Combined Land Use Research Articles

The Assessment of Land Suitability for Urban Expansion and Renewal for Coastal Urban Agglomerations: A Pilot Study of the Guangdong-Hong Kong-Macao Greater Bay Area

Effectively and rationally allocating land resources, while coordinating urban expansion with internal renewal strategies, is crucial for achieving high-quality regional development in coastal urban agglomerations. Land-use suitability assessment (LSA) is a key method for coastal land-use planning, but it is primarily used to delineate ecological redlines or areas for urban expansion, often overlooking the spatial analysis needed for urban renewal. This is particularly critical in coastal urban agglomerations facing land scarcity and ecological fragility. Here, we combined land use and the Analytical Hierarchical Process (to consider stakeholder priorities) in a Minimum cumulative resistance model (MCRM) to determine suitable coastal urban growth and renewal based on a suite of 12 indicators relevant to development intensity and stock space. Application to the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) indicates a dominance of the Ecological Buffer Zone (70.5%), and the available stock space in the GBA comprises only 9.2% of the total area. Our modeling framework tailored different development strategies for different cities: Huizhou and Zhaoqing had space for urban expansion to varying degrees, while other cities were found to be suitable for urban renewal due to low stock space and high development intensity. Our modeling approach, incorporating stakeholder input and objective evaluation of geographic land-use information, can assist planners in improving ecological security while promoting high-quality developments in coastal areas.

Spatially Explicit Impact of Land Use Changes in the Bay Area on Anthropogenic Phosphorus Emissions and Freshwater Eutrophication Potential.

Land use changes significantly impact anthropogenic phosphorus (P) emissions, their migration to a water environment, and the formation of freshwater eutrophication potential (FEP), yet the spatiotemporally heterogeneous relationships at the regional scale have been less explored. This study combines land use classification, P-flow modeling, spatial analysis, and cause-effect chain modeling to assess P emissions and P-induced FEP at a fine spatial resolution in Guangdong-Hong Kong-Macao Greater Bay Area and reveals their dynamic responses to land use changes. We find that land conversion from cultivated land to impervious land corresponded to an increase in P emissions of 4.1, 1.8, and 0.5 Gg during 2000-2005, 2005-2010, and 2010-2015 periods, respectively, revealing its dominant but weakening role in the intensification of P emissions especially in less-developed cities. Expansion of aquacultural land gradually became the primary contributor to the increase in both the amount and intensity of P emissions. Land conversions from cultivated land to impervious land and from natural water bodies to aquacultural land led to 35.9% and 25.3% of the increase in FEP, respectively. Our study identifies hotspots for mitigating the environmental pressure from P emissions and provides tailored land management strategies at specific regional development stages and within sensitive areas.

Research on Improving the Accuracy of SIF Data in Estimating Gross Primary Productivity in Arid Regions

Coupling solar-induced chlorophyll fluorescence (SIF) with gross primary productivity (GPP) for ecological function integration research presents numerous uncertainties, especially in ecologically fragile and climate-sensitive arid regions. Therefore, evaluating the suitability of SIF data for estimating GPP and the feasibility of improving its accuracy in the northern region of Xinjiang is of profound significance for revealing the spatial distribution patterns of GPP and the strong coupling relationship between GPP and SIF in arid regions, achieving the goal of “carbon neutrality” in arid regions. This study is based on multisource SIF satellite data and GPP observation data from sites in three typical ecosystems (cultivated and farmlands, pasture grasslands, and desert vegetation). Two precision improvement methods (canopy and linear) are used to couple multiple indicators to determine the suitability of multisource SIF data for GPP estimation and the operability of accuracy improvement methods in arid regions reveal the spatial characteristics of SIF (GPP). The results indicate the following. (1) The interannual variation of GPP shows an inverted “U” shape, with peaks values in June and July. The cultivated and farmland areas have the highest peak value among the sites (0.35 gC/m2/month). (2) The overall suitability ranking of multisource SIF satellite products for GPP estimation in arid regions is RTSIF > CSIF > SIF_OCO2_005 > GOSIF. RTSIF shows better suitability in the pasture grassland and cultivated and farmland areas (R2 values of 0.85 and 0.84, respectively). (3) The canopy method is suitable for areas with a high leaf area proportion (R2 improvement range: 0.05–0.06), while the linear method is applicable across different surface types (R2 improvement range: 0.01–0.13). However, the improvement effect of the linear method is relatively weaker in areas with high vegetation cover. (4) Combining land use data, the overall improvement of SIF (GPP) is approximately 0.11%, and the peak values of its are mainly distributed in the northern and southern slopes of the Tianshan Mountains, while the low values are primarily found in the Gurbantunggut Desert. The annual mean value of SIF (GPP) is about 0.13 mW/m2/nm/sr. This paper elucidates the applicability of SIF for GPP estimation and the feasibility of improving its accuracy, laying the theoretical foundation for the spatiotemporal coupling study of GPP and SIF in an arid region, and providing practical evidence for achieving carbon neutrality goals.

Short-Term Nitrogen Dioxide Exposure and Emergency Hospital Admissions for Asthma in Children: A Case-Crossover Analysis in England.

There is an increasing body of evidence associating short-term ambient nitrogen dioxide (NO2) exposure with asthma-related hospital admissions in children. However, most studies have relied on temporally resolved exposure information, potentially ignoring the spatial variability of NO2. We aimed to investigate how daily NO2 estimates from a highly resolved spatio-temporal model are associated with the risk of emergency hospital admission for asthma in children in England. We conducted a time-stratified case-crossover study including 111,766 emergency hospital admissions for asthma in children (aged 0-14 years) between 1st January 2011 and 31st December 2015 in England. Daily NO2 levels were predicted at the patients' place of residence using spatio-temporal models by combining land use data and chemical transport model estimates. Conditional logistic regression models were used to obtain the odds ratios (OR) and confidence intervals (CI) after adjusting for temperature, relative humidity, bank holidays, and influenza rates. The effect modifications by age, sex, season, area-level income deprivation, and region were explored in stratified analyses. For each 10 µg/m³ increase in NO2 exposure, we observed an 8% increase in asthma-related emergency admissions using a five-day moving NO2 average (mean lag 0-4) (OR 1.08, 95% CI 1.06-1.10). In the stratified analysis, we found larger effect sizes for male (OR 1.10, 95% CI 1.07-1.12) and during the cold season (OR 1.10, 95% CI 1.08-1.12). The effect estimates varied slightly by age group, area-level income deprivation, and region. Short-term exposure to NO2 was significantly associated with an increased risk of asthma emergency admissions among children in England. Future guidance and policies need to consider reflecting certain proven modifications, such as using season-specific countermeasures for air pollution control, to protect the at-risk population.

Potential Interactions between Climate Change and Land Use for Forest Issues in the Eastern United States

Applying an interaction framework, we examined whether climate change and combined land use and disturbance changes were synergistic, antagonistic, or neutral for forest issues of wildfires, tree growth, tree species distributions, species invasions and outbreaks, and deer herbivory, focused on the eastern United States generally since the 1800s and the development of instrumental records (1895). Climate largely has not warmed during 1981–2020 compared to 1895–1980, but precipitation has increased. Increased precipitation and land use (encompassing fire exclusion and forestation, with coarse fuel accumulation due to increased tree densities) have interacted synergistically to dampen wildfire frequency in the humid eastern U.S. For overall tree growth, increased precipitation, carbon fertilization, and land use (i.e., young, fast-growing dense stands) likely have been positive, generating a synergistic interaction. Human activities created conditions for expanding native tree species distributions, non-native species invasions, and damaging native species outbreaks. No strong evidence appears to exist for recent climate change or land use influences on deer populations and associated herbivory levels. In the future, a warmer and effectively drier climate may reverse synergistic and neutral interactions with land use, although effects of climate interactions with land use will vary by species. Management can help correct non-climate stressors due to land use and support resilient structures and species against climate change.

What would it look like? Visualizing a future US Corn Belt landscape with more table food production

Abstract Most farmland in the US Corn Belt is used to grow row crops at large scales (e.g., corn, soybean) that are highly processed before entering the human food stream rather than specialty crops grown in smaller areas and meant for direct human consumption (table food). Bolstering local table food production close to urban populations in this region through peri-urban agriculture (PUA) could enhance sustainability and resilience. Understanding factors influencing PUA producers' preferences and willingness to produce table food would enable supportive planning and policy efforts. This study combined land use visualization and survey data to examine the potential for increased local table food production for the US Corn Belt. We developed a spatial visualization of current agricultural land use and a future scenario with increased table food production designed to meet 50% of dietary requirements for a metropolitan population in 2050. A survey was administered to row crop (1360) and specialty crop (55) producers near Des Moines, Iowa, US to understand current and intended agricultural land use and factors influencing production. Responses from 316 row crop and 25 specialty crop producers were eligible for this analysis. A future scenario with increased table food production would require less than 3% of available agricultural land and some additional producers (approximately 130, primarily for grain production). Survey responses indicated PUA producers planned small increases in table food production in the next three to five years. Producer plans, including land rental for table food production, could provide approximately 25% of residents' fruit, vegetables, and grains, an increase from the baseline of 2%. Row crop producers ranked food safety regulations, and specialty producers ranked labor concerns as strong influences on their decision-making. Both groups indicated that crop insurance and processing facilities were also important. Increasing table food production by clustering mid-scale operations to increase economies of scale and strengthening supply chains and production infrastructure could provide new profitable opportunities for farmers and more resilient food systems for growing urban regions in the US Corn Belt. Continuing to address producer factors and landscape-scale environmental impacts will be critical in considering food system sustainability challenges holistically.

Associations between Land-Use Patterns and Cardiovascular Disease Mortality in the Beijing—Tianjin–Hebei Megacity Region

Megacity regions where human activities are intensive are key areas for CVD prevention and control in China. Optimizing land-use patterns has been widely recognized as an important public health intervention. Ecological space, agricultural space, and construction space are three basic management objects in China’s new land-use management system. Given that most existing studies focused on a single type of land use, this study treats them as a whole and not only explores the impact of each type, but also systematically investigates the effects of the interactions between any two types of land use and the whole land-use pattern. Specifically, this study first constructs a hierarchical index system, then uses spatial error models (SEM) to explore the global associations between each index and age-standardized CVD mortality rates (ASMRs) and uses the multiple geographical weighted regression model (MGWR) to explore the spatial heterogeneity of factor effects. The possible association between land-use patterns and CVD mortality is then explored, and recommendations for policy formulation are provided. The analysis results show that the overall pattern of moderately decentralized and organically combined land use can control CVD mortality to a certain extent, but the specific influence mechanisms show significant differences according to different land-use types, relationships, and location conditions. First, in terms of single-type land-use distribution, the concentration of ecological space has positive health benefits, while a too high concentration of agricultural space has negative effects. Second, the combination of different types of land use has a significant association with CVD, in which the mixed layout of ecological and agricultural space helps to suppress CVD, while ecological and construction space need to be appropriately regularized and should not be too interspersed. Third, the same index may have different effects in different regions, suggesting that policy makers need to tailor their policies to local conditions.

Regionalization and optimization strategy of ecological management in Xinjiang, China based on supply-demand relationship and spatial flow of ecosystem services.

As an important basis for the optimization of territorial space, ecological management zoning is of great significance for maintaining regional ecological security and promoting the construction of ecological civilization. With 10 ecosystem services, such as wind break and sand fixation, water conservation, and forest and grass supply, we built a supply index system for Xinjiang. Modelling and ecological economics methods were used to quantify ecosystem service supply. Ecosystem service demand of Xinjiang in 2020 was quantitatively assessed by combining land use intensity, population, and economic status. Based on the ecosystem service supply-demand ratio model and quadrant matching method, we explored the matching relationship and spatial differentiation of ecosystem ser-vice supply and demands on the 1 km grid scale. The breaking point formula and field intensity formula were used to evaluate the flow range and intensity of ecosystem services, and then ecological management zones were divided and corresponding control measures were proposed. The results showed obvious spatial differences in the supply and demand of ecosystem services in Xinjiang in 2020. The high-supply areas were mainly distributed in river valleys and along river systems, while the demand was concentrated in oasis-central cities. The overall supply of ecosystem services was less than the demand. The spatial distribution was dominated by low supply-low demand areas and high supply-high demand areas. There were seven output zones of ecosystem services in Xinjiang, namely Fuyun County, Fuhai County, Yizhou District, Shanshan County, Alashankou City, Keping County and Qira County. The rests were input zones. According to the comprehensive analysis, Xinjiang could be divided into five ecological management areas, i.e., mountain ecological barrier area, oasis ecological restoration area, desert ecological improvement area, desert-oasis ecological protection area, and patch ecological transport area.

The problem of the modernisation of land and building register in Poland as exemplified by the village of Rejowiec

The right of ownership is the broadest and one of the most basic property rights, which allows the owner to use and dispose of possessions without the participation of third parties. Therefore, the process of modernising the land and building register (MLBR) is extremely important considering, for example, that the data contained in this register is the basis for the subsequent calculation of public-legal obligations associated with the owned property, such as taxes. According to the current legislation, the data collected in the land and building register (cadastre) on the type of land use in combination with the soil classification of agricultural and forest land, the use of the property, its purpose and other information, are the basis for determining the agricultural, forest and real estate taxes by the competent authority. In Poland, in most cases, we have to deal with a situation in which the data appearing in the register differs from the actual state. Municipal budgets suffer losses because of this, and owners of properties of similar area and value sometimes pay completely different taxes. In this paper, the authors show a practical example of MLBR and the problems existed with it.

Recognition of the Interaction Mechanisms between Water and Land Resources Based on an Improved Distributed Hydrological Model

Conflicts between humans and land use in the process of using water and conflicts between humans and water resources in the process of using land have led to an imbalance between natural ecosystems and socio-economic systems. It is difficult to understand the impact of the processes of water production and consumption on land patches and their ecological effects. A grid-type, basin-distributed hydrological model was established in this study, which was based on land-use units and coupled with groundwater modules to simulate the water production and consumption processes in different units. By combining land use and net primary productivity, the runoff coefficient and the water use efficiency (NPP/ET) of different land units were used as indicators to characterize the interaction between water and land resources. The results showed that the average runoff coefficients of cultivated land, forest land and grassland were 0.7, 0.5 and 0.9, respectively. Moreover, the average runoff coefficients of hills, plains and basins were 0.7, 0.7 and 0.8, respectively. The NPP produced by the average unit, evapotranspiration, in cultivated land, forest land and grassland was 7 (gC/(m2•a))/mm, 0.7 (gC/(m2•a))/mm and 0.2 (gC/(m2•a))/mm, respectively. These results provide quantitative scientific and technological support in favor of the comprehensive ecological management of river basins.

Revolutionizing TOD Planning in a Developing Country: An Objective-Weighted Framework for Measuring Nodal TOD Index

Transit-oriented development (TOD) is a planning strategy that combines land use and transportation planning to promote economic, environmental, and social sustainability. While developed cities have embraced TOD, developing cities need to adopt it faster. This has resulted in a need for robust TOD measurement frameworks for developing countries. Furthermore, existing frameworks often use subjective weightage for different TOD indicators, which can lead to human biases. To address these issues, the authors aimed to develop a more robust and objective framework for measuring TOD in developing cities, particularly Dhaka, Bangladesh. The authors used density, diversity, destination accessibility, and design criteria to select eight indicators for measuring TOD. However, a buffer radius of 800 meters was taken for each of the 17 stations to calculate TOD. An objective-weighted spatial multi-criteria analysis (OSMCA) was used to evaluate the framework. The model’s robustness was assessed by analyzing the sensitivity of eight TOD scenarios and identifying hotspot clusters using statistical methods. Additionally, the authors ranked the stations based on the highest TOD score and compared TOD with developed and developing cities to gain planning insights. They proposed three different TOD planning methodologies for nodes that emphasize the importance of design, destination access, and density for (re)development, zoning, and affordable housing policies in Dhaka’s regions. Finally, the study discussed limitations and future research priorities.

Applying wind patterns and land use to estimate the concentrations of airborne pollen of herbaceous taxa in a statistical framework

Airborne pollen concentrations are influenced by wind direction, wind speed, temperature and rainfall among other meteorological variables, but they are conditioned by local land use. Combining land use and wind frequencies within a single variable would allow the estimation of the contribution of the emission sources to the airborne pollen detected. The aim of this study was to develop this new variable and to compare its relevance in estimating airborne pollen concentrations of anemophilous (i.e. wind pollinated) herbaceous taxa versus other meteorological predictors.The airborne pollen concentrations of some herbaceous pollen types were studied in Malaga, Spain (1992–2020). The land-use surfaces were combined with the daily wind direction frequencies to develop an index. This index was relevant for estimating daily airborne pollen concentrations in random forest frameworks since high pollen concentrations were detected on days with high index values. However, the relationship between the index and the pollen concentrations was not linear due to the influence of other variables.Overall, this index constitutes an easy-to-use approach to integrate both land use and wind frequencies in pollen models, and it can be applied to other sampling locations and pollen types.

Contribution of ‘human induced fires’ to forest and savanna land conversion dynamics in the Luki Biosphere Reserve landscape, western Democratic Republic of Congo

ABSTRACT Human-induced fire is one of the most important determinants of forest cover and change in tropical and subtropical regions of the world. Yet its impact on forest cover and forest cover change remains unclear, as fires in Africa generally do not spread over very large area. This is particularly the case in the Democratic Republic of Congo (DRC), a region of the world that is still poorly investigated. Here, we propose to study the effect of human-induced fire on land use and land cover change in a protected area of the DRC, i.e. the Luki Biosphere Reserve (LBR). We investigate tree cover changes in and around the reserve between 2002 and 2019 using Landsat 7 ETM+, Landsat 8 OLI/TIRS and MODIS MCD12Q1 images and quantify human induced fires using MODIS MCD64A1 images. The study combines land use and land cover (LULC) change detection analysis of four images, two acquired in 2002 and two acquired in 2019, with multi-temporal assessment of annual burnt area acquired between 2002 and 2019 from MODIS MCD64A1 to assess the role of fire in LULC changes and the sensitivity of different LULC types to fire. The results show a dynamic conversion of primary forest to secondary forest over about 16% of the area, the evolution of savanna to secondary forest over 9.6% (Landsat image) and the replacement of secondary forest by savanna over 8.1% (MODIS image) of the total area of Luki Reserve. Of the total area undergoing land use change, 34.1% (Landsat image) and 35.7% (MODIS image) were caused by fire, which however did not cause a significant LULC change. For the LULC types that experienced fire events, the least stable type was primary forest, which had the lowest stability rate (34.2% and 23% for Landsat and MODIS image analysis, respectively) compared to others. This result illustrates the importance of fire as a driver of primary forest loss and degradation in the region. Despite the high exposure of savannas to fire events, they were not significantly destabilized by fire (stability rates of 86.3 and 97% for Landsat and MODIS analysis, respectively). Future analyses should focus on discriminating between different fire types to better understand the complex relationship between fire and ecosystem conditions.

Multi-spatial scale effects of multidimensional landscape pattern on stream water nitrogen pollution in a subtropical agricultural watershed

Multidimensional (coupled land use, soil properties, and topography) landscape effects on stream water nitrogen (N) are complex and scale-dependent. However, studies that identify critical buffer zones that explain large variations in riverine N, and estimate specific thresholds of multidimensional landscape patterns at the class level, result in a sudden changes in riverine N pollution, are still limited. Here, a new multidimensional landscape metric that combined land use, soil properties, and topography effects was applied to various riparian buffer zones and sub-watershed scales, and their relationships to riverine N levels were investigated. We used stream water ammonium−N, nitrate−N, and total−N concentrations datasets, from 2010 to 2017, in the nine subtropical sub-watersheds in China. The results of model selection and model averaging in ordinary least squares regressions, indicated that the riparian buffer zone with widths of 400 m, had more pronounced influence on water NH4–N and TN levels than at other scales. Within the 400 m buffer zone, the key landscape metrics for NH4–N, NO3–N and TN concentrations in stream water were different, and explained up to 43.35%–76.55% (adjusted R2) of the total variation in river N levels. When ENN_MNClass17 below 39–56 m, PDClass8 above 4.63–6.55 n/km2, PLANDClass27 above 23–29%, and CONTIG_MNClass42 below 0.35–0.37% within the 400 m buffer zone, riverine NH4–N and TN would be abruptly increased. This study provided practical ideas for regulation regarding landscape management linked to watershed structure, and identified reference thresholds for multidimensional landscape metrics, which should help reduce riverine N pollution in subtropical China.

Modelling Hourly Particulate Matter (PM10) Concentrations at High Spatial Resolution in Germany Using Land Use Regression and Open Data

Air pollution is a major health risk factor worldwide. Regular short- and long-time exposures to ambient particulate matter (PM) promote various diseases and can lead to premature death. Therefore, in Germany, air quality is assessed continuously at approximately 400 measurement sites. However, knowledge about this intermediate distribution is either unknown or lacks a high spatial–temporal resolution to accurately determine exposure since commonly used chemical transport models are resource intensive. In this study, we present a method that can provide information about the ambient PM concentration for all of Germany at high spatial (100 m × 100 m) and hourly resolutions based on freely available data. To do so we adopted and optimised a method that combined land use regression modelling with a geostatistical interpolation technique using ordinary kriging. The land use regression model was set up based on CORINE (Coordination of Information on the Environment) land cover data and the Germany National Emission Inventory. To test the model’s performance under different conditions, four distinct data sets were used. (1) From a total of 8760 (365 × 24) available h, 1500 were randomly selected. From those, the hourly mean concentrations at all stations (ca. 400) were used to run the model (n = 566,326). The leave-one-out cross-validation resulted in a mean absolute error (MAE) of 7.68μgm−3 and a root mean square error (RMSE) of 11.20μgm−3. (2) For a more detailed analysis of how the model performs when an above-average number of high values are modelled, we selected all hourly means from February 2011 (n = 256,606). In February, measured concentrations were much higher than in any other month, leading to a slightly higher MAE of 9.77μgm−3 and RMSE of 14.36μgm−3, respectively. (3) To enable better comparability with other studies, the annual mean concentration (n = 413) was modelled with a MAE of 4.82μgm−3 and a RMSE of 6.08μgm−3. (4) To verify the model’s capability of predicting the exceedance of the daily mean limit value, daily means were modelled for all days in February (n = 10,845). The exceedances of the daily mean limit value of 50 μgm−3 were predicted correctly in 88.67% of all cases. We show that modelling ambient PM concentrations can be performed at a high spatial–temporal resolution for large areas based on open data, land use regression modelling, and kriging, with overall convincing results. This approach offers new possibilities in the fields of exposure assessment, city planning, and governance since it allows more accurate views of ambient PM concentrations at the spatial–temporal resolution required for such assessments.

Individual and combined effects of land use and weeds on Cry1Ab/c protein expression and yield of transgenic cry1Ab/c rice

ABSTRACT Considering the anticipated commercial exploitation of insect-resistant transgenic rice and that the planting area of cultivated rice overlaps with wild rice, simulating an escape of transgenic rice from farmlands and exploring its fitness after entering semi-natural or natural ecosystems through uncontrolled seed dispersal or gene flow are critical to understand the resulting potential long-term environmental risks. The expression of foreign Cry1Ab/c protein and vegetative and reproductive fitness of insect-resistant transgenic rice Huahui1 (HH1) and its parental-line Minghui63 (MH63) were studied under four treatments combining land use and weed competition: farmland and uncultivated land under weed control (F-NW and U-NW, respectively), and farmland and uncultivated land without weed control (F-W and U-W, respectively). The expression of Cry1Ab/c was significantly lower in U-NW, F-W, and U-W than that in the control treatment, F-NW. Except for plant height, key vegetative (tiller number and biomass) and reproductive (grain number and grain weight per plant) growth indices of transgenic HH1 were significantly lower than those of the parental-line MH63 in F-NW and U-NW, indicating a significant fitness cost. In F-W and U-W, vegetative growth indices (plant height, tiller number, and biomass) were similar in HH1 and MH63; however, key reproductive indices including seed-set rate were significantly higher in HH1 than in MH63, indicating significant fitness benefits. Although these results support large-scale cultivation of insect-resistant transgenic rice in China, the ecological risk involved is high in farmland or uncultivated land without weed control (F-W and U-W).

Towards a global behavioural model of anthropogenic fire: The spatiotemporal distribution of land-fire systems

Landscape fire regimes are created through socio-ecological processes, yet in current global models the representation of anthropogenic impacts on fire regimes is restricted to simplistic functions derived from coarse measures such as GDP and population density. As a result, fire-enabled dynamic global vegetation models (DGVMs) have limited ability to reproduce observed patterns of fire, and limited prognostic value. At the heart of this challenge is a failure to represent human agency and decision-making related to fire. This paper outlines progress towards a global behavioural model that captures the categorical differences in human fire use and management that arise from diverse land use objectives under varying socio-ecological contexts. We present a modelled global spatiotemporal distribution of what we term ‘land-fire systems’ (LFSs), a classification that combines land use systems and anthropogenic fire regimes. Our model simulates competition between LFSs with a novel bootstrapped classification tree approach that performs favourably against reference multinomial regressions. We evaluate model outputs with the human appropriation of net primary production (HANPP) framework and find good overall agreement. We discuss limitations to our methods, as well as remaining challenges to the integration of behavioural modelling in DGVMs and associated model-intercomparison protocols.

ApisRAM Formal Model Description

The ApisRAM model is an agent-based colony model for honey bees in which each bee is modelled as an individual agent. The behaviour of the colony emerges from the decisions and actions taken by individuals in the colony and the interactions between agents. The bees interact with, and react to, both other bees and the resources in the colony, the hive physical and chemical properties, and the environment outside the colony. A key feature of ApisRAM is the approach to representing bee health. This is a ‘vitality’ model which is used to integrate multiple stressors (unfavourable temperature, food shortage, infectious agents and pesticides) for each individual bee. The vitality of each model bee interacts with all the four stressors. The environment in which the colony is modelled is implemented as a dynamic landscape simulation within ALMaSS (the Animal Landscape and Man Simulation System). The ALMaSS landscape model is a spatially and temporally dynamic model which combines land use, detailed farm practices, weather, crop growth, semi-natural habitats, and flower resource models. With the combination of the colony and landscape models, the ApisRAM model provides a framework for in silico experiments, e.g., pesticides applications, designed to explore the effects of combined stressors on honey bee colonies under a variety of environmental and human (e.g. beekeeping management practices) factors.

Hierarchical health risk assessment and influence factors of an ecological post-restoration oil shale mining area based on metal bioavailability

The environmental problems caused by mining are continuous and multifaceted, in order to help manage and plan restored mining areas, the bioavailability of metals is an effective tool for measuring the potential risks to human health. This study analyzes the geochemical fractions of eight metals (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn) to compare their bioavailability and establishes a Hierarchical health risk (HHR) model to assess the human health risks of the mine area after restoration. The results indicated that children have the highest non-carcinogenic risks exposed through ingestion (HI-ingestion) due to their special behaviors; HI-dermal may be enriched in the body; and HI-inhalation is lowest, as it is related to soil particle size. Affected by local economic development, environmental climate, soil type, and mining, the carcinogenic risk of exposure through the skin (CR-dermal) for adults significantly exceeds the acceptable safety level (ASL). The spatial distribution shows that the harm of mining to human health is a continuous process. There was still a significant CR for adults after remediation, and the HI of tailings exposure was more serious. The Classification and Regression Tree (CART) model of metal bioavailability was developed by integrating the extrinsic and intrinsic factors of metals to explore the effects of different factors on metal bioavailability and predict. The results showed that the bioavailability of metals was a dynamic process that combined land use, the distance to traffic roads, physicochemical properties of soil, and geochemical fractions of metal, and that it affects human health both directly and indirectly. Due to the fragility and sensitivity of the ecosystem after the mining area is restored, it may face greater environmental health risks.

Revealing the strength of gross potential for cycling as a planning support for starter cycling cities

While the bicycle is at the forefront of the development of sustainable mobility strategies, urban areas often have a different pace of implementation. Those at the earlier stages, identified as starter cycling cities, face numerous obstacles in this process, due to a combination of inexistent know-how, ineffective guidance, and a lack of political and societal commitment. A planning support system especially developed for this context, while simultaneously addressing basic user-friendliness and soundness aspects, can play a key role in the decision-making process, serving as a catalyst for overcoming these barriers.This paper explores the potential of a new PSS, designated Gross Potential for Cycling (GPC), which aims to map the territorial hotspots for potential bicycle use, combining land use and socio-demographic assessment layers. Its suitability to provide a meaningful contribution for practice was tested through a series of experiential workshops involving planning practitioners from a wide range of Portuguese contexts (all in starter cycling areas). Participants were asked to use the insights from the tool in developing cycling strategies and to assess its user friendliness, the soundness of its results and its inherent utility for the planning process. This assessment was complemented by workshops with researchers and bicycle activists.The results demonstrate that the tool was found to be easy to use by most practitioners, while recognizing its methodological soundness, a key aspect for increasing its possibility of future use. Crucial evidence was also found as to its usefulness in several steps of the planning process. Most participants recognised an enhanced level of confidence in the potential for cycling in their municipality after being presented with the results of the tool. The ability of GPC to validate planners’ territorial preconceptions with a sound scientific approach is, perhaps, its most valuable contribution.