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Productivity of coniferous forests evaluated by remote sensing and field-based models
The inadequacy of Norway spruce (NS) monocultures in fulfilling ecosystem services, due to deteriorating health and consequent forest ecosystem collapses, has recently become a concerning issue for the forestry sector in Central Europe. This study investigates spruce forest productivity using in-situ field observations (DendroNetwork) and satellite remote sensing (RS) data in the Czech Republic during the past two decades. Tree growth index and moderate resolution imaging spectroradiometer net primary productivity were used to assess productivity at the national scale along an elevation gradient. The analyses of spatiotemporal variation in carbon dynamics indicate a decreasing trend in productivity in 51% and 80% (2800 km ^2 and 4200 km ^2 ) of the spruce stands from the RS and in-situ data, respectively. The increasing trend is particularly evident in montane regions, where satellite data identified an elevation threshold around 900 m a.s.l. while in-situ data 700 m a.s.l. In these energy-limited montane areas, NS may benefit from increased temperatures and may remain relatively safe from drought stress. The decreasing trends detected by both approaches indicate deteriorating conditions for NS in lower elevations. This study suggests that combining in-situ and RS data provides an efficient and robust way to estimate forest productivity at the national scale. The anticipated response of spruce forests associated with declines in productivity and growth in areas with low to moderate elevation points to the adverse effects of climate change by shifting the ecological optimum to higher elevations. We conclude that detailed mapping of forest response to changing environmental conditions is critical to support sustainable forest management and decision-making, ultimately reflecting the need to adopt adequate strategies to mitigate the impacts of climate change and related natural and anthropogenic disturbances.
Productivity of coniferous forests evaluated by remote sensing and field-based models
The inadequacy of Norway spruce (NS) monocultures in fulfilling ecosystem services, due to deteriorating health and consequent forest ecosystem collapses, has recently become a concerning issue for the forestry sector in Central Europe. This study investigates spruce forest productivity using in-situ field observations (DendroNetwork) and satellite remote sensing (RS) data in the Czech Republic during the past two decades. Tree growth index and moderate resolution imaging spectroradiometer net primary productivity were used to assess productivity at the national scale along an elevation gradient. The analyses of spatiotemporal variation in carbon dynamics indicate a decreasing trend in productivity in 51% and 80% (2800 km ^2 and 4200 km ^2 ) of the spruce stands from the RS and in-situ data, respectively. The increasing trend is particularly evident in montane regions, where satellite data identified an elevation threshold around 900 m a.s.l. while in-situ data 700 m a.s.l. In these energy-limited montane areas, NS may benefit from increased temperatures and may remain relatively safe from drought stress. The decreasing trends detected by both approaches indicate deteriorating conditions for NS in lower elevations. This study suggests that combining in-situ and RS data provides an efficient and robust way to estimate forest productivity at the national scale. The anticipated response of spruce forests associated with declines in productivity and growth in areas with low to moderate elevation points to the adverse effects of climate change by shifting the ecological optimum to higher elevations. We conclude that detailed mapping of forest response to changing environmental conditions is critical to support sustainable forest management and decision-making, ultimately reflecting the need to adopt adequate strategies to mitigate the impacts of climate change and related natural and anthropogenic disturbances.
Productivity of coniferous forests evaluated by remote sensing and field-based models
A Kusbach jun (author) / J Krejza (author) / L Homolová (author) / M Fischer (author) / R Janoutová (author) / P Horáček (author)
2025
Article (Journal)
Electronic Resource
Unknown
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