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Human activity has greatly reduced the area of old-growth forest in Europe, with some of the largest remaining fragments in the Carpathian Mountains of south-western Ukraine. We used satellite image analysis to calculate old-growth forest disturbance in this region from 2010 to 2019. Over this period, we identified 1335 ha of disturbance in old-growth forest, equivalent to 1.8% of old-growth forest in the region. During 2015 to 2019, the average annual disturbance rate was 0.34%, varying with altitude, distance to settlements and location within the region. Disturbance rates were 7&ndash, 8 times lower in protected areas compared to outside of protected areas. Only one third of old-growth forest is currently within protected areas, expansion of the protected area system to include more old-growth forests would reduce future loss. A 2017 law that gave protection to all old-growth forest in Ukraine had no significant impact on disturbance rates in 2018, but in 2019 disturbance rates reduced to 0.19%. Our analysis is the first indication that this new legislation may be reducing loss of old-growth forest in Ukraine.

Understanding forest loss patterns in Amazonia, the Earth’s largest rainforest region, is critical for effective forest conservation and management. Following the most detailed analysis to date, spanning the entire Amazon and extending over a 14-year period (2001–2014), we reveal significant shifts in deforestation dynamics of Amazonian forests. Firstly, hotspots of Amazonian forest loss are moving away from the southern Brazilian Amazon to Peru and Bolivia. Secondly, while the number of new large forest clearings (>50 ha) has declined significantly over time (46%), the number of new small clearings (

Old-growth forests are an important, rare and endangered habitat in Europe. The ability to identify old-growth forests through remote sensing would be helpful for both conservation and forest management. We used data on beech, Norway spruce and mountain pine old-growth forests in the Ukrainian Carpathians to test whether Sentinel-2 satellite images could be used to correctly identify these forests. We used summer and autumn 2017 Sentinel-2 satellite images comprising 10 and 20 m resolution bands to create 6 vegetation indices and 9 textural features. We used a Random Forest classification model to discriminate between dominant tree species within old-growth forests and between old-growth and other forest types. Beech and Norway spruce were identified with an overall accuracy of around 90%, with a lower performance for mountain pine (70%) and mixed forest (40%). Old-growth forests were identified with an overall classification accuracy of 85%. Adding textural features, band standard deviations and elevation data improved accuracies by 3.3%, 2.1% and 1.8% respectively, while using combined summer and autumn images increased accuracy by 1.2%. We conclude that Random Forest classification combined with Sentinel-2 images can provide an effective option for identifying old-growth forests in Europe.

In upland areas of Great Britain, large tracts of non-native conifer plantations have been established on poor quality agricultural land. There is now considerable interest in the conversion of some of these plantations to a more natural woodland comprised of native tree species. We studied the tree regeneration and ground flora on 15 upland sites (altitudes ranging from 120 m to 380 m above sea level) that had been clearfelled of conifers. Regeneration of native tree species was successful where a clearcut site was adjacent to mature native trees, which acted as a seed source. Mean regeneration densities of native tree species on clearcut sites were typically greater than 1000 stems/ha, exceeding minimum recommended planting densities for the establishment of new native woodland. Whilst 10 native woody tree species were recorded, the regeneration was dominated by birch species. Regeneration densities were significantly higher on clearcut sites than on adjacent areas of unplanted moorland, probably due to the lack of a dense ground flora following the clearfelling operations. Our results indicate that where local native seed sources exist, clearfelling upland conifer plantation sites to allow natural regeneration has the potential to be an effective method of establishing native woodland.

Protected areas (PAs) have been established to conserve tropical forests, but their effectiveness at reducing deforestation is uncertain. To explore this issue, we combined high resolution data of global forest loss over the period 2000-2012 with data on PAs. For each PA we quantified forest loss within the PA, in buffer zones 1, 5, 10 and 15 km outside the PA boundary as well as a 1 km buffer within the PA boundary. We analysed 3376 tropical and subtropical moist forest PAs in 56 countries over 4 continents. We found that 73% of PAs experienced substantial deforestation pressure, with >0.1% a-1 forest loss in the outer 1 km buffer. Forest loss within PAs was greatest in Asia (0.25% a-1) compared to Africa (0.1% a-1), the Neotropics (0.1% a-1) and Australasia (Australia and Papua New Guinea; 0.03% a-1). We defined performance (P) of a PA as the ratio of forest loss in the inner 1 km buffer compared to the loss that would have occurred in the absence of the PA, calculated as the loss in the outer 1 km buffer corrected for any difference in deforestation pressure between the two buffers. To remove the potential bias due to terrain, we analysed a subset of PAs (n = 1804) where slope and elevation in inner and outer 1 km buffers were similar (within 1° and 100 m, respectively). We found 41% of PAs in this subset reduced forest loss in the inner buffer by at least 25% compared to the expected inner buffer forest loss (P

Natural forests in Vietnam have experienced rapid declines in the last 70 years, as a result of degradation from logging and conversion of natural forests to timber and rubber plantations. Degradation of natural forests leads to loss of biodiversity and ecosystem services, impacting the livelihoods of surrounding communities. Efforts to address ongoing loss of natural forests, through mechanisms such as Reduced Emissions from Deforestation and Degradation (REDD+), require an understanding of the links between forest degradation and the livelihoods of local communities, which have rarely been studied in Vietnam. We combined information from livelihood surveys, remote sensing and forest inventories around a protected natural forest area in North Central Vietnam. For forest-adjacent communities, we found natural forests contributed an average of 28% of total household income with plantation forests contributing an additional 15%. Although officially prohibited, logging contributed more than half of the total income derived from natural forests. Analysis of Landsat images over the period 1990 to 2014 combined with forest inventory data, demonstrates selective logging was leading to ongoing degradation of natural forests resulting in loss of 3.3 ± 0.8 Mg biomass ha−1 yr−1 across the protected area. This is equivalent to 1.5% yr−1 of total forest biomass, with rates as high as 3% yr−1 in degraded and easily accessible parts of the protected area. We estimate that preventing illegal logging would incur local opportunity costs of USD $4.10 ± 0.90 per Mg CO2, similar to previous estimates for tropical forest protected areas and substantially less than the opportunity costs in timber or agricultural concessions. Our analysis suggests activities to reduce forest degradation in protected areas are likely to be financially viable through Vietnam’s REDD+ program.