Si). The main causes of increased river nutrient loading are the increasing livestock and crop production and fertilizer use, and increasing wastewater flows. There have been considerable gains in knowledge of current amounts and sources of N and P entering the terrestrial biosphere, and biogeophysical factors that control the amount of N and P ultimately exported by rivers to coastal ecosystems. Considerably less work has addressed how various socioeconomic factors and approaches to nutrient management affect N and P inputs to the terrestrial biosphere and subsequent impacts on river nutrient export. [2] This special section of Global Biogeochemical Cycles focuses on Past and Future Trends in Nutrient Export from Global Watersheds and Impacts on Water Quality and Eutrophication. It summarizes the recent work of the Global Nutrient Export fromWatersheds (NEWS) work group, using an integrated modeling approach connecting socioeconomic, nutrient management and biogeophysical factors to river export. [3] We present the second generation of the Global NEWS model [Mayorga et al., 2010; Seitzinger et al., 2010]. The first generation of the NEWS model was published in a 2005 Special Section of Global Biogeochemical Cycles [Beusen et al., 2005; Dumont et al., 2005; Harrison et al., 2005a; Harrison et al., 2005b; Seitzinger et al., 2005]. The NEWS model calculates river export of different forms of N, P, C and Si as a function of hydrology, morphology, land use and human activities in the river basin. More than 6000 river basins are included in the model. [4] Since 2005, three important developments took place on which we report in this special section: (1) several submodels for individual nutrient forms were updated [Beusen et al., 2009; Harrison et al., 2010; Mayorga et al., 2010; Seitzinger et al., 2010], such as including detergent sources of P in the DIP submodel [Harrison et al. 2010], and development of a submodel for river export of dissolved silica [Beusen et al., 2009]; (2) the models for different nutrient species were integrated into one modeling interface [Mayorga et al., 2010]; and (3) the model was used to analyze past trends (1970–2000) and four future scenarios (up to 2050). The future scenarios were based on the Millennium Ecosystem Assessment (MEA) [Alcamo et al., 2006]. We interpreted these scenarios to develop spatially explicit model inputs for diffuse sources of nutrients from agriculture and natural ecosystems [Bouwman et al., 2009] and sewage [Van Drecht et al., 2009], and hydrology [Fekete et al., 2010] consistent with the range of social, economic, policy, and ecological considerations in the four MEA scenarios. [5] Past and future trends in river nutrient export to coastal waters calculated from the NEWS model were used to analyze global trends [Seitzinger et al., 2010] as well as changes at the continental scale for South America andAfrica [van der Struijk and Kroeze, 2010; Yasin et al., 2010] or at the scale of individual river basins in Europe [Thieu et al., 2010; Yan et al., 2010], and a time series comparison of measured and modeled DIN export by the Changjiang River (1970–2003) [Yan et al., 2010]. We also developed a global perspective on indicators for nutrient inputs to land, and for changing nutrient ratios which could favor increases in nondiatom algal blooms [Billen et al., 2010; Garnier et al., 2010]. [6] Our results indicate that since 1970, river export of nutrients has been increasing considerably in many world regions. During the coming decades, DIN andDIP loads were projected to continue to increase in many world regions; however, particulate loads were projected to decrease. Perhaps the most surprising result of our analyses was that for large world areas, at least in one scenario, we calculate lower nutrient export rates in the future than in 2000, despite inInstitute of Marine and Coastal Sciences, Rutgers University, Rutgers/NOAA CMER Program, New Brunswick, New Jersey, USA. Netherlands Environmental Assessment Agency, Bilthoven, Netherlands. Environmental Systems Analysis Group, Wageningen University, Wageningen, Netherlands. School of Science, Open University of Netherlands, Heerlen, Netherlands.

Environmental Management, 44 (6), ISSN:0364-152X, ISSN:1364-152X, ISSN:1432-1009

The reform of the European Common Agricultural Policy (CAP) will fundamentally affect the decision behaviour of land users. So far transfer payments were coupled to specific forms of land use. The reform encourages land users to make decisions concerning production based solely on market aspects. The effects of the CAP reform on the Lahn Dill region in Germany are simulated with the spatially explicit land use model ProLand. The results show that land use decisions will be based stronger on site specific natural conditions than was the case in the Agenda 2000 scenario. The transfer payment volume directed into the region increases considerably.