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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2019

Abstract

Global Forest Watch (GFW) provides a global map of annual forest cover loss (FCL) produced from Landsat imagery, offering a potentially powerful tool for monitoring changes in forest cover. In managed forests, FCL primarily provides information on commercial harvesting. A semi-autonomous method for providing data on the location and attributes of harvested sites at a landscape level was developed which could significantly improve the basis for catchment management, including risk mitigation. FCL in combination with aerial images was used for detecting and characterising harvested sites in a 1607 km2 mountainous boreal forest catchment in south-central Norway. Firstly, the forest cover loss map was enhanced (FCLE) by removing small isolated forest cover loss patches that had a high probability of representing commission errors. The FCLE map was then used to locate and assess sites representing annual harvesting activity over a 17-year period. Despite an overall accuracy of >98%, a kappa of 0.66 suggested only a moderate quality for detecting harvested sites. While errors of commission were negligible, errors of omission were more considerable and at least partially attributed to the presence of residual seed trees on the site after harvesting. The systematic analysis of harvested sites against aerial images showed a detection rate of 94%, but the area of the individual harvested site was underestimated by 29% on average. None of the site attributes tested, including slope, area, altitude, or site shape index, had any effect on the accuracy of the area estimate. The annual harvest estimate was 0.6% (standard error 12%) of the productive forest area. On average, 96% of the harvest was carried out on flat to moderately steep terrain (<40% slope), 3% on steep terrain (40% to 60% slope), and 1% on very steep terrain (>60% slope). The mean area of FCLE within each slope category was 1.7 ha, 0.9 ha, and 0.5 ha, respectively. The mean FCLE area increased from 1.0 ha to 3.2 ha on flat to moderate terrain over the studied period, while the frequency of harvesting increased from 249 to 495 sites per year. On the steep terrain, 35% of the harvesting was done with cable yarding, and 62% with harvester-forwarder systems. On the very steep terrain (>60% slope), 88% of the area was harvested using cable yarding technology while harvesters and forwarders were used on 12% of the area. Overall, FCL proved to be a useful dataset for the purpose of assessing harvesting activity under the given conditions.

Abstract

In the past decade, China imported massive quantities of soybean from the international market to meet its increasing domestic demand for protein[1]. However, China’s soybean imports from US decreased from 32.86 Mt (Million tons, 34% of the total 95.54 Mt) in 2017 to 16.64 Mt (19% of the total 88.03 Mt) in 2018[2] due to the China-US trade war. To reduce China’s reliance on imports, the Chinese government has been making policy incentive, e.g. higher subsidies, to encourage farmers for soybean cultivation. Traditionally Northeast China is the key production area for soybean. Soybean cultivation is tightly linked to the regional climate and environment. On the one hand, the local soybean growth is vulnerable[3] to the frequent meteorological hazards (e.g. droughts, floods) in the Northeast China[4]. The meteorological risks for soybean production in this area still remain unknown. On the other hand, albeit with relatively high production cost[5] and low water use efficiency[6], the local soybean cultivation is expected to effectively improve the nitrogen use efficiency and therefore alleviate the growing environment pollutions in this region[7]. Yet so far there are few quantitative research being reported on this environmental issue. Our research aims to explore both the meteorological risks and environmental costs of the policy-driven soybean expansion. We have developed a new version of the soybean growth algorithms within the DNDC (DeNitrification-DeComposition) model including nitrogen biogeochemical processes and performed regional simulations for soybean-related cropping systems in Northeast China. We will present the following results by combining model outputs and observations: (i) potential yield and the meteorological risks of soybean cultivation; (ii) fertilizer reduction in different crop rotation systems and the corresponding benefits to water ecosystem; and (iii) consequences of different policy scenarios (e.g. change in subsidy, GMO permission) to soybean production and environment.

To document See dataset

Abstract

Coastal erosion is an issue of major concern for coastal managers and is expected to increase in magnitude and severity due to global climate change. This paper analyzes the potential consequences of climate change on coastal erosion (e.g., impacts on beaches, wetlands and protected areas) by applying a Regional Risk Assessment (RRA) methodology to the North Adriatic (NA) coast of Italy. The approach employs hazard scenarios from a multi-model chain in order to project the spatial and temporal patterns of relevant coastal erosion stressors (i.e., increases in mean sea-level, changes in wave height and variations in the sediment mobility at the sea bottom) under the A1B climate change scenario. Site-specific environmental and socio-economic indicators (e.g., vegetation cover, geomorphology, population) and hazard metrics are then aggregated by means of Multi-Criteria Decision Analysis (MCDA) with the aim to provide an example of exposure, susceptibility, risk and damage maps for the NA region. Among seasonal exposure maps winter and autumn depict the worse situation in 2070–2100, and locally around the Po river delta. Risk maps highlight that the receptors at higher risk are beaches, wetlands and river mouths. The work presents the results of the RRA tested in the NA region, discussing how spatial risk mapping can be used to establish relative priorities for intervention, to identify hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies.

To document

Abstract

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