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The major threat to human societies posed by undernutrition has been recognised for millennia. Despite substantial economic development and scientific innovation, however, progress in addressing this global challenge has been inadequate. Paradoxically, the last half-century also saw the rapid emergence of obesity, first in high-income countries but now also in low- and middle-income countries. Traditionally, these problems were approached separately, but there is increasing recognition that they have common drivers and need integrated responses. The new nutrition reality comprises a global ‘double burden’ of malnutrition, where the challenges of food insecurity, nutritional deficiencies and undernutrition coexist and interact with obesity, sedentary behaviour, unhealthy diets and environments that foster unhealthy behaviour. Beyond immediate efforts to prevent and treat malnutrition, what must change in order to reduce the future burden? Here, we present a conceptual framework that focuses on the deeper structural drivers of malnutrition embedded in society, and their interaction with biological mechanisms of appetite regulation and physiological homeostasis. Building on a review of malnutrition in past societies, our framework brings to the fore the power dynamics that characterise contemporary human food systems at many levels. We focus on the concept of agency, the ability of individuals or organisations to pursue their goals. In globalized food systems, the agency of individuals is directly confronted by the agency of several other types of actor, including corporations, governments and supranational institutions. The intakes of energy and nutrients by individuals are powerfully shaped by this ‘competition of agency’, and we therefore argue that the greatest opportunities to reduce malnutrition lie in rebalancing agency across the competing actors. The effect of the COVID-19 pandemic on food systems and individuals illustrates our conceptual framework. Efforts to improve agency must both drive and respond to complementary efforts to promote and maintain equitable societies and planetary health.

Land use change under rapid urbanization can drastically change terrestrial ecological conditions. This study presents an integrated analysis of land use dynamics and the resultant ecological impacts on sustainable development over the past 25 years (1990–2015) in response to urban development. Remote sensing and geographic information system techniques were employed to examine the spatiotemporal trajectory of land use changes. Based on the analysis of the equivalent factor table for land use types and ecosystem services value (ESV), the value of ecosystem services was calculated in the case study of Fuyang, China. Correlations were identified between ESV and a family of landscape fragmentation metrics. The results showed that the area affected by land use changes represented 33.35% of the total study area and caused a 31.74 million US$·a−1 decrease in ESV from 1990 to 2015. The ESV was spatially imbalanced and generally low in urban areas. Ecological plans for cropland reforestation and urban green projects were effective in slowing ESV losses while urban areas rapidly developed. In addition, total ESV was negatively correlated with edge density (ED), patch density (PD), landscape shape index (LSI), and Shannon's diversity index (SHDI) but positively correlated with aggregation index (AI), suggesting that landscape fragmentation had an adverse impact on the overall ESV in Fuyang. Therefore, sustainable land use planning must be integrated with landscape patterns to provide useful guidance regarding the spatial regulation of a given area to protect and improve ecosystem services.

Land suitability analysis is an important step in land use planning for livestock development because of its high efficiency to allocate livestock farms to the most suitable land areas and minimize adverse effects on environment. This study aimed to use two multi-criteria analysis approaches: Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA), to comparatively evaluate and map land use suitability for livestock production in Hangzhou metropolitan area, China. The evaluation used eight factors as suitability criteria, relating to topographic, environmental, human factors, and socio-economic data. The analytic hierarchy process (AHP) method and GIS techniques were integrated into the evaluation models to create the land suitability map. The results of WLC approach showed that 11.4% of the total area was highly suitable for livestock production while 48.6% was unsuitable. Of these, areas located far from central city had higher suitability, while areas close to the urban district, drinking water source area, ecological and natural conservation area, had lower suitability. Sensitivity analysis indicated this expert suitability results for livestock production were robust. Indirect validations conducted by mutual comparisons of suitability maps computed using the WLC and OWA approaches demonstrated 90.4% of the overall agreement with a kappa coefficient of 0.857, indicating that both methods provide very similar spatial land use suitability distributions. Ecological fitness was evaluated by comparing the suitability analysis result with a previous livestock development planning and several recommendations aimed at improving the long-term livestock development plans were made for Hangzhou.

Background: Early childbirth is associated with adverse maternal and child health outcomes. In South Asia, where women generally marry before having children, public health efforts need to focus on delaying marriage. Female education is widely considered the primary means to achieve this. However, it remains unclear how much education is required to delay marriage to the universal minimum age of 18 years, or what predicts marriage age in women lacking any education. This is crucial to address in the Terai region of Nepal which has the highest proportion of children out of school and where girls marry and have their first pregnancy early. Methods: We analyzed data from 6,406 women aged 23-30 years from a cluster-randomized trial in lowland Terai Nepal. Using Kaplan-Meier survival analysis, multivariable logistic and Cox proportional hazards regression models, we investigated associations between women's education level and age at marriage and first pregnancy, and the interval between these events. Among the uneducated women, we investigated associations of husband's education level with the same outcomes. Results: Compared to uneducated women, educated women had a greater probability of delaying marriage until the age of 18 years and of pregnancy until 20 years. Women needed to complete grade 9, and ideally 11, to substantially increase their odds of marrying after 18 years. Delaying first pregnancy to 20 years was largely due to marrying later; education had little extra effect. The association of marriage with first pregnancy age worked independently of education. However, later-marrying women, who generally had completed more education, had their first pregnancy sooner after marriage than earlier marrying women. Most uneducated women, regardless of their husbands' level of education, still married under the legal age of marriage. Conclusion: Delaying marriage to majority age requires greater efforts to ensure girls get to school in the first place, and complete secondary education. Since currently only 36% of girls in the Terai attend secondary school, parallel efforts to delay marriage are crucial to prevent early childbearing. Sexual and reproductive health programmes in school and in women's groups for married and uneducated adolescents may help prepare for marriage and pregnancy.

Airborne Lidar (Light detection and ranging) is an efficient tool for the generation of Digital Terrain Models (DTMs). Although many studies have been conducted in generating DTMs using Lidar data, it is still a challenging research area. The difficulty in filtering large buildings as well as a diversity of urban features makes the design of urban DTM generating methods an ongoing priority. This research adopted an upward-fusion methodology to generate urban DTMs using airborne Lidar data. Firstly, several preliminary DTMs of different resolutions were obtained using a local minimum method. Next, upward fusion was conducted between these DTMs. This process began with the DTM of the largest grid size, which was treated as a trend surface. A finer DTM was compared with this large scale DTM. By setting appropriate thresholds, a new DTM was achieved by selecting qualified elevation values from the finer DTM and retaining the value of the trend surface when the value from the finer DTM was beyond the threshold. This process continued iteratively until all preliminary DTMs had been included in the upward fusion and a refined DTM of high resolution was achieved. To further reduce possible errors in the resulting DTM, an extended local minimum method was proposed for filtering outliers and generating preliminary DTMs. A case study was carried out in the city of Cambridge, which represents an urban landscape with a variety of building forms, street patterns and vegetation structures. The time efficiency, results of the accuracy assessments and comparison with leading software proved the success of the case study and indicated that upward-fusion was an effective method for the generation of urban DTMs with airborne Lidar data and could improve the accuracy of other DTM generating algorithms. This paper also proposed possible approaches for further improvements on this methodology.

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale.

This paper examines the impact that different olive cultivation practices have on the nature of the ground flora of olive groves in the region of the Psiloritis massif and Messara Plain in central and southern Crete, Greece. In lower, flatter areas there are areas of both traditional and intensive forms of olive cultivation. In more marginal, upland areas there are traditional terraced olive groves, some of which are being abandoned. The relationship between the vegetation composition of the ground flora and environmental variables was established, by means of TWINSPAN® and ordination analysis, using survey data from nineteen sites across the region. Four vegetation communities are identified: olive with herbaceous taxa; olive with sclerophyllous shrub taxa; and two forms of sclerophyllous shrub communities. Ordination results indicate that environmental variables, such as soil characteristics, slope aspect and slope angle, explain about 60 per cent of the species–environment relationships. The remaining variation in species composition is interpreted to be the result of different cultivation practices. The implications for land degradation are examined, in particular the changes in vegetation diversity of both intensive and semi-abandoned olive groves, the potential for increased soil erosion, and the risk of fire as a result of increased fuel loading as flammable shrubs invade abandoned terraces. Intensification of olive cultivation in Crete, and across the Mediterranean, has been encouraged by subsidies from the European Union leading to rapid landscape change. Thus there is a need to monitor changes in olive cultivation practices both at the local scale, by means of ground-based fieldwork, and at landscape and regional scales, by means of remote sensing. Copyright © 2006 John Wiley & Sons, Ltd.

Aim This paper describes the development of novel indices of bird-habitat preference to examine bird species’ use of habitats and their distributions relative to habitats. It assesses the implications for bird conservation regionally and the scope for biodiversity assessments generally. Location A 200 km by 400 km area of farmland with seminatural and urban areas, covering south-eastern England. Methods Cluster analysis was used to link birds to landscapes. Cluster centroid coordinate values were processed to derive indices of bird-habitat preference. Further developments assessed the relative values of individual habitats for birds. Results Clustering objectively linked birds to landscapes. Maps of the clusters showed strong regional patterns associated with distinctive habitat assemblages. Derived indices related bird species directly to individual habitats and habitats to birds. Even rare species and scarce habitats showed successful linkages, often to each other. Objective corroboration strongly supported the associations of coastal, wetland, urban and woodland birds and habitats; but, it suggested that farmland birds, whose numbers have nearly halved since 1977, may prefer alternative habitats. Main conclusions Land cover maps from remote sensing provide an effective way to link birds to habitats and vice versa. Thus, generalized habitat maps might be used to extrapolate localized or sample-based bird observations or the results of autecological studies, helping to predict and understand bird distributions in the wider countryside. The weak links between farmland birds and farmland habitats in a region dominated by farming, suggests that reasons for the decline in farmland birds may be deep seated and thus hard to reverse. The procedures described are repeatable elsewhere and applicable more generally to evaluate landscapes and biodiversity. It is suggested that remote sensing could rarely be bettered as a means of assessing habitats, comprehensively, over wide areas, in most parts of the world.

This paper develops a comprehensive and objective picture of bird distributions relative to habitats across Britain. Bird species presence/absence data from an extensive field survey and habitat data from the remotely sensed UK Land Cover Map 2000 were analysed in 36,920 tetrads (2 km×2 km) across Britain (a 65% sample of Britain's c. 240 000 km2). Cluster analysis linked birds to generalised landscapes based on distinctive habitat assemblages. Maps of the clusters showed strong regional patterns associated with the habitat assemblages. Cluster centroid coordinates for each bird species and each habitat were combined across clusters to derive individualised bird–habitat preference indices and examine the importance of individual habitats for each bird species. Even rare species and scarce habitats showed successful linkages. Results were assessed against published accounts of bird–habitat relations. Objective corroboration strongly supported the associations. Relatively scarce coastal and wetland habitats proved particularly important for many birds. However, extensive arable farmland and woodland habitats were also favoured by many species, despite reported declines in bird numbers in these habitats. The fact that habitat-specialists do not or cannot move habitat is perhaps a reason for declining numbers where habitats have become unsuitable. This study showed that there are unifying principles determining bird–habitat relations which apply and can be quantified at the national scale, and which corroborate and complement the cumulative knowledge of many and varied surveys and ecological studies. This ‘generality’ suggests that we may be able, reliably and objectively, to integrate and scale up such disparate studies to the national scale, using this generalised framework. It also suggests the potential for a landscape ecology approach to bird–habitat analyses. Such developments will be important steps in building models to develop and test the sustainable management of landscapes for birds.