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Monitoring pesticide use is essential for assessing farming practices and the risks associated with the use of pesticides. Currently, there are neither consolidated, public data available on glyphosate use in Europe, nor a standardized categorization of its major uses. In this study, data on glyphosate sales and use in Europe were collected from multiple sources and compiled into a dataset of the agricultural use of glyphosate from 2013 to 2017. The survey shows that glyphosate represented 33% of the herbicide volume sold in Europe in 2017. One third of the acreage of annual cropping systems and half of the acreage of perennial tree crops received glyphosate annually. Glyphosate is widely used for at least eight agronomic purposes, including weed control, crop desiccation, terminating cover crops, terminating temporary grassland and renewing permanent grassland. Glyphosate use can be classified into occasional uses—i.e., exceptional applications, triggered by meteorological conditions or specific farm constraints—and recurrent uses, which are widespread practices that are embedded in farming systems and for which other agronomic solutions may exist but are not frequently used. This article proposes a framework for the precise monitoring of glyphosate use, based on the identification of the cropping systems in which glyphosate is used, the agronomic purposes for which it is employed, the dose used and the rationale behind the different uses.

The land ecosystem provides essential natural resources for the survival and development of human beings. Therefore, land ecological security (LES) acts as a vital part of the sustainable development of human society and economy. This study included a dynamic analysis of land use change in Chaohu Lake Basin (CLB) in China from 1998 to 2018, evaluating the spatiotemporal patterns of LES at both the administrative district scale and grid scale (200 m × 200 m). Then, geographic detector was applied to analyze the influence of the assessment index on LES. The results show that in the 2008–2018 period, land use changed more significantly compared to the 1998–2008 period. The continuous extension of urban land led to a decrease in the areas of other land use types. In the CLB (administrative district scale), the LES levels varied throughout the study period. In Changfeng, Feixi, and the other three regions, the LES has been significantly improved. However, the LES in six other regions showed different degrees of decline, particularly in Hexian and Urban Hefei. Simultaneously, the LES showed a gradual improvement at a 200 m × 200 m grid scale level. The influence of anthropogenic factors on the LES was stronger than natural factors. Findings from this study provide reliable guidance for improving the ecosystem environment in ecologically fragile areas.

Due to an increase in international demand, quinoa production has boomed tremendously in the Andes since the early 2010s. This has led to significant investments into developing improved varieties for large-scale agribusinesses, but breeding programs are not tailored to the needs of smallholders. In this paper, we study farmers’ preferences and willingness to pay for improved quinoa varieties in the Junín region in Peru. We use data from a choice experiment among 458 smallholders and estimate generalized multinomial logit models to control for preference and scale heterogeneity. We find that farmers generally prefer improved varieties over traditional varieties, with mildew-resistance as the most important crop trait. In general, farmers prefer varieties that are characterized by larger grain sizes, higher yield levels, lower levels of saponin, and a reduced maturation period. Yet, food-insecure farmers are found to be indifferent to early maturity and a larger grain size, which can be explained by a lower degree of commercialization among these farmers. Our results imply that developing mildew-tolerant and higher-yielding varieties with a medium to low saponin content is a priority if investments in quinoa technologies are to benefit small-scale and food insecure farmers in the Andean highlands of Peru.

Given the multidimensional nature of climate change issues, decision-making in climate change adaptation is a complex process, and suitable decision support methods are needed. The aim of this paper was to rank saltwater intrusion adaptation options for farmers in two provinces in the central coastal region of Vietnam using the analytical hierarchy process method. Data for the analysis were obtained through a literature review, field observations, and face-to-face interviews and focus group discussions with key informants. We combined two ways of weighting to arrive at final scores for each of the identified adaptation options: prioritizing criteria and subcriteria by pairwise comparison and rating the different alternatives with respect to the lowest level subcriteria. In doing so, we also investigated differences in the priority sets and final rankings of the analytical hierarchy process applications in both provinces. In our study, we worked with group consensus scores on both the criteria weights and the ratings for the different adaptation options for each of the criteria. Our results revealed that “sustainability and equity” was the most important criteria, while coherence ranked lowest. The final ranking of adaptation options differed between both provinces due to differences in the geographical and socioeconomic characteristics of the study areas. The consistency ratios for all pairwise matrices were less than 0.1, indicating that judgments from the focus group discussions with respect to the different criteria were highly consistent. A sensitivity analysis of our results confirmed the robustness of the rankings in our research.

Green space in intra-urban regions plays a significant role in improving the human habitat environment and regulating the ecosystem service in the Inner Mongolian Plateau of China, the environmental barrier region of North China. However, a lack of multi-scale studies on intra-urban green space limits our knowledge of human settlement environments in this region. In this study, a synergistic methodology, including the main process of linear spectral decomposition, vegetation-soil-impervious surface area model, and artificial digital technology, was established to generate a multi-scale of green space (i.e., 15-m resolution intra-urban green components and 0.5-m resolution park region) and investigate multi-scale green space characteristics as well as its ecological service in 12 central cities of the Inner Mongolian Plateau. Results showed that: (1) Total urban areas and urban green space across the studied cities were 1249.87 km2 and 295.40 km2, indicating that the average proportion of green space to urban areas was 24.03%. (2) The proportion of green space to urban areas ranged from 17.09% to 32.17%, and the proportion of parks’ green space to green space ranged from 5.55% to 50.20%, indicating a wide range of quantitative discrepancies. (3) In different climate regions, there were higher proportions of urban/park green space in arid/semi-arid areas to reduce the impacts of dry climate on human settlements; by contrast, lower green space in humid areas mainly displayed a scattered pattern because of the relatively lower influence of climate pressure. (4) Green coverage was an essential indicator of the “Beautiful China” project, and its ratio within 500-m ecological service zones from parks across all cities was 46.14%, which indicated that the ratio of residential land and green space was close to 1:1. Overall, urban/park green space patterns in urban areas adapted to the different climate features in the Inner Mongolian Plateau. For better human settlement sustainability across all studied cities, more greening patches and ecological corridors should be designed in the lower green space regions of the Inner Mongolian Plateau.

This article reinterprets open space as the theatre of adaptive regimes in the interfering wakes of two major waves of transformation: the agricultural and the urban transformation. The aim of the wave regime concept is to accommodate traditional and emerging land uses in a logical scheme of co-existing regimes separated by transition waves in space and time. Each wave corresponds to a transitional stage from one set to another set of value regime, which by the agents of the transformation is interpreted as a major value increase. The current struggle for space and the difficult interpretations of quality and sustainability can be explained as expressions of competition between value regimes. These value regimes tend to be driven and perpetuated by customary paradigms of land-use planning and management (urban planning, ecology, agronomy, etc.). Land-use sectors ask for rather unambiguous definitions and clear use rights of land use categories and zoning, leaving limited possibility for interaction, mixed regimes and innovative multifunctional land-use. New service demands, new sustainability and resilience urgencies challenge these customary land-use planning paradigms and their rules and instruments. This paper acknowledges a third wave and consequent fourth regime. This regime seeks overall increased sustainability and resilience in open spaces, stressing the strategic importance of unsealed soils and other life conditioning substrates. Different existing land-use models, such as “transition towns”, “agroforestry” and many more, can be interpreted as fourth regime examples, but altogether there is a need for more coordination or integration to turn the third wave concept into a real “wave”. A specific target is to scan territories for characteristics and values according to the prevailing regimes, and assess each unit in terms of third wave transition opportunities, even within active uses that may be at odds with customary rules and expectations. This is illustrated for cases of illegal intake of farmland for non-agricultural activities and for domestic gardens as a missing category in customary rural and land use policy.

Coastal communities living in the low delta areas of Vietnam are increasingly vulnerable to tropical storms and related natural hazards of global climate change. Particularly in the Red River Delta Biosphere Reserve (RRDBR), farmers change the crop structure and diversify agricultural systems to adapt to the changing climate. The paper deals with a quantitative approach combined with behavior theories and surveyed data to analyze farmers’ intention to climate change adaptation in agriculture. Based on the Protection Motivation Theory (PMT), seven constructs are developed to a questionnaire surveying 526 local farmers: risk perception, belief, habit, maladaptation, subjective norm, adaptation assessment, and adaptation intention. Structural Equation Modeling (SEM) is implemented to extract eight factors and to quantify the relationship between protective behavior factors with the adaptation intention of the surveyed farmers. Two bootstrap samples of sizes 800 and 1200 are generated to estimate the coefficients and standard errors. The SEM result suggests a regional and three local structural models for climate change adaptation intention of farmers living in the RRDBR. Farmers show a higher adaptation intention when they perceive higher climate risks threatening their physical health, finances, production, social relationships, and psychology. In contrast, farmers are less likely to intend to adapt when they are subject to wishful thinking, deny the climate risks, or believe in fatalism.