Can we be certain about future land use change in Europe? A multi-scenario, integrated-assessment analysis

Multiple scenario land use simulation based on a coupled MOGA-PLUS model: a case of the Yellow River Basin

Land use changes have profoundly influenced global environmental dynamics. The Yellow River (YR), as the world's fifth-longest river, significantly contributes to regional social and economic growth due to its extensive drainage area, making it a key global player. To ensure ecological stability and coordinate land use demand, modeling the future land allocation patterns of the Yellow River Basin (YRB) will assist in striking a balance between land use functions and the optimization of its spatial design, particularly in water and sand management. In this research, we used a multi-objective genetic algorithm (MOGA) with the PLUS model to simulate several different futures for the YRB's land use between 1990 and 2020 and predict its spatial pattern in 2030. An analysis of the spatiotemporal evolution of land use changes in the YRB indicated that construction land expansion is the primary driver of landscape pattern and structure changes and ecological degradation, with climate change also contributing to the expansion of the watershed area. On the other hand, the multi-scenario simulation, constrained by specific targets, revealed that economic development was mainly reflected in land expansion for construction. At the same time, grassland and woodland were essential pillars to support the region's ecological health, and increasing the development of unused land emerged as a potential pathway towards sustainable development in the region. This study could be used as a template for the long-term growth of other large river basins by elucidating the impacts of human activities on land use and rationalizing land resource allocation under various policy constraints.

A Study on the Spatial-Temporal Evolution and Driving Factors of Non-Grain Production in China's Major Grain-Producing Provinces

Food self-sufficiency in a large country with 1.4 billion people is very important for the Chinese government, especially in the context of COVID-19 and the Russian-Ukrainian conflict. The objective of this paper is to explore the spatial-temporal evolution and driving factors of non-grain production in thirteen major grain-producing provinces in China, which account for more than 75% of China's grain production, using 2011-2020 prefecture-level statistics. In the present study, the research methodology included GIS spatial analysis, hot spot analysis, and spatial Durbin model (SDM). The findings of this study are as follows: (1) The regions with a higher level of non-grain production were mainly concentrated in the central and western regions of Inner Mongolia, the middle and lower reaches of Yangtze River and Sichuan, while the regions with a low level of non-grain production were mainly distributed in the Northeast Plain. The regions with a higher proportion of grain production to the national total grain production were concentrated in the Northeast Plain, the North China Plain, and the Middle and Lower Yangtze River Plain of China. The hot spot regions with changes in non-grain production levels were mainly distributed in the Sichuan region and Alashan League City in Inner Mongolia, and the cold spot regions were mainly distributed in Hebei, Shandong, Henan, and other regions. (2) An analysis of the SDM indicated that the average air temperature among the natural environment factors, the ratio of the sum of gross secondary and tertiary industries to GDP, the ratio of gross primary industry to the GDP of economic development level, the urbanization rate of social development, and the difference in disposable income per capita between urban and rural residents of the urban-rural gap showed positive spatial spillover effects. The grain yield per unit of grain crop sown area of grain production resource endowment, the total population of social development, and the area sown to grain crops per capita of grain production resource endowment all showed negative spatial spillover effects. The research results of this paper can provide a reference for the country to carry out the governance of non-grain production and provide a reference for China's food security guarantee.

Developing socio-ecological scenarios: A participatory process for engaging stakeholders

Deltas are experiencing profound demographic, economic and land use changes and human-induced catchment and climate change. Bangladesh exemplifies these difficulties through multiple climate risks including subsidence/sea-level rise, temperature rise, and changing precipitation patterns, as well as changing management of the Ganges and Brahmaputra catchments. There is a growing population and economy driving numerous more local changes, while dense rural population and poverty remain significant. Identifying appropriate policy and planning responses is extremely difficult in these circumstances. This paper adopts a participatory scenario development process incorporating both socio-economic and biophysical elements across multiple scales and sectors as part of an integrated assessment of ecosystem services and livelihoods in coastal Bangladesh. Rather than simply downscale global perspectives, the analysis was driven by a large and diverse stakeholder group who met with the researchers over four years as the assessment was designed, implemented and applied. There were four main stages: (A) establish meta-framework for the analysis; (B) develop qualitative scenarios of key trends; (C) translate these scenarios into quantitative form for the integrated assessment model analysis; and (D) a review of the model results, which raises new stakeholder insights (e.g., preferred adaptation and policy responses) and questions. Step D can be repeated leading to an iterative learning loop cycle, and the process can potentially be ongoing. The strong and structured process of stakeholder engagement gave strong local ownership of the scenarios and the wider process. This process can be generalised for widespread application across socio-ecological systems following the same four-stage approach. It demands sustained engagement with stakeholders and hence needs to be linked to a long-term research process. However, it facilitates a more credible foundation for planning especially where there are multiple interacting factors.

The Taiwan Climate Change Projection Information and Adaptation Knowledge Platform: A Decade of Climate Research

Taiwan’s climate change projections have always presented a challenge due to Taiwan’s size and unique meteorological and geographical characteristics. The Taiwan Climate Change Projection Information and Adaptation Knowledge Platform (TCCIP), funded by the Ministry of Science and Technology, Taiwan, is a decade-long climate research project with the most predominant climate data provider and national adaptation policymaking in the country. This paper outlines the evolution of the project. It describes the project’s major achievements, including climate projection arising from participation in the WCRP Coupled Model Inter-comparison Project (CMIP), dynamically and statistically downscaled data with resolutions up to 5 km grid, impact assessments of various themes, such as flooding, as well as the support of national policies through approaches including risk maps, climate data, and knowledge brokering.

Diversity of European habitat types is correlated with geography more than climate and human pressure

Habitat richness, that is, the diversity of ecosystem types, is a complex, spatially explicit aspect of biodiversity, which is affected by bioclimatic, geographic, and anthropogenic variables. The distribution of habitat types is a key component for understanding broad-scale biodiversity and for developing conservation strategies. We used data on the distribution of European Union (EU) habitats to answer the following questions: (i) how do bioclimatic, geographic, and anthropogenic variables affect habitat richness? (ii) Which of those factors is the most important? (iii) How do interactions among these variables influence habitat richness and which combinations produce the strongest interactions? The distribution maps of 222 terrestrial habitat types as defined by the Natura 2000 network were used to calculate habitat richness for the 10 km × 10 km EU grid map. We then investigated how environmental variables affect habitat richness, using generalized linear models, generalized additive models, and boosted regression trees. The main factors associated with habitat richness were geographic variables, with negative relationships observed for both latitude and longitude, and a positive relationship for terrain ruggedness. Bioclimatic variables played a secondary role, with habitat richness increasing slightly with annual mean temperature and overall annual precipitation. We also found an interaction between anthropogenic variables, with the combination of increased landscape fragmentation and increased population density strongly decreasing habitat richness. This is the first attempt to disentangle spatial patterns of habitat richness at the continental scale, as a key tool for protecting biodiversity. The number of European habitats is related to geography more than climate and human pressure, reflecting a major component of biogeographical patterns similar to the drivers observed at the species level. The interaction between anthropogenic variables highlights the need for coordinated, continental-scale management plans for biodiversity conservation.

An Agent-Based Model-Driven Decision Support System for Assessment of Agricultural Vulnerability of Sugarcane Facing Climatic Change

In recent years, there have been significant changes in weather patterns, mainly caused by sharp increases in temperature, increases in carbon dioxide, and fluctuations in precipitation levels, negatively impacting agricultural production. Agricultural systems are characterized by being vulnerable to the variation of biophysical and socioeconomic factors involved in the development of agricultural activities. Agent-based models (ABMs) enable the study, analysis, and management of ecosystems through their ability to represent networks and their spatial nature. In this research, an ABM is developed to evaluate the behavior and determine the vulnerability in the sugarcane agricultural system; allowing the capitalization of knowledge through characteristics such as social ability and autonomy of the modeled agents through fuzzy logic and system dynamics. The methodology used includes information networks for a dynamic assessment of agricultural risk modeled by time series, system dynamics, uncertain parameters, and experience; which are developed in three stages: vulnerability indicators, crop vulnerability, and total system vulnerability. The development of ABM, a greater impact on the environmental contingency is noted due to the increase in greenhouse gas emissions and the exponential increase in extreme meteorological phenomena threatening the cultivation of sugarcane, making the agricultural sector more vulnerable and reducing the yield of the harvest.

Large variability in response to projected climate and land-use changes among European bumblebee species

Bumblebees (Bombus ssp.) are among the most important wild pollinators, but many species have suffered from range declines. Land-use change, agricultural intensification, and the associated loss of habitat have been identified as drivers of the observed dynamics, amplifying pressures from a changing climate. However, these drivers are still underrepresented in continental-scale species distribution modeling. Here, we project the potential distribution of 47 European bumblebee species in 2050 and 2080 from existing European-scale distribution maps, based on a set of climate and land-use futures simulated through a regional integrated assessment model and consistent with the RCP-SSP scenario framework. We compare projections including (1) dynamic climate and constant land use (CLIM); (2) constant climate and dynamic land use (LU); and (3) dynamic climate and dynamic land use (COMB) to disentangle the effects of land use and climate change on future habitat suitability, providing the first rigorous continental-scale assessment of linked climate-land-use futures for bumblebees. We find that direct climate impacts, although variable across species, dominate responses for most species, especially under high-end climate change scenarios (up to 99% range loss). Land-use impacts are highly variable across species and scenarios, ranging from severe losses (up to 75% loss) to considerable gains (up to 68% gain) of suitable habitat extent. Rare species thereby tend to be disproportionally affected by both climate and land-use change. COMB projections reveal that land use may amplify, attenuate, or offset changes to suitable habitat extent expected from climate impact depending on species and scenario. Especially in low-end climate change scenarios, land use has the potential to become a game changer in determining the direction and magnitude of range changes, indicating substantial potential for targeted conservation management.

Agricultural Land Transition in the “Groundnut Basin” of Senegal: 2009 to 2018

The study aims to reveal the transition features of agricultural land use in the Groundnut Basin of Senegal from 2009 to 2018, especially the impact of urbanization on agricultural land and the viewpoint of farmland spatiotemporal evolution. Integrated data of time series MCD12Q1 land-use images of 2009, 2012, 2015, and 2018 were used to provide a land transition in agricultural and urban areas through the synergistic methodology. Socio-economic data was also used to serve as a basis for the argument. The results highlight that: (1) Agricultural land increased by 14.53%, with a dynamic index of 1.45 from 2009–2018. (2) Over the same period, urbanization increased by 2.80%, with a dynamic index of 0.28. (3) In different regions, the transition of agricultural land in Kaffrine is most intense (expansion rate: 22.80%). The same situation of urbanization happened in Thiès Region with a value of 7.94%. Except for Thiès, agricultural land in other regions has not yet been subject to major pressure due to urbanization. Overall, the farming system in Groundnut Basin is an extensive model, the recommendations from the point of view of land-use planning and land law are necessary to ensure efficient agricultural land management in the area.

Future scenarios impact on land use change and habitat quality in Lithuania

Anticipating future land use and land cover (LULC) changes can improve our knowledge of the complexity of human-environment interactions that lead to transformations in the landscape. Therefore, it is key to understand these LULC changes under different scenarios and how they affect habitat quality (HQ) a key indicator for ecosystem services (ES) supply quality. This work aims to study the impacts of LULC changes under different scenarios: business as usual (A0), urbanisation (A1), land abandonment and afforestation (A2) and agriculture intensification (A3) in 2050. To simulate future LULC changes we applied the Cellular Automata (CA) method, and to assess HQ, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used. Spatial autocorrelation was assessed with a Moran's I index and the Getis Ord* hotspot analysis. The result showed that the LULC model calibration and validation were accurate (80%). Between 1990 and 2018 there was an increase in urban areas and forest and woodlands, which was reflected in the A0 scenario in 2050. Under the A1 scenario there was an increase in the urban area (4628 ha) compared to 2018, and in the most important cities (e.g., Vilnius, Kaunas, Klaipeda) in the scenario A2 there was an increase of 375,820 ha of woodland and forest. Finally, under the scenario A3, a large growth in cropland area (884,030 ha) was identified. HQ model had a better validation using three cover density data (r² = 0.67), than with imperviousness (r² = 0.26). A2 scenario showed the highest HQ and A3 scenario have the lowest HQ. The land uses of 1990, 2018, and A3 scenario had a clustered distribution while A0, A1 and A2 showed a random pattern. The results can support policy-makers by assessing the impact of future LULC changes in Lithuania.

Integrated assessment of the food-water-land-ecosystems nexus in Europe: Implications for sustainability

Climate and socio-economic change impacts are likely to cross traditional sectoral and regional boundaries with cascading indirect, and potentially far-reaching, repercussions. This is particularly important for the food-water-land-ecosystems (FWLE) nexus, which is fundamental for the achievement of at least six of the seventeen Sustainable Development Goals (SDGs). A holistic understanding of the FWLE nexus interactions and how and to what extent various exogenous drivers of change affect them is therefore central to cross-sectoral adaptation planning. Here, we present such an integrated assessment for Europe applying a regional Integrated Assessment Platform (IAP). The study explores a wide range of future climate and socio-economic scenarios using more than 900 model simulations. The results show that food production is likely to be the main driver of Europe's future landscape change dynamics (with or without climate change). Agriculture and land use allocation is often driven by complex cross-sectoral interactions with cascading effects on other sectors such as forestry, biodiversity, and water under the various scenarios. The modelling also highlighted that while sustaining current levels of food production at the European level could be achievable under most climate and socio-economic scenarios, there are significant regional differences with winners and losers. The analysis raises the question of whether current production and consumption policies are sustainable in the long-term. Such systematic integrated model-based analysis plays a crucial role in informing development of cross-sectoral policies that maximise synergies and minimise trade-offs across nexus sectors, regions, and scenarios. This is essential to achieve the SDGs.

Shared Socio-economic Pathways for European agriculture and food systems: The Eur-Agri-SSPs

Scenarios describe plausible and internally consistent views of the future. They can be used by scientists, policymakers and entrepreneurs to explore the challenges of global environmental change given an appropriate level of spatial and sectoral detail and systematic development. We followed a nine-step protocol to extend and enrich a set of global scenarios - the Shared Socio-economic Pathways (SSPs) - providing regional and sectoral detail for European agriculture and food systems using a one-to-one nesting participatory approach. The resulting five Eur-Agri-SSPs are titled (1) Agriculture on sustainable paths, (2) Agriculture on established paths, (3) Agriculture on separated paths, (4) Agriculture on unequal paths, and (5) Agriculture on high-tech paths. They describe alternative plausible qualitative evolutions of multiple drivers of particular importance and high uncertainty for European agriculture and food systems. The added value of the protocol-based storyline development process lies in the conceptual and methodological transparency and rigor; the stakeholder driven selection of the storyline elements; and consistency checks within and between the storylines. Compared to the global SSPs, the five Eur-Agri-SSPs provide rich thematic and regional details and are thus a solid basis for integrated assessments of agriculture and food systems and their response to future socio-economic and environmental changes.

Assessing Ecosystem Services Supplied by Agroecosystems in Mediterranean Europe: A Literature Review

Agricultural landscapes in the Mediterranean region may be considered as social-ecological systems that are important for biodiversity conservation whilst contributing to a wide range of ecosystem services. This literature review aims to identify the current state and biases of ecosystem service assessment in agroecosystems within the Mediterranean region, evaluate pressures impacting on agroecosystems and their services, and practices that promote ecosystem service synergies in Mediterranean agroecosystems. A total of 41 papers were selected for analysis from a set of 573 potentially relevant papers. Most of the selected papers focused on supporting, regulating and provisioning services, and mostly assessed ecosystem structure or services in the European Mediterranean context. Literature about benefits and values ascribed to by communities and stakeholders remain limited. Results presented here support the notion of multifunctional Mediterranean agroecosystems and multiple synergies were recorded in this review. Publications dealing with pressures that related to agricultural practices and demographic changes were in the majority and impact on different cropping systems. This review highlights the need to carry out integrated ecosystem service assessments that consider the multiple benefits derived from agroecosystems and which may be used to identify management practices that lead to the improvement of ecosystem services capacities and flows.

Modeling Major Rural Land-Use Changes Using the GIS-Based Cellular Automata Metronamica Model: The Case of Andalusia (Southern Spain)

The effective and efficient planning of rural land-use changes and their impact on the environment is critical for land-use managers. Many land-use growth models have been proposed for forecasting growth patterns in the last few years. In this work; a cellular automata (CA)-based land-use model (Metronamica) was tested to simulate (1999–2007) and predict (2007–2035) land-use dynamics and land-use changes in Andalucía (Spain). The model was calibrated using temporal changes in land-use covers and was evaluated by the Kappa index. GIS-based maps were generated to study major rural land-use changes (agriculture and forests). The change matrix for 1999–2007 showed an overall area change of 674971 ha. The dominant land uses in 2007 were shrubs (30.7%), woody crops on dry land (17.3%), and herbaceous crops on dry land (12.7%). The comparison between the reference and the simulated land-use maps of 2007 showed a Kappa index of 0.91. The land-cover map for the projected PRELUDE scenarios provided the land-cover characteristics of 2035 in Andalusia; developed within the Metronamica model scenarios (Great Escape; Evolved Society; Clustered Network; Lettuce Surprise U; and Big Crisis). The greatest differences were found between Great Escape and Clustered Network and Lettuce Surprise U. The observed trend (1999–2007–2035) showed the greatest similarity with the Big Crisis scenario. Land-use projections facilitate the understanding of the future dynamics of land-use change in rural areas; and hence the development of more appropriate plans and policies

Future land use changes in a peri-urban context: Local stakeholder views

Future land use/cover change (LUCC) analysis has been increasingly applied to spatial planning instruments in the last few years. Nevertheless, stakeholder participation in the land use modelling process and analysis is still low. This paper describes a methodology engaging stakeholders (from the land use planning, agriculture, and forest sectors) in the building and assessment of future LUCC scenarios. We selected as case study the Torres Vedras Municipality (Portugal), a peri-urban region near Lisbon. Our analysis encompasses a participatory workshop to analyse LUCC model outcomes, based on farmer LUCC intentions, for the following scenarios: A0 - current social and economic trend (Business as Usual); A1 - regional food security; A2 - climate change; and B0 - farming under urban pressure. This analysis allowed local stakeholders to develop and discuss their own views on the most plausible future LUCC for the following land use classes: artificial surfaces, non-irrigated arable land, permanently irrigated land, permanent crops and heterogeneous agricultural land, pastures, forest and semi-natural areas, and water bodies and wetlands. Subsequently, we spatialized these LUCC views into a hybrid model (Cellular Automata - Geographic Information Systems), identifying the most suitable land conversion areas. We refer to this model, implemented in NetLogo, as the stakeholder-LUCC model. The results presented in this paper model where, when, why, and what conversions may occur in the future in regard to stakeholders' points of view. These outcomes can better enable decision-makers to perform land use planning more efficiently and develop measures to prevent undesirable futures, particularly in extreme events such as scenarios of food security, climate change, and/or farming under pressure.

Riparian wetland rehabilitation and beaver re-colonization impacts on hydrological processes and water quality in a lowland agricultural catchment

Quantifying the catchment water balance and the characterization of its water quality changes are effective tools for establishing the response of catchments to shifting land management practices. Here we assess long-term hydrological partitioning and stream water chemistry over a 30-year period in a rural mixed land use catchment in northern Germany undergoing riparian wetlands and widespread re-colonization by beavers (Castor fiber) along the river network. We used long-term spatially distributed stream discharge, groundwater levels and surface water quality data with a simple monthly water balance model, changes in the variability in discharge measurements, and statistical analysis of spatio-temporal changes in stream water quality to assess long-term changes. Water balance estimates indicated high proportions of evapotranspiration loss (~90% of total precipitation) and relatively low groundwater recharge (<5% of total precipitation) prior to riparian rehabilitation in 2000. Increasing groundwater levels from 2000 to 2017 and the relatively linear nature of the catchment storage - discharge relationship, indicate a gradual increase in groundwater recharge (buts still <10% of total precipitation). Wetland rehabilitation, greatly enhanced by increasing beaver populations, resulted in longer water transit times in the stream network, less linear storage-discharge relationship and a loss of daily stream variability, increased DOC concentrations, isotopic evaporative enrichment downstream, and moderated stream temperatures. There was limited long-term water quality improvements from wetland rehabilitation on either nitrate or total phosphorus concentrations, with unchanged seasonal summer and winter peak concentrations for phosphorus and nitrate, respectively. This likely reflects the long-term legacy of fertilizer use on nutrient reservoirs in the catchment's soils, aquifers, and stream network. These long-term changes in hydrology and stream chemistry resulting from riparian rehabilitation and changes in agricultural management practices provide invaluable insights into catchment functioning and an evidence base for future planning in relation to long-term climatic changes.

A protocol to develop Shared Socio-economic Pathways for European agriculture

Moving towards a more sustainable future requires concerted actions, particularly in the context of global climate change. Integrated assessments of agricultural systems (IAAS) are considered valuable tools to provide sound information for policy and decision-making. IAAS use storylines to define socio-economic and environmental framework assumptions. While a set of qualitative global storylines, known as the Shared Socio-economic Pathways (SSPs), is available to inform integrated assessments at large scales, their spatial resolution and scope is insufficient for regional studies in agriculture. We present a protocol to operationalize the development of Shared Socio-economic Pathways for European agriculture - Eur-Agri-SSPs - to support IAAS. The proposed design of the storyline development process is based on six quality criteria: plausibility, vertical and horizontal consistency, salience, legitimacy, richness and creativity. Trade-offs between these criteria may occur. The process is science-driven and iterative to enhance plausibility and horizontal consistency. A nested approach is suggested to link storylines across scales while maintaining vertical consistency. Plausibility, legitimacy, salience, richness and creativity shall be stimulated in a participatory and interdisciplinary storyline development process. The quality criteria and process design requirements are combined in the protocol to increase conceptual and methodological transparency. The protocol specifies nine working steps. For each step, suitable methods are proposed and the intended level and format of stakeholder engagement are discussed. A key methodological challenge is to link global SSPs with regional perspectives provided by the stakeholders, while maintaining vertical consistency and stakeholder buy-in. We conclude that the protocol facilitates systematic development and evaluation of storylines, which can be transferred to other regions, sectors and scales and supports inter-comparisons of IAAS.

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers' views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change.

Lyme Disease Risks in Europe under Multiple Uncertain Drivers of Change

BACKGROUND

Debates over whether climate change could lead to the amplification of Lyme disease (LD) risk in the future have received much attention. Although recent large-scale disease mapping studies project an overall increase in Lyme disease risk as the climate warms, such conclusions are based on climate-driven models in which other drivers of change, such as land-use/cover and host population distribution, are less considered.

OBJECTIVES

The main objectives were to project the likely future ecological risk patterns of LD in Europe under different assumptions about future socioeconomic and climate conditions and to explore similarity and uncertainty in the projected risks.

METHODS

An integrative, spatially explicit modeling study of the ecological risk patterns of LD in Europe was conducted by applying recent advances in process-based modeling of tick-borne diseases, species distribution mapping, and scenarios of land-use/cover change. We drove the model with stakeholder-driven, integrated scenarios of plausible future socioeconomic and climate change [the Shared Socioeconomic Pathway (SSPs) combined with the Representative Concentration Pathways (RCPs)].

RESULTS

The model projections suggest that future temperature increases may not always amplify LD risk: Low emissions scenarios (RCP2.6) combined with a sustainability socioeconomic scenario (SSP1) resulted in reduced LD risk. The greatest increase in risk was projected under intermediate (RCP4.5) rather than high-end (RCP8.5) climate change scenarios. Climate and land-use change were projected to have different roles in shaping the future regional dynamics of risk, with climate warming being likely to cause risk expansion in northern Europe and conversion of forest to agriculture being likely to limit risk in southern Europe.

CONCLUSIONS

Projected regional differences in LD risk resulted from mixed effects of temperature, land use, and host distributions, suggesting region-specific and cross-sectoral foci for LD risk management policy. The integrated model provides an improved explanatory tool for the system mechanisms of LD pathogen transmission and how pathogen transmission could respond to combined socioeconomic and climate changes. https://doi.org/10.1289/EHP4615.

Spatio-temporal analysis of land use/land cover change and its effects on soil erosion (Case study in the Oplenac wine-producing area, Serbia)

In this paper, various spatial modelling techniques were applied to analyse changes in soil cover and their impact on soil erosion in the Oplenac wine-producing area in Serbia in the past (1985 and 2013) and in the future (with predictions for 2041). The Integrated Valuation of Ecosystem Services and Trade-offs Sediment Delivery Ratio (InVEST SDR) model and the Modules for Land Use Change Evaluation (MOLUSCE) model, integrated with methods of remote sensing, were successfully applied and were shown to be valid tools for predicting the impact of Land Use Land Cover (LULC) changes when estimating soil loss. The results revealed that the greatest impact of land use changes between 1985 and 2013 was on a reduction in areas under vineyards and an extension of meadow and pasturelands as an individual and social response to economic conditions during the research period. The forecast for 2041 reflected the trends observed in the previous period, with the greatest changes witnessing an increase in urban areas and a decrease in areas of arable land. It was also found that the effect of LULC changes on spatio-temporal patterns in the Oplenac wine-producing area did not have a major impact on soil loss, meaning this area, with its good agro-climatic characteristics, is suitable for the intensification of agricultural production.

Variations in climatic suitability and planting regionalization for potato in northern China under climate change

Investigating the variations in crop climatic suitability and planting regionalization can provide scientific evidence for ensuring food security under climate change. In this study, variations in climatic suitability and planting regionalization for the potato in northern China were investigated based on daily data from 1965 to 2014 collected at 321 agro-meteorological observation stations located throughout the region. Northern China was divided into three areas, including Northwest China, North China and Northeast China. The agricultural climatic suitability theory and the fuzzy mathematics method were applied. The potato growth seasons were divided into threestages:from sowing to emergence, from emergence to flowering and from flowering to maturity. The comprehensive climatic suitabilityindex (C), which varied from 0 to 1, was established to evaluate the effects of climate change on potato planting. The results showed that, from 1965 to 2014, the C value in the study area increased 0.002 every ten years over the past 50 years with an average of 0.706, benefitting potato growth in the vast area of northern China. Nonetheless, precipitation was found to be the main climatic factor restricting potato growth in northern China. For spatial distribution, the C value showed a gradually declining trend from east to west, decreasing westward and southward over the past 50 years. For the growth season, the C value varied during different potato growth stages over the past 50 years. The C value increased during the sowing-emergence stage and decreased during the emergence-flowering stage and the flowering-maturity stage. The decreased C during the later growth stages would directly affect the quality and yield of the potato, mainly because the flowering-maturity stage was associated with potato tuber enlargement and starch accumulation. Variations in potato planting regionalization in northern China over the past 50 years were evident. Climate change was more beneficial to potato cultivation in northeast China where the highly suitable areas had clearly expanded. However, potato cultivation was most negatively affected in northwest China where the middle suitable areas had receded. Our findings have important implications for improving climate change impact studies and agricultural production to cope with ongoing climate change.

Minimal climate change impacts on natural organic matter forecasted for a potable water supply in Ireland

Natural organic matter poses an increasing challenge to water managers because of its potential adverse impacts on water treatment and distribution, and subsequently human health. Projections were made of impacts of climate change on dissolved organic carbon (DOC) in the primarily agricultural Boyne catchment which is used as a potable water supply in Ireland. The results indicated that excluding a potential rise in extreme precipitation, future projected loads are not dissimilar to those observed under current conditions. This is because projected increases in DOC concentrations are offset by corresponding decreases in precipitation and hence river flow. However, the results presented assume no changes in land use and highlight the predicted increase in DOC loads from abstracted waters at water treatment plants.

Modelling climate change impacts on nutrients and primary production in coastal waters

There is high confidence that the anthropogenic increase of atmospheric greenhouse gases (GHGs) is causing modifications in the Earth's climate. Coastal waterbodies such as estuaries, bays and lagoons are among those most affected by the ongoing changes in climate. Being located at the land-sea interface, such waterbodies are subjected to the combined changes in the physical-chemical processes of atmosphere, upstream land and coastal waters. Particularly, climate change is expected to alter phytoplankton communities by changing their environmental drivers (especially climate-related), thus exacerbating the symptoms of eutrophication events, such as hypoxia, harmful algal blooms (HAB) and loss of habitat. A better understanding of the links between climate-related drivers and phytoplankton is therefore necessary for projecting climate change impacts on aquatic ecosystems. Here we present the case study of the Zero river basin in Italy, one of the main contributors of freshwater and nutrient to the salt-marsh Palude di Cona, a coastal waterbody belonging to the lagoon of Venice. To project the impacts of climate change on freshwater inputs, nutrient loadings and their effects on the phytoplankton community of the receiving waterbody, we formulated and applied an integrated modelling approach made of: climate simulations derived by coupling a General Circulation Model (GCM) and a Regional Climate Model (RCM) under alternative emission scenarios, the hydrological model Soil and Water Assessment Tool (SWAT) and the ecological model AQUATOX. Climate projections point out an increase of precipitations in the winter period and a decrease in the summer months, while temperature shows a significant increase over the whole year. Water discharge and nutrient loads simulated by SWAT show a tendency to increase (decrease) in the winter (summer) period. AQUATOX projects changes in the concentration of nutrients in the salt-marsh Palude di Cona, and variations in the biomass and species of the phytoplankton community.

To defend or to grow: lessons from Arabidopsis C24

The emergence of Arabidopsis as a model species and the availability of genetic and genomic resources have resulted in the identification and detailed characterization of abiotic stress signalling pathways. However, this has led only to limited success in engineering abiotic stress tolerance in crops. This is because there needs to be a deeper understanding of how to combine resistances to a range of stresses with growth and productivity. The natural variation and genomic resources of Arabidopsis thaliana (Arabidopsis) are a great asset to understand the mechanisms of multiple stress tolerances. One natural variant in Arabidopsis is the accession C24, and here we provide an overview of the increasing research interest in this accession. C24 is highlighted as a source of tolerance for multiple abiotic and biotic stresses, and a key accession to understand the basis of basal immunity to infection, high water use efficiency, and water productivity. Multiple biochemical, physiological, and phenological mechanisms have been attributed to these traits in C24, and none of them constrains productivity. Based on the uniqueness of C24, we postulate that the use of variation derived from natural selection in undomesticated species provides opportunities to better understand how complex environmental stress tolerances and resource use efficiency are co-ordinated.

Modelling regional cropping patterns under scenarios of climate and socio-economic change in Hungary

Impacts of socio-economic, political and climatic change on agricultural land systems are inherently uncertain. The role of regional and local-level actors is critical in developing effective policy responses that accommodate such uncertainty in a flexible and informed way across governance levels. This study identified potential regional challenges in arable land use systems, which may arise from climate and socio-economic change for two counties in western Hungary: Veszprém and Tolna. An empirically-grounded, agent-based model was developed from an extensive farmer household survey about local land use practices. The model was used to project future patterns of arable land use under four localised, stakeholder-driven scenarios of plausible future socio-economic and climate change. The results show strong differences in farmers' behaviour and current agricultural land use patterns between the two regions, highlighting the need to implement focused policy at the regional level. For instance, policy that encourages local food security may need to support improvements in the capacity of farmers to adapt to physical constraints in Veszprém and farmer access to social capital and environmental awareness in Tolna. It is further suggested that the two regions will experience different challenges to adaptation under possible future conditions (up to 2100). For example, Veszprém was projected to have increased fallow land under a scenario with high inequality, ineffective institutions and higher-end climate change, implying risks of land abandonment. By contrast, Tolna was projected to have a considerable decline in major cereals under a scenario assuming a de-globalising future with moderate climate change, inferring challenges to local food self-sufficiency. The study provides insight into how socio-economic and physical factors influence the selection of crop rotation plans by farmers in western Hungary and how farmer behaviour may affect future risks to agricultural land systems under environmental change.

Past crops yield dynamics reconstruction from tree-ring chronologies in the forest-steppe zone based on low- and high-frequency components

Interrelations of the yield variability of the main crops (wheat, barley, and oats) with hydrothermal regime and growth of conifer trees (Pinus sylvestris and Larix sibirica) in forest-steppes were investigated in Khakassia, South Siberia. An attempt has been made to understand the role and mechanisms of climatic impact on plants productivity. It was found that amongst variables describing moisture supply, wetness index had maximum impact. Strength of climatic response and correlations with tree growth are different for rain-fed and irrigated crops yield. Separated high-frequency variability components of yield and tree-ring width have more pronounced relationships between each other and with climatic variables than their chronologies per se. Corresponding low-frequency variability components are strongly correlated with maxima observed after 1- to 5-year time shift of tree-ring width. Results of analysis allowed us to develop original approach of crops yield dynamics reconstruction on the base of high-frequency variability component of the growth of pine and low-frequency one of larch.