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Multiple cropping, the simultaneous cultivation of several crops in space or time, is a global practice essential for intensifying and diversifying agriculture. Despite its substantial impact on environmental and socioeconomic outcomes of farming, multiple cropping is hardly accounted for in assessments of global food production, sustainability, and climate impacts. Such studies, often relying on

The expansive carbon reservoirs of the boreal region are becoming some of the most rapidly growing sources of greenhouse gasses under a positive feedback between intensifying fire activity and climate change. However, current regional-scale methods lack the spatial precision needed to improve understanding of the drivers of these fluxes to inform strategies aimed at maximizing landscape carbon sto

Reference pollen data for use in interpreting fossil pollen assemblages may be either collected as surface samples or monitored by means of pollen traps. Surface samples can be obtained from moss polsters or lake-surface sediment, or exceptionally soil, leaf litter, or snow. The advantage of such samples is that a large number can be collected relatively quickly. Within the resulting pollen assemb

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

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

Forestation is expected to play an significant role as a terrestrial carbon dioxide removal technology in low-emission scenarios by storing carbon in the biosphere, thereby changing the physical properties of the land surface. To represent land use change, including afforestation and reforestation (AR), Earth system models (ESM) that contribute to the Coupled Model Intercomparison Project Phase 6

Nitrogen (N) transformation processes by soil microbes account for significant nitrous oxide (N2O) emissions from natural ecosystems and cropland. However, understanding and quantifying global soil N2O emissions and their responses to changing environmental conditions remain challenging. Here, we implemented a soil nitrification–denitrification module into the dynamic vegetation model LPJ-GUESS to

Nitrous oxide (N2O) is the most important stratospheric ozone-depleting agent based on current emissions and the third largest contributor to increased net radiative forcing. Increases in atmospheric N2O have been attributed primarily to enhanced soil N2O emissions. Critically, contributions from soils in the Northern High Latitudes (NHL, >50°N) remain poorly quantified despite their exposure to r

Meeting the Paris Agreement’s temperature goals requires limiting future carbon emissions, yet current policies make temporarily overshooting the 1.5°C target likely. The potential climate feedback from destabilizing peatlands, storing large amounts of carbon, remains poorly quantified. Using the reduced-complexity Earth System Model OSCAR with an integrated peat carbon module, we found that acros

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

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

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

https://www.jur.lu.se/sites/jur.lu.se/files/2024-10/Kursutv%C3%A4rdering%20JMRA04%20ST24.pdf - 2026-05-24

https://www.jur.lu.se/sites/jur.lu.se/files/2025-04/Kursutv%C3%A4rdering%20JCDA02%20(BO)%20HT24.pdf - 2026-05-24

https://www.jur.lu.se/sites/jur.lu.se/files/2025-04/Kursutv%C3%A4rdering%20Medr%C3%A4tt%20HT24.pdf - 2026-05-24