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Despite the fact that it is the total crop production that shapes future food supply rather than one of its single component, previous studies have mainly focused on the changes in crop yield. It is possible that recent gains in crop production are mainly due to improvement of yield rather than growth of harvest area. However, it remains unclear about the geographical patterns of their relative contributions at fine scales and the possible mechanisms. Analysis of US maize production shows that maize production has increased significantly at a rate of 2.1%/year during 1980-2010. Although yield is the dominant factor contributing to production growth for the country as a whole, the importance of harvest area has become more evident with time. In 56% of US's maize growing counties, harvest area has also contributed more than yield to production changes. High spatial correlation between the change rates of harvest area and production is observed (R = 0.96), while a weak relation (R = 0.21) is found between the spatial patterns of yield and production. This suggests that harvest area has exerted the dominant role in modulating the spatial distribution pattern of maize production changes. Further analysis suggests that yield and harvest area respond differently to climate variability, which has great implications for adaptation strategies. Comparing 11 state-of-the-art crop model simulations against census data reveals large bias in the simulated spatial patterns of maize production. Nevertheless, such bias can be reduced substantially by incorporating the observed dynamics of harvest area, pointing to a potential pathway for future model improvement. This study highlights the importance of accounting for harvest area dynamics in assessing agricultural production empirically or with crop models.

Terrestrial ecosystems, occupying 28.26% of Earth's surface, are extensively at risk from droughts, which is likely to propagate into human communities owing to loss of vital services. Ecosystem risk also tends to fluctuate within anthropogenically-forced nonstationary environments, raising considerable concerns about effectiveness of mitigation strategies. This study aims to assess dynamic ecosystem risk induced by droughts and identify risk hotspots. Bivariate nonstationary drought frequency was initially derived as a hazard component of risk. By coupling vegetation coverage and biomass quantity, a two-dimensional exposure indicator was developed. Trivariate likelihood of vegetation decline was calculated under arbitrary droughts to intuitively determine ecosystem vulnerability. Ultimately, time-variant drought frequency, exposure and vulnerability were multiplied to derive dynamic ecosystem risk, followed by hotspot and attribution analyses. Risk assessment implemented in the drought-prevalent Pearl River basin (PRB) of China during 1982-2017 showed that meteorological droughts in eastern and western margins, although less frequent, were prolonged and aggravated in contrast to prevalence of less persistent and severe droughts in the middle. In 86.12% of the PRB, ecosystem exposure maintains high levels (0.62). Relatively high vulnerability (>0.5) occurs in water-demanding agroecosystems, exhibiting a northwest-southeast-directed extension. A 0.1-degree risk atlas unveils that high and medium risks occupy 18.96% and 37.99% of the PRB, while risks are magnified in the north. The most pressing hotspots with high risk continuing to escalate reside in the East River and Hongliu River basins. Our results provide knowledge of composition, spatio-temporal variability and driving mechanism of drought-induced ecosystem risk, which will assist in risk-based mitigation prioritization.

AbstractThe land–river interface (LRI) is important for sustainable development. The environmental processes that define the LRI support the natural capital and ecosystem services that are linked directly to multiple Sustainable Development Goals (SDGs). However, existing approaches to scale up or down SDG targets and link them to natural capital are insufficient for the two-way human–environment interactions that exist in the LRI. Therefore, this study proposes a place-based approach to interpret the SDG framework to support sustainable land/water management, by (i) identifying key priorities for sustainable development through a normative content analysis of the SDG targets, and (ii) illustrating these priorities and associated challenges within the LRI, based on a literature review and case-studies on human–environment interactions. The content analysis identifies three overarching sustainable development priorities: (i) ensuring improved access to resources and services provided by the LRI, (ii) strengthening the resilience of the LRI to deal with social and natural shocks, and (iii) increasing resource efficiency. The review of the current state of LRIs across the world confirms that these are indeed priority areas for sustainable development. Yet, the challenges of attaining the sustainable development priorities in the LRI are also illustrated with three examples of development-related processes. Urbanisation, dam construction, and aggregate mining occur within specific zones of the LRI (land, land–river, river, respectively), but their impacts can compromise sustainable development across the entire LRI and beyond. The existence of these unintended impacts highlights the need to consider the geomorphic, hydrological, and ecological processes within the LRI and how they interact with human activity. Identifying the place-based priorities and challenges for sustainable development will help achieve the SDGs without compromising the functions and services of the LRI.