Forest restoration is a crucial natural climate solution, yet its long-term carbon benefits remain uncertain. Globally, three main strategies are adopted: natural regeneration (NR), assisted natural regeneration (ANR), and active restoration (AR). We integrated 36 years of aboveground carbon (AGC) dynamics derived from lidar, Landsat, and forest monitoring plots across East Africa and applied a a quasi-experimental framework to quantify the additionality of active interventions (including AR and ANR) for AGC change over time. We found active interventions commonly exhibit early-stage setbacks in AGC accumulation relative to NR, reflecting site preparation and seedling establishment. However, their impact strengthens over time, becoming pronounced > 9 years after restoration. Long-term AGC gains attributable to ANR and AR range from 0.88 to 3.31 Mg C ha-1 yr-1, with AR performing best in environmentally constrained dry and montane systems and ANR in productive forests facing land-use competition. Optimizing restoration across 14.45 million hectares in East Africa—2.1% of global potential restoration areas—could enhance carbon removal by 2.18 ± 0.36 Gt C by 2050, although less than one-quarter would be realized by 2030. Restoration benefits are therefore strongly time-dependent, and sustained commitment is essential to realize their climate mitigation potential and enhance restoration efficiency.
Governance networks, made of diversified and multidisciplinary actors, have a prominent role in the development and implementation of actions for agri-food system transformation that foster both farm-level and societal change, as in the case of agroecology transitions. This article aims at delivering a typology of governance networks, building on evidence from across Europe. By adopting a governance network theory perspective, a multiple case study is developed through participatory research, by characterising the emerging governance networks from transition actions at different levels in the pathway towards agroecological redesign. Three types of governance networks are identified. Adoption networks develop from early-stage actions in the agroecology transition pathway, to facilitate the shift from conventional to more sustainable farming practices. Positioning networks emerge from actions to create a demand for agroecologically produced food, through the development of marketing strategies and the creation of market channels. Amplification networks are the closest to agroecological redesign, originating from actions structured towards participatory planning and the development and reinforcement of diversity and transdisciplinarity. Advisory services play a key role in all three types, by fostering knowledge diffusion and exchange, as well as by developing trust among farmers and encouraging cooperation, including conflict management. The role of advisory services for agroecology could be strengthened further through targeted policy. Measures to sustain multi-actor cooperation have the potential to create these conditions by developing and exploiting synergies between and within value chains, and with other relevant actors, including consumers.
Hedgerows provide habitat and food for a wide range of species and play a crucial role for biodiversity in agricultural landscapes. In addition, hedgerows render an important carbon stock, above and below ground, and protect agricultural soils from erosion. However, comprehensive, standardized and area wide information regarding the distribution of hedgerows is often lacking, which makes it hard to incorporate them in nature conservation plans and national carbon balance models. We evaluate the potential of high-resolution PlanetScope multitemporal satellite data and semantic segmentation approaches to map the distribution of hedgerows across the entire agricultural landscape in Germany. Based on a comprehensive set of independent reference data from the federal state of Schleswig-Holstein, we evaluate the performance of different loss functions and different combinations of spectral and temporal input feature sets. We assess the transferability of the final model using independent test data from three additional German Federal states. Additionally, we compare our results against the Copernicus Land Monitoring Service High Resolution Layer Small Woody Features, and a recently published biomass map of trees outside forests. All loss functions tested offered similar performance, but the binary-cross entropy function allowed for overcoming sensor artifacts to some extent. Visible and near-infrared imagery from all four monthly mosaics (April, June, August and October) of PlanetScope data was found to yield better results (F1-score 0.65) than different combinations of months and only red-green-blue inputs. We estimate a total surface of 4081 (+/- 1425) km2 of hedgerows across Germany, which represent 2.3 % of the agricultural land in Germany. By combining our results with a digital landscape model, we reveal heterogenous estimates of hedgerow height across municipalities. Our findings highlight that semantic segmentation approaches are wellsuited for area-wide hedgerow mapping, especially in combination with multitemporal high-resolution satellite data. Furthermore, we underscore the relevance of using application-specific models over post-processing existing products, and provide for the first time a spatially explicit and comprehensive overview of the distribution of hedgerows and their structure across agricultural landscapes in Germany. Our methodology and product can be incorporated into landscape biodiversity models, carbon balance estimations and soil protection policies at national, regional and local scale.
The crop cover and management factor (C factor) is crucial to assess the impact of management on soil erosion by water within the (R)USLE (Revised Universal Soil Loss Equation) modelling framework. Its derivation is challenging due to the need for spatiotemporal data on crop sequences. Therefore, the aim of this study is the generation of spatiotemporal detailed C factor datasets for Germany by integrating (a) crop composition data from agricultural statistics on the municipality level for six individual years from 1999 to 2020 and (b) high-resolution (10 x 10 m) crop sequence information for 2017 to 2023 derived from earth observation data in the C factor estimation. The results reveal an overall increase of 8.7 % in the mean C factor for German municipalities from 1999 to 2020, which can be attributed to policy-driven changes in crop composition. The comparison of the two C factor datasets emphasises the importance of multi-annual information on crops in (R)USLE-based erosion modelling as (i) highresolution C factors based on single years show a weak agreement with crop sequence-derived C factors (RMSE of 0.062) and (ii) C factors based on crop composition data from agricultural statistics are 5.7 % lower compared to high-resolution crop sequence-derived C factors. As high-resolution crop type data from earth observation is updated yearly, the C factor maps presented here can be incorporated into German monitoring systems as agri-environmental indicators. Further research is needed to obtain more detailed information on cover crops and tillage practices to improve C factor derivation. These findings and the visible heterogenious patterns in the pixel-based multi-annual C factor data highlight that spatiotemporal high-resolution input data is key in C factor estimation. (c) 2025 International Research and Training Center on Erosion and Sedimentation, China Water & Power Press, and China Institute of Water Resources and Hydropower Research. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The aim of the study was to analyze the meat quality of immunocastrated (Improvac®, IC) male in comparison with female (GI), surgically castrated (BA) and entire male (EM) fattening pigs. In contrast to previous experimental studies, this analysis is based on slaughter data from routine slaughtering from one slaughterhouse (Germany), which offered farmers since 2018 the option of voluntarily supplying IC without the usual financial deduction for boars. Carcass parameters were assessed using AutoFOM III™. Until 2022, data from 1,736,684 pigs from 203 farms were available. After checking for completeness, plausibility and gender balance, slaughter data of 1,613,660 pigs with 434,479 IC from 182 farms remained for analysis. Number of IC slaughtered per year increased to 48 % during the study period and largely replaced BA animals (5.4 %) in 2022. Sex had the largest influence on the most important carcass parameters (e.g. lean meat percentage), while carcass weight was mainly influenced by the farm, but also by the change in the price mask. The carcass parameters of IC ranked mainly between GI and BA and within the acceptable range of slaughterhouse requirements, with IC tending to have values closer to GI. The analysis shows that the meat quality of IC animals can meet slaughterhouse requirements comparable to GI and BA. Considering the carcass parameters analyzed in this study immunocastration appears to be a sustainable and future-proof solution to the castration controversy and should be promoted through fair accounting of IC via the standard price masks for BA and GI.
