Hyperspectral remote sensing enables the large-scale mapping of canopy biochemical properties. This study explored the possibility of retrieving the concentration of nitrogen, phosphorus, potassium, calcium, magnesium, and sodium from mangroves in the Berau Delta, Indonesia. The objectives of the study were to (1) assess the accuracy of foliar chemistry retrieval, (2) compare the performance of models based on support vector regression (SVR), i.e. ε-SVR, ν-SVR, and least squares SVR (LS-SVR), to models based on partial least squares regression (PLSR), and (3) investigate which spectral transformations are best suited. The results indicated that nitrogen could be successfully modelled at the landscape level (R 2 = 0.67, root mean square error (RMSE) = 0.17, normalized RMSE (nRMSE) = 15%), whereas estimations of P, K, Ca, Mg, and Na were less encouraging. The developed nitrogen model was applied over the study area to generate a map of foliar N variation, which can be used for studying ecosystem processes in mangroves. While PLSR attained good results directly using all untransformed bands, the highest accuracy for nitrogen modelling was achieved using a combination of LS-SVR and continuum-removed derivative reflectance. All SVR techniques suffered from multicollinearity when using the full spectrum, and the number of independent variables had to be reduced by singling out the most informative wavelength bands. This was achieved by interpreting and visualizing the structure of the PLSR and SVR models.

Aim: The aims of this study were to (1) estimate current rates of woody encroachment across African savannas; (2) identify relationships between change in woody cover and potential drivers, including water constraints, fire frequency and livestock density. The found relationships led us to pursue a third goal: (3) use temporal dynamics in woody cover to estimate potential woody cover.Location: Sub-Saharan African savannas. Methods:The study used very high spatial resolution satellite imagery at sites with overlapping older (2002)(2003)(2004)(2005)(2006) and newer (2011)(2012)(2013)(2014)(2015)(2016) imagery to estimate change in woody cover. We sampled 596 sites in 38 separate areas across African savannas. Areas with high anthropogenic impact were avoided in order to more clearly identify the influence of environmental factors. Relationships between woody cover change and potential drivers were identified using linear regression and simultaneous autoregression, where the latter accounts for spatial autocorrelation.Results: The mean annual change in woody cover across our study areas was 0.25% per year. Although we cannot explain the general trend of encroachment based on our data, we found that change rates were positively correlated with the difference between potential woody cover and actual woody cover (a proxy for water availability; p < .001), and negatively correlated with fire frequency (p < .01).Using the relationship between rates of encroachment and initial cover, we estimated potential woody cover at different rainfall levels. Main conclusions:The results indicate that woody encroachment is ongoing and widespread across African savannas. The fact that the difference between potential and actual cover was the most significant predictor highlights the central role of water availability and tree-tree competition in controlling change in woody populations, both in water-limited and mesic savannas. Our approach to derive potential woody cover from the woody cover change trajectories demonstrates that temporal dynamics in woody populations can be used to infer resource limitations. K E Y W O R D SAfrica, change detection, fire, potential woody cover, savanna, simultaneous autoregression, very high spatial resolution imagery, water constraints, woody cover, woody encroachmentThe work was carried out in the South Dakota State University.---

Abstract. Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP) modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the level of spatial aggregation among woody plants in the landscape will vary across environmental gradients. A high level of woody plant aggregation is most distinct in periodic vegetation patterns (PVPs), which emerge as a result of ecohydrological processes such as runoff generation and increased infiltration close to plants. Similar, albeit weaker, forces may influence the spatial distribution of woody plants elsewhere in savannas. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. Using high-spatial-resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enabled us to elucidate the effects of rainfall regimes (MAP and seasonality), soil texture, slope, and fire frequency on woody vegetation properties. We found that previously documented increases in woody cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. Along a gradient of mean annual precipitation from the driest (< 200 mm yr−1) to the wettest (1200–1400 mm yr−1) end, mean estimates of crown size, crown density, and woody cover increased by 233, 73, and 491 % respectively. We also found a unimodal relationship between mean crown size and sand content suggesting that maximal savanna tree sizes do not occur in either coarse sands or heavy clays. When examining the occurrence of PVPs, we found that the same factors that contribute to the formation of PVPs also correlate with higher levels of woody plant aggregation elsewhere in savannas and that rainfall seasonality plays a key role for the underlying processes.

Driven by population growth and rising incomes, the demand for animal source foods in low and middle-income countries is increasing rapidly. Pork is one of the most commonly consumed animal-based food, with the highest demand being in China due to its largest population and changing dietary habits linked to increasing wealth. Here, we show the changes in pig production systems in terms of farms capacity, productivity and production at the national and provincial levels by analyzing several censuses of China. In addition, we used a downscaling methodology to provide a recent and highly detailed map of the distribution of pigs in China. Between 2007 and 2017, pork production in China increased by 26.6\%, up to 55 million tons and the number of large-scale farms with a yearly production of over 10 000 heads increased by 145\%. Much of the production has changed from extensive backyard subsistence farming to intensive corporate farming. Moreover, the pig distribution has shifted from watercourse-intense southeast to northeast and southwest of China due to environmental policy in 2015. These policy-driven transitions primarily aimed to increase pig production efficiency and reduce environmental impacts and resulted in a profound transformation of geographic production patterns.

&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP) modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the spatial distribution of woody plants in the landscape, will vary across environmental gradients. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. However, a lack of data on woody vegetation structure across African savannas has so far prevented a thorough analysis of their relationships with abiotic factors. Using high spatial resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enables us to elucidate the effects of rainfall regimes (MAP and seasonality), soil texture, slope, and fire frequency on woody vegetation properties. We estimate trends in mean crown size across the African savanna rainfall gradient and show that previously documented increases in woody vegetation cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. We also find a unimodal relationship between mean crown size and sand content suggesting that maximal savanna tree-sizes do not occur in either coarse sands or heavy clays. When examining the occurrence of periodic vegetation patterns (PVPs), we find that the same factors that contribute to the formation of PVPs also correlate with higher levels of woody plant aggregation elsewhere in savannas and that rainfall seasonality plays a key role for the underlying processes.&lt;/p&gt;