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Abstract. A 5-year greenhouse gas (GHG) exchange study of the three major gas species (CO2, CH4 and N2O) from an intensively managed permanent grassland in Switzerland is presented. Measurements comprise 2 years (2010 and 2011) of manual static chamber measurements of CH4 and N2O, 5 years of continuous eddy covariance (EC) measurements (CO2–H2O – 2010–2014), and 3 years (2012–2014) of EC measurement of CH4 and N2O. Intensive grassland management included both regular and sporadic management activities. Regular management practices encompassed mowing (three to five cuts per year) with subsequent organic fertilizer amendments and occasional grazing, whereas sporadic management activities comprised grazing or similar activities. The primary objective of our measurements was to compare pre-plowing to post-plowing GHG exchange and to identify potential memory effects of such a substantial disturbance on GHG exchange and carbon (C) and nitrogen (N) gains and losses. In order to include measurements carried out with different observation techniques, we tested two different measurement techniques jointly in 2013, namely the manual static chamber approach and the eddy covariance technique for N2O, to quantify the GHG exchange from the observed grassland site. Our results showed that there were no memory effects on N2O and CH4 emissions after plowing, whereas the CO2 uptake of the site considerably increased when compared to pre-restoration years. In detail, we observed large losses of CO2 and N2O during the year of restoration. In contrast, the grassland acted as a carbon sink under usual management, i.e., the time periods 2010–2011 and 2013–2014. Enhanced emissions and emission peaks of N2O (defined as exceeding background emissions 0.21 ± 0.55 nmol m−2 s−1 (SE = 0.02) for at least 2 sequential days and the 7 d moving average exceeding background emissions) were observed for almost 7 continuous months after restoration as well as following organic fertilizer applications during all years. Net ecosystem exchange of CO2 (NEECO2) showed a common pattern of increased uptake of CO2 in spring and reduced uptake in late fall. NEECO2 dropped to zero and became positive after each harvest event. Methane (CH4) exchange fluctuated around zero during all years. Overall, CH4 exchange was of negligible importance for both the GHG budget and the carbon budget of the site. Our results stress the inclusion of grassland restoration events when providing cumulative sums of C sequestration potential and/or global warming potential (GWP). Consequently, this study further highlights the need for continuous long-term GHG exchange observations as well as for the implementation of our findings into biogeochemical process models to track potential GHG mitigation objectives as well as to predict future GHG emission scenarios reliably.

AbstractGreenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.

In today’s intrinsically connected world, the Water–Food–Energy–Climate Nexus (WFEC Nexus) concept provides a starting point for informed and transparent decision-making based on the trade-offs and synergies between different sectors, including aquatic ecosystems, food security, energy production, and climate neutrality. The WFEC Nexus approach is particularly applicable in regions requiring transboundary water management, such as Central Asia. Unfortunately, this region with unevenly distributed water resources—consisting of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan—is characterized by data scarcity, which limits informed decision-making. However, open-source geodata is becoming increasingly available. This paper aims to fill Central Asia’s WFEC Nexus data gap by providing an overview of key data. We collected geodata through an integrated survey of stakeholders and researchers, stakeholder consultation, and literature screening. Sixty unique datasets were identified, belonging to one of six thematic categories: (1) climate, (2) hydrology, (3) geography and topography, (4) geomorphology, (5) ecology, and (6) anthropogenic uses. For each dataset, a succinct description, including a link to the online source, is provided. We also provide possible applications of using the presented datasets, demonstrating how they can assist in conducting various studies linked to the WFEC Nexus in Central Asia and worldwide.

The Indonesian government recently confirmed its Intended Nationally Determined Contributions (INDCs) to mitigate global climate change. A forest moratorium policy that protects forest and peatland is a significant part of the INDCs; however, its effectiveness is unclear in the face of complex land-use and land-cover change. This study aims to assess the dynamics of land-use change and ecosystem service supply as a function of local decision-making. We developed an agent-based model, Land-Use Change and Ecosystem Services (LUCES), and used it to explore the possible effects of the forest moratorium policy on the land-use decisions of private companies and communities. Our simulations for two districts in Central Kalimantan show that the current implementation of the forest moratorium policy is not effective in reducing forest conversion and carbon emissions. This is because companies continue to invest in converting secondary forest on mineral soils and the moratorium does not affect community decision-making. A policy that combines a forest moratorium with livelihood support and increases farm-gate prices of forest and agroforestry products could increase the local communities' benefits from conservation. Forest and agroforestry areas that are profitable and competitive are more likely to be conserved and reduce potential carbon emission by about 36 %. The results for the two districts, with different pressures on local resources, suggest that appropriate additional measures require local fine-tuning. The LUCES model could be an ex ante tool to facilitate such fine-tuning and help the Indonesian government achieve its INDC goals as part of a wider sustainable development policy.

International climate negotiations have stressed the importance of considering emissions from forest degradation under the planned REDD+ (Reducing Emissions from Deforestation and forest Degradation + enhancing forest carbon stocks) mechanism. However, most research, pilot-REDD+ projects and carbon certification agencies have focused on deforestation and there appears to be a gap in knowledge on complex mosaic landscapes containing degraded forests, smallholder agriculture, agroforestry and plantations. In this paper we therefore review current research on how avoided forest degradation may affect emissions of greenhouse gases (GHG) and expected co-benefits in terms of biodiversity and livelihoods. There are still high uncertainties in measuring and monitoring emissions of carbon and other GHG from mosaic landscapes with forest degradation since most research has focused on binary analyses of forest vs. deforested land. Studies on the impacts of forest degradation on biodiversity contain mixed results and there is little empirical evidence on the influence of REDD+ on local livelihoods and tenure security, partly due to the lack of actual payment schemes. Governance structures are also more complex in landscapes with degraded forests as there are often multiple owners and types of rights to land and trees. Recent technological advances in remote sensing have improved estimation of carbon stock changes but establishment of historic reference levels is still challenged by the availability of sensor systems and ground measurements during the reference period. The inclusion of forest degradation in REDD+ calls for a range of new research efforts to enhance our knowledge of how to assess the impacts of avoided forest degradation. A first step will be to ensure that complex mosaic landscapes can be recognised under REDD+ on their own merits.