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Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

To increase the spatial resolution of Soil Moisture Active Passive (SMAP), this study modifies the downscaling factor model based on the Temperature Vegetation Drought Index (TVDI) using data from the Project for On-Board Autonomy (PROBA-V). In the modified model, TVDI parameters were derived from the temperature-vegetation space and the Enhanced Vegetation Index (EVI). This study was conducted in the north China region using SMAP, PROBA-V, and Moderate Resolution Imaging Spectroradiometer satellite images. The 9-km spatial resolution SMAP data was downscaled to 0.3-km spatial resolution soil moisture using a modified downscaling method. Downscaling accuracies from the original and modified downscaling factor models were compared based on field observations. The results show that both methods generated similar spatial distributions in which soil moisture estimates increased as vegetation coverage increased from built-up areas to forest. However, based on the root mean square error between observations and estimations, the modified model demonstrated an increased estimation accuracy of 4.2% for soil moisture compared to the original method. This study also implies that downscaled soil moisture shows promise as a data source for subsequent watershed scale studies.

Valorisation of food waste offers an economical and environmental opportunity, which can reduce the problems of its conventional disposal. Food waste is commonly disposed of in landfills or incinerated, causing many environmental, social, and economic issues. Large amounts of food waste are produced in the food supply chain of agriculture: production, post-harvest, distribution (transport), processing, and consumption. Food waste can be valorised into a range of products, including biofertilisers, bioplastics, biofuels, chemicals, and nutraceuticals. Conversion of food waste into these products can reduce the demand of fossil-derived products, which have historically contributed to large amounts of pollution. The variety of food chain suppliers offers a wide range of feedstocks that can be physically, chemically, or biologically altered to form an array of biofertilisers and soil amendments. Composting and anaerobic digestion are the main large-scale conversion methods used today to valorise food waste products to biofertilisers and soil amendments. However, emerging conversion methods such as dehydration, biochar production, and chemical hydrolysis have promising characteristics, which can be utilised in agriculture as well as for soil remediation. Valorising food waste into biofertilisers and soil amendments has great potential to combat land degradation in agricultural areas. Biofertilisers are rich in nutrients that can reduce the dependability of using conventional mineral fertilisers. Food waste products, unlike mineral fertilisers, can also be used as soil amendments to improve productivity. These characteristics of food wastes assist in the remediation of contaminated soils. This paper reviews the volume of food waste within the food chain and types of food waste feedstocks that can be valorised into various products, including the conversion methods. Unintended consequences of the utilisation of food waste as biofertilisers and soil-amendment products resulting from their relatively low concentrations of trace element nutrients and presence of potentially toxic elements are also evaluated.

Global urban development is increasingly becoming an aspect of focus as nations fight sustainability challenges. A review of the current literature on urban sustainability suggests that research on development of cities, in both developed and developing countries, is growing fast, with an emphasis on sustainable development. However, very little of this research contains an integrated framework to systematically identify and examine the various dimensions of urban sustainability and to measure and evaluate them appropriately. Cities are more than the sum of their sectors, and are complex and interdependent systems on whose dynamics the quality of life of millions of human beings and a good part of the economy depend. Environmental, economic, social and governance problems can create formidable barriers to urban sustainability. Governance remains a critically important dimension of urban sustainability, especially when discussing urbanization in developing countries, given rapid population movements and imbalances in socio-economic development. Understanding how cities function is fundamental to resolving these imbalances. The aim of this paper is to provide a review and analysis of the concept of urban sustainability and to propose the development of a holistic framework through integration of environmental, economic, social, and governance dimensions of sustainability. Such a review would make it possible to understand the complex dynamics of the four dimensions and to assess the progress and challenges in moving towards urban sustainability, taking the case of Nairobi, Kenya, as an example. The paper argues that, for urban sustainability in developing countries, more emphasis should be placed on the governance dimension, because this is where the biggest challenge exists, with increasing needs for immediate management of rapid urbanization.

Sugarcane is a lignocellulosic crop and the juice extracted from its stalks provides the raw material for 86% of sugar production. Globally, sugarcane processing to obtain sugar and/or ethanol generates more than 279 million tons of solid and liquid waste annually, as well as by-products; namely, straws, bagasse, press mud, wastewater, ash from bagasse incineration, vinasse from ethanol distillation, and molasses. If not properly managed, this waste will pose risks to both environmental factors and human health. Lately, valorization of waste has gained momentum, having an important contribution to the fulfillment of policies and objectives related to sustainable development and circular bioeconomy. Various technologies are well-established and implemented for the valorization of waste and by-products from sugarcane processing, while other innovative technologies are still in the research and development stage, with encouraging prospects. We propose a sustainable sugarcane processing flow and present an analysis of the physico-chemical characteristics of generated wastes and by-products. We emphasize the available possibilities of valorizing each waste and by-product, considering that they are important biomass resources for obtaining biofuels and a wide range of other products with added value, which will contribute to the sustainability of the environment, agriculture, and human health worldwide.

Data collection Preparation for our quantitative survey included extensive theoretical and literature studies on relational values and human-nature relationships. Building upon prior empirical work in the region (see e.g. (Balázsi et al., 2019; Hartel et al., 2016; Riechers et al., 2019) the questionnaire development included two focus groups with laypersons to improve structure and wording of the questionnaire and a pilot study with n = 20. The questionnaire contained parts on (1) utilisation of nature (Visiting frequency of natural areas in the vicinity from “daily” to “never”; distance travelled to these places from “up to 1km” to “over 10km”, use of different natural products such as water, wood, decorative material from “always” to “never”) (2) attitudes towards nature and nature conservation (importance from “very important” to “not important” of the conservation of specific natural attributes in the landscape), (3) relational, intrinsic and instrumental values and (4) socio-demographic information (see Supplementary Material S1 for the full questionnaire). In our study we focused on nine relational values that were seen as important from our prior research, instrumental and intrinsic values. An overview of the values used in this paper and their description can be found in Table 1. Data were collected through face-to-face surveys, within randomly chosen villages within the focal landscapes. We used proportionate sampling based on the population density of the villages in the focal landscapes. Within the villages the streets and households were sampled randomly. Surveys were conducted on various days of the week. After a second unsuccessful try, selected households were marked as dropouts. To decrease the dropout rate we did not randomly select respondents within a given household. All respondents were asked for an oral consent to participate in this study, as a personal signature was deemed to create discomfort and increase drop-out rates, especially in Romania. Data were collected between April and July 2017. This resulted in a total sample size of n = 819 across 52 villages (Romania n = 22, Germany n = 30). The ethics approval of this research was granted by the Leuphana University. Data analysis Exploratory factor analysis Our relational value data frame had a size of N = 819 observations of 18 variables. We imputed missing data with the method of predictive mean matching. Cronbach’s α for these variables was 0.83, while Kaiser-Meyer-Olkin’s measure of sampling adequacy was 0.93, well above the recommended value of 0.6, Bartlett’s test of sphericity was significant (χ² (153) = 5583.0, p < .001). All of these diagnostics suggest reasonable factorability. We considered three, four and five-factor models using oblimin rotation and a minimum residual factoring method. Associated scree plots and fit statistics indicated that the four-factor model was sufficient (RMSEA = 0.071, Tucker-Lewis-Index = 0.885). The four factors explained 29%, 7%, 5% and 4% of the variance respectively for a total of 45%. We refrained from removing items with factor loadings <0.4 because of our sample size of well above 300 (Stevens, 2002 :395). We provide the full loadings matrix in Table 3. We created composite scores for each factor by adding the scores of the items loading onto each factor for subsequent regression analysis. Candidate modeling We modelled the response of the three latent factors to a set of socio-demographic variables using beta regression models (Cribari-Nieto and Zeileis, 2010; Grün et al., 2012) on the latent factor scores that we transformed to the open standard unit interval (0, 1). The transformation applied was the one recommended by Smithson and Verkuilen (Smithson and Verkuilen, 2006), so that y’ = (y × (n – 1) + 0.5) / n where y is the data of length n. We based the set of candidate models on grouping explanatory variables into three categories: personal characteristics of the respondent (‘P’: gender, age), nature-based variables (‘N’: distance travelled, attitude towards conservation, visiting frequency, frequency of use of natural products) and focal landscape (‘L’). We constructed the following set of eight candidate models, which may be seen as our hypotheses regarding what variables might explain the latent factor scores observed: Null, N, P, L, N + P, N + L, L + P, N + P + L. We based model selection on AICc values and used the full average method where model averaging was required (Grueber et al., 2011; Nakagawa and Freckleton, 2011). We conducted our analyses using the R programming language (R Core Team 2019). We present the coefficients of the best-fitting models for each latent factor in Tables 4 and 5 and in the supplementary tables A1-A4. Relational values recently emerged as a concept to comprehensively understand and communicate the many values of nature. Relational values can be defined as preferences and principles about human-nature relationships and focus both on human-nature connections, as well as human-human connections. Here, drawing on 819 face-to-face questionnaires, we analysed relational, intrinsic and instrumental values across a total of six agricultural landscapes in Transylvania (Romania) and Lower Saxony (Germany). The landscapes described a gradient of land use intensity, within and across the countries. Our results suggest a bundling of values into four groups: those concerned with individual cognition (including intrinsic values), those that focus on nature as a place for social interaction and relaxation, those that capture cultural identity and spiritual values and one bundle that only includes instrumental values. These different values, in turn, were strongly related to (i) respondents’ attitudes towards environmental conservation and the (ii) frequency with which respondents used nature as a resource. Instrumental values have the tendency to be inversely related with relational values and were found to increase with the land use intensity of the focal landscapes. Data has been anonymised.

World Heritage Sites (WHSs) play an important role in sustaining community identity and enhancing local economic development through tourism. Although the Li River was designated as a WHS in 2014, severe damage to its ecosystem and environmental problems have been reported in recent years. Thus, the purpose of this study is to estimate residents’ willingness to pay (WTP) for the preservation of the Li River using a contingent valuation method. Moreover, a two-stage approach using hypothetical and real setting scenarios was utilized to reduce a hypothetical bias and overvaluation. Logit models were used to estimate the preservation value and compare factors influencing WTP between the hypothetical and real scenarios. The results of this study support the usefulness of a two-stage approach to avoid hypothetical bias and estimate a realistic preservation value. In the real setting scenario, WTP was 144.66–163.90 Yuan (USD 20.83–23.60) per capita per year, and the aggregate value was 721–818 million Yuan (USD 104–118 million) depending on mean WTP and truncated WTP. The study findings provide useful implication to support government’s fund and sustainable efforts to preserve the Li River.

AbstractThe objective of this research was to determine the capacity of a soil tillage system in soil conservation, in productivity and in energy efficiency. The minimum tillage and no-tillage systems represent good alternatives to the conventional (plough) system of soil tillage, due to their conservation effects on soil and to the good production of crops (Maize, 96%-98% of conventional tillage for minimum tillage, and 99.8% of conventional tillage for no till; Soybeans, 103%-112% of conventional tillage for minimum tillage and 117% of conventional tillage for no till; Wheat, 93%-97% of conventional tillage for minimum tillage and 117% of conventional tillage for no till. The choice of the right soil tillage system for crops in rotation help reduce energy consumption, thus for maize: 97%-98% energy consumption of conventional tillage when using minimum tillage and 91% when using no-tillage; for soybeans: 98% energy consumption of conventional tillage when using minimum tillage and 93 when using no-tillage; for wheat: 97%-98% energy consumption of conventional tillage when using minimum tillage and 92% when using no-tillage. Energy efficiency is in relation to reductions in energy use, but also might include the efficiency and impact of the tillage system on the cultivated plant. For all crops in rotation, energy efficiency (energy produced from 1 MJ consumed) was the best in no-tillage — 10.44 MJ ha−1 for maize, 6.49 MJ ha−1 for soybean, and 5.66 MJ ha−1 for wheat. An analysis of energy-efficiency in agricultural systems includes the energy consumed-energy produced-energy yield comparisons, but must be supplemented by soil energy efficiency, based on the conservative effect of the agricultural system. Only then will the agricultural system be sustainable, durable in agronomic, economic and ecological terms. The implementation of minimum and no-tillage soil systems has increased the organic matter content from 2% to 7.6% and water stable aggregate content from 5.6% to 9.6%, at 0–30 cm depth, as compared to the conventional system. Accumulated water supply was higher (with 12.4%-15%) for all minimum and no-tillage systems and increased bulk density values by 0.01%-0.03% (no significant difference) While the soil fertility and the wet aggregate stability have initially been low, the effect of conservation practices on the soil characteristics led to a positive impact on the water permeability in the soil. Availability of soil moisture during the crop growth period led to a better plant watering condition. Subsequent release of conserved soil water regulated the plant water condition and soil structure.