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Monitoring crop growth and estimating crop yield are essential for managing agricultural production, ensuring food security, and maintaining sustainable agricultural development. Combining the mechanistic framework of a crop growth model with remote sensing observations can provide a means of generating realistic and spatially detailed crop growth information that can facilitate accurate crop yiel

Introduction: Health problems in people with intellectual and developmental disability (IDD) are traditionally known to be common in adults of all age, with at least twice as many health problems in this group as the general ageing population. In addition, there is considerable international evidence indicating an earlier death for people with IDD compared to the general population, exacerbated by

Crop yield improvement during the last decades has relied on increasing the ratio of the economic organ to the total aboveground biomass, known as the harvest index (HI). In most crop models, HI is set as a parameter; this empirical approach does not consider that HI not only depends on plant genotype, but is also affected by the environment. An alternative is to simulate allocation mechanisticall

This article focuses on citizens’ experiences of enablers of- and barriers to obtaining digital citizenship. E-applications for social assistance are used as an exemplar. In Sweden, as in many countries, there is political pressure on welfare services to become more digitalized, and to offer different kinds of self-service technology such as e-applications. Even if the goals of implementing these

Childhood stunting is a serious public health concern in Rwanda. Although stunting causes have been documented, we still lack a more in-depth understanding of their local factors at a more detailed geographic level. We cross-sectionally examined 615 height-for-age prevalence observations in the Northern Province of Rwanda, linked with their related covariates, to explore the spatial heterogeneity

Remote sensing observations and artificial intelligence algorithms have emerged as key components for crop yield estimation at various scales during the past decades. However, the utilization of multi-source satellite data and machine learning for estimating aggregated crop yield at the regional level in Europe has been only scarcely explored. Our study aims to bridge this research gap by focusing

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO2 enrichm

Across the Arctic, the net ecosystem carbon (C) balance of tundra ecosystems is highly uncertain due to substantial temporal variability of C fluxes and to landscape heterogeneity. We modeled both carbon dioxide (CO2) and methane (CH4) fluxes for the dominant land cover types in a ~100-km2 sub-Arctic tundra region in northeast European Russia for the period of 2006–2015 using process-based biogeoc

The 8.2 ka bp cooling event is assumed to be the most clearly marked abrupt climate event in the Holocene at northern mid- to high latitudes. In this study, we simulate the vegetation responses to the 8.2 ka bp climate change event over Europe and Northern Africa. Our results show that all dominant plant functional types (PFTs) over Europe and North Africa respond to these climate changes, but the

Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to underst

In his comment (Kowalski 2023) on our recent publication (Heiskanen et al. 2022) where we present the Integrated Carbon Observation System (ICOS) research infrastructure, Andrew Kowalski introduces three important and, in our opinion, different potential issues in the definition, collection, and availability of field measurements made by the ICOS network, and he proposes possible solutions to thes

Accurate maps of past land cover and human land use are necessary for studying the impact of anthropogenic land-cover changes, such as deforestation, on the climate. The maps of past land cover should ideally be separated into naturally occurring vegetation and human-induced changes, thereby enabling the quantification of the effect of human land use on the past climate. A Bayesian hierarchical mo

Land cover governs biogeophysical and biogeochemical feedbacks between the land surface and atmosphere. Holocene vegetation-atmosphere interactions are of particular interest, both to understand the climate effects of intensifying human land use and as a possible explanation for the Holocene Conundrum, a widely studied mismatch between simulated and reconstructed temperatures. Progress addressing

The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a reali

Nonlinear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross-compartmental feedback loops in the Earth system. These feedbacks are less well represented in the traditional stand-alone atmosphere and ocean models on which many of today's regional climate assessments rely (e.g., EURO-CORDEX, NOSCCA and BACC II). This has promote

In this work, the forestry-enabled dynamic vegetation model LPJ-GUESS was used to simulate forest standing volume for the three main regions of Sweden. At the regional scale, the model results were evaluated against observational data from the Swedish National Forest Inventory. Carbon fluxes of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco) were si

Cover crops (CCs) can improve soil nutrient retention and crop production while providing climate change mitigation co-benefits. However, quantifying these ecosystem services across global agricultural lands remains inadequate. Here, we assess how the use of herbaceous CCs with and without biological nitrogen (N) fixation affects agricultural soil carbon stocks, N leaching, and crop yields, using

We present an analysis of atmospheric transport impact on estimating CO2 fluxes using two atmospheric inversion systems (CarboScope-Regional (CSR) and Lund University Modular Inversion Algorithm (LUMIA)) over Europe in 2018. The main focus of this study is to quantify the dominant drivers of spread amid CO2 estimates derived from atmospheric tracer inversions. The Lagrangian transport models STILT

Over the past half-century, drastically increased chemical fertilizers have entered agricultural ecosystems to promote crop production on the Yangtze Plain, potentially enhancing agricultural nutrient sources for eutrophication in freshwater ecosystems. However, long-term trends of nitrogen dynamics in terrestrial ecosystems and their impacts on eutrophication changes in this region remain poorly