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Altitudinal forest limits are typically climatically dependent, such that increasing temperatures connected to global warming are causing upslope shifts in treeline ecotones worldwide. However, at the local and regional levels, the degree of such a response is dependent on differences in climate, topography and soil features. In recent decades, attempts have been undertaken to estimate tree stand dynamics with remote sensing methods, but their resolution is still too coarse for a precise assessment of stand structural changes, and requires ground-truthing, which is not possible without historical data collected on a single-tree level. We used aerial photos (1962) and satellite images (2021) in combination with historical inventory data to investigate changes in open forest positions at different spatial scales at the eastern macroslope of the Polar Urals over the past 60 years. Additionally, obtained remote sensing data were validated on a single-slope level using tree crown size estimations. Our investigations showed that since 1960 up to present day, the total crown coverage increased from 6.9 to 22.1% within the test polygon. A highly spatially variable upslope advance in an open forest boundary was identified from 1.7 up to 7.1 m in altitude per decade. We revealed that the rate of tree stand transformations was to a great extent depended on the stand density in the 1960s, soil substrate type, moisture regime, slope aspect and inclination. Our results highlighted the necessity to consider the abovementioned factors when trying to predict climate-induced tree distributional responses in subarctic mountain regions.

Altitudinal forest limits are typically climatically dependent, such that increasing temperatures connected to global warming are causing upslope shifts in treeline ecotones worldwide. However, at the local and regional levels, the degree of such a response is dependent on differences in climate, topography and soil features. In recent decades, attempts have been undertaken to estimate tree stand dynamics with remote sensing methods, but their resolution is still too coarse for a precise assessment of stand structural changes, and requires ground-truthing, which is not possible without historical data collected on a single-tree level. We used aerial photos (1962) and satellite images (2021) in combination with historical inventory data to investigate changes in open forest positions at different spatial scales at the eastern macroslope of the Polar Urals over the past 60 years. Additionally, obtained remote sensing data were validated on a single-slope level using tree crown size estimations. Our investigations showed that since 1960 up to present day, the total crown coverage increased from 6.9 to 22.1% within the test polygon. A highly spatially variable upslope advance in an open forest boundary was identified from 1.7 up to 7.1 m in altitude per decade. We revealed that the rate of tree stand transformations was to a great extent depended on the stand density in the 1960s, soil substrate type, moisture regime, slope aspect and inclination. Our results highlighted the necessity to consider the abovementioned factors when trying to predict climate-induced tree distributional responses in subarctic mountain regions.

The Limpopo estuary mangrove forest covers about 928 ha, however 382 ha remain intact and 546 ha were degraded after the 2000 floods. Mangrove replanting campaigns have been carried out at the site. This article aims to evaluate the structure and carbon pool of aboveground and belowground living biomass and soil carbon in natural and replanted mangrove forests (2016, 2014 and 2010). The methodology consisted of selecting 40 strata where structural data were collected. Living biomass above and below ground and soil carbon was obtained based on the methodology described by Kauffman and Donato (2012). The results showed that A. marina was the most observed species in all study areas. The carbon reserve of living biomass above and below ground in the natural forest was 67.9±100.9 MgCha -1 and 65.0±77.1MgC ha -1 , respectively; and in the planted forests (2016, 2014, 2010) it was 1.1±0.5MgCha-1 and 2.1±1.0MgCha-1, 1.8±1.0MgCha-1 and 3.6±2.0MgCha-1, 3.7±2.0MgCha-1 and 5.3±2.5MgCha-1 . Soil carbon reserve was 229.4±119.4 MgCha-1 in natural forest and 230.3±134.8 MgCha-1 , 234.8±132.7MgC ha-1, 229.4±119.4 MgCha-1 in planted forests (2016, 2014, 2010). The total carbon reserve in the natural forest was 362.3 MgCha-1 and in the planted forestsn(2016, 2014, 2010) it was 233.5 MgCha-1 , 240.2 MgCha-1, 246.4 MgCha-1. Natural and restored forests had similar anoumts of soil carbon, which reinforces the idea that soil is a stabel carbon pool. Morever, restored forests failed to store the same amount of live biomass (an carbon), which supports the idea that it is better to prevent habitat degradation than to restore it.

The Limpopo estuary mangrove forest covers about 928 ha, however 382 ha remain intact and 546 ha were degraded after the 2000 floods. Mangrove replanting campaigns have been carried out at the site. This article aims to evaluate the structure and carbon pool of aboveground and belowground living biomass and soil carbon in natural and replanted mangrove forests (2016, 2014 and 2010). The methodology consisted of selecting 40 strata where structural data were collected. Living biomass above and below ground and soil carbon was obtained based on the methodology described by Kauffman and Donato (2012). The results showed that A. marina was the most observed species in all study areas. The carbon reserve of living biomass above and below ground in the natural forest was 67.9±100.9 MgCha -1 and 65.0±77.1MgC ha -1 , respectively; and in the planted forests (2016, 2014, 2010) it was 1.1±0.5MgCha-1 and 2.1±1.0MgCha-1, 1.8±1.0MgCha-1 and 3.6±2.0MgCha-1, 3.7±2.0MgCha-1 and 5.3±2.5MgCha-1 . Soil carbon reserve was 229.4±119.4 MgCha-1 in natural forest and 230.3±134.8 MgCha-1 , 234.8±132.7MgC ha-1, 229.4±119.4 MgCha-1 in planted forests (2016, 2014, 2010). The total carbon reserve in the natural forest was 362.3 MgCha-1 and in the planted forestsn(2016, 2014, 2010) it was 233.5 MgCha-1 , 240.2 MgCha-1, 246.4 MgCha-1. Natural and restored forests had similar anoumts of soil carbon, which reinforces the idea that soil is a stabel carbon pool. Morever, restored forests failed to store the same amount of live biomass (an carbon), which supports the idea that it is better to prevent habitat degradation than to restore it.

Ongoing climate change and human activities have a great effect on vegetation dynamics. Understanding the impact of climate change and human activities on vegetation dynamics in different ecologically vulnerable regions has great significance in ecosystem management. In this study, the predicted NPP (Net Primary Productivity) and the actual NPP based on different ecological process data and models were combined to estimate the vegetation dynamics and their driving forces in the Northern Wind-sand, Loess Plateau, Arid Desert, Tibetan Plateau, and Karst regions from 2000 to 2015. The results indicated that the NPP in all ecologically vulnerable regions showed a restoration trend, except for that in the Karst region, and the percentage of areas in which NPP increased were, in order, 78% for the Loess Plateau, 71% for the Northern Wind-sand, 69% for the Arid Desert, 54% for the Tibetan Plateau, and 31% for the Karst regions. Vegetation restorations in the Northern Wind-sand and Arid Desert regions were primarily attributable to human activities (86% and 61% of the restoration area, respectively), indicating the success of ecological restoration programs. The Loess Plateau had the largest proportion of vegetation restoration area (44%), which was driven by combined effects of climate and human factors. In the Tibetan Plateau, the vegetation changes due to climate factors were primarily distributed in the west, while those due to human factors were primarily distributed in the east. Human activities caused nearly 60% of the vegetation degradation in the Karst region. Based on these results, it is recognizable that regional climate conditions are the key factor that limits ecological restoration. Therefore, future policy-making should pay more attention to the local characteristics of different ecological vulnerable regions in regional ecosystem management to select reasonable restoration measures, improve restoration efficiency, and maximize the benefits of ecological restoration programs.

Ongoing climate change and human activities have a great effect on vegetation dynamics. Understanding the impact of climate change and human activities on vegetation dynamics in different ecologically vulnerable regions has great significance in ecosystem management. In this study, the predicted NPP (Net Primary Productivity) and the actual NPP based on different ecological process data and models were combined to estimate the vegetation dynamics and their driving forces in the Northern Wind-sand, Loess Plateau, Arid Desert, Tibetan Plateau, and Karst regions from 2000 to 2015. The results indicated that the NPP in all ecologically vulnerable regions showed a restoration trend, except for that in the Karst region, and the percentage of areas in which NPP increased were, in order, 78% for the Loess Plateau, 71% for the Northern Wind-sand, 69% for the Arid Desert, 54% for the Tibetan Plateau, and 31% for the Karst regions. Vegetation restorations in the Northern Wind-sand and Arid Desert regions were primarily attributable to human activities (86% and 61% of the restoration area, respectively), indicating the success of ecological restoration programs. The Loess Plateau had the largest proportion of vegetation restoration area (44%), which was driven by combined effects of climate and human factors. In the Tibetan Plateau, the vegetation changes due to climate factors were primarily distributed in the west, while those due to human factors were primarily distributed in the east. Human activities caused nearly 60% of the vegetation degradation in the Karst region. Based on these results, it is recognizable that regional climate conditions are the key factor that limits ecological restoration. Therefore, future policy-making should pay more attention to the local characteristics of different ecological vulnerable regions in regional ecosystem management to select reasonable restoration measures, improve restoration efficiency, and maximize the benefits of ecological restoration programs.

In this study, we assessed the impacts of climate change on the production of pulpwood and biomass for bioenergy, and the profitability of slash pine stands in the Southeastern United States. We employed the 3-PG (Physiological Processes Predicting Growth) model to determine the effects of future climates on forest growth and integrated it with a stand-level economic model to determine their impacts on optimal forest management. We found that the average production of pulpwood increased for all sites by 7.5 m3 ha−1 for all climatic scenarios and productivity conditions. In the case of forest biomass for bioenergy, the average increase was less than 1 Mg ha−1. Considering a payment for forest biomass for bioenergy of $4.2 per green Mg−1, the land expectation values (LEVs), on average, increased by $242.1 ha−1 under extreme climatic conditions and high productivity conditions. However, the increase in LEVs due to payments for biomass for bioenergy was small, accounting for $23 ha−1. We also found that the combined effect of increased site productivity and climate change reduced the optimal harvest age of slash pine. Our results confirm that emerging bioenergy markets coupled with changing climatic conditions can increase the economic returns for landowners.

In this study, we assessed the impacts of climate change on the production of pulpwood and biomass for bioenergy, and the profitability of slash pine stands in the Southeastern United States. We employed the 3-PG (Physiological Processes Predicting Growth) model to determine the effects of future climates on forest growth and integrated it with a stand-level economic model to determine their impacts on optimal forest management. We found that the average production of pulpwood increased for all sites by 7.5 m3 ha−1 for all climatic scenarios and productivity conditions. In the case of forest biomass for bioenergy, the average increase was less than 1 Mg ha−1. Considering a payment for forest biomass for bioenergy of $4.2 per green Mg−1, the land expectation values (LEVs), on average, increased by $242.1 ha−1 under extreme climatic conditions and high productivity conditions. However, the increase in LEVs due to payments for biomass for bioenergy was small, accounting for $23 ha−1. We also found that the combined effect of increased site productivity and climate change reduced the optimal harvest age of slash pine. Our results confirm that emerging bioenergy markets coupled with changing climatic conditions can increase the economic returns for landowners.