Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importanc...Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.展开更多
Background:Assessing functional diversity to identify its spatial patterns and drivers is an important step towards understanding the adaptive capacity of ecosystems to environmental change. However, until now, these ...Background:Assessing functional diversity to identify its spatial patterns and drivers is an important step towards understanding the adaptive capacity of ecosystems to environmental change. However, until now, these mechanisms were poorly understood in the temperate forests of northeastern China, which prevented the development of new management methods aimed at increasing functional trait diversity and thus ecological resilience.Methods:In this study, we mapped functional diversity distributions using a Kriging Interpolation Method. A specific random forest model approach was adopted to test the importance ranking of 18 variables in explaining the spatial variation of functional diversity. Three piecewise structural equation models (pSEMs) with forest types as random effects were constructed for testing the direct effects of climate, and the indirect effects of stand structure on functional diversity across the large study region. Specific causal relationships in each forest type were also examined using 15 linear structural equation models.Results:Although environmental filtering by climate is important, stand structure explains most of the functional variation of the forest ecosystems in northeastern China. Our study thus only partially supports the stressdominance hypothesis. Several abundant species determine most of the functional diversity, which supports the mass ratio hypothesis.Conclusions:Our results suggest that forest management aimed at increasing structural complexity can contribute to increased functional diversity, especially regarding the mixing of coniferous and broad-leaved tree species.展开更多
Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for in...Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for individual forest stands may be fairly poor. An extension of validation efforts to different forest biomes could therefore provide more comprehensive assessment and understanding of the Bitterlich sampling technique. In this study, this technique was quantitatively evaluated by using simulated sparse boreal forests and dense tropical forests from an empirical forest structure model (EFSM). Theoretical estimation of basal areas and practical estimation influenced by the hidden-tree effect were both compared with true basal areas of the simulated forests. The evaluation results indicated that: 1) Bitterlich sampling can yield acceptable accuracy and precision when the count number (CN) of trees was set to 10 for the studied boreal and tropical forests with distinct characteristics, 2) the theoretical estimation of basal area can be improved by increasing the CN values for both forests, and 3) when the hidden-tree effect is encountered, the accuracy for tropical forests will be decreased by increasing the CN values, whereas the accuracy for boreal forests can still be improved. Accordingly, a relatively high CN, at a reasonable cost, is recommended for sparse boreal forests to improve the accuracy of basal area estimation. In contrast, for dense tropical forests, a CN of ten is appropriate to mitigate the hidden-tree effect.展开更多
According to the unification principle of system structure and system function of the Water Resource Conservation Forests,seven factors were selected from stand spatial structure,trees structure and healthy of woods,t...According to the unification principle of system structure and system function of the Water Resource Conservation Forests,seven factors were selected from stand spatial structure,trees structure and healthy of woods,the multifunction management optimization model target was confirmed by using nonlinearity multi-objective programming approach, and the target function-stand spatial structure homogeneity index was defined to establish spatial optimization models with restraining conditions set up in diversity of stand structure and spatial structure.The spatial structure of available typical stand in the wet land area in southern Donting Lake was optimized by means of selective cutting and reinforcement planting.The results showed that the spatial structure was improved obviously and trees diversity and stand health were not weakened.It’s suggested that the established optimization model can effectively guide multifunction management,stand structure optimization and the steadiness of ecological ecosystem and it is convenient and operable in practice,and it’s very important to protect and recover ecosystem of Water Resource Conservation Forests.展开更多
基金financially supported by the Innovation Foundation for Doctoral Program of Forestry Engineering of Northeast Forestry University,grant number:LYGC202117the China Scholarship Council(CSC),grant number:202306600046+1 种基金the Research and Development Plan of Applied Technology in Heilongjiang Province of China,grant number:GA19C006Research and Demonstration on Functional Improvement Technology of Forest Ecological Security Barrier in Heilongjiang Province,grant number:GA21C030。
文摘Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.
基金supported by the Program of National Natural Science Foundation of China (No. 31971650)the Key Project of National Key Research and Development Plan (No. 2017YFC0504104)Beijing Forestry University Outstanding Young Talent Cultivation Project(No. 2019JQ03001)
文摘Background:Assessing functional diversity to identify its spatial patterns and drivers is an important step towards understanding the adaptive capacity of ecosystems to environmental change. However, until now, these mechanisms were poorly understood in the temperate forests of northeastern China, which prevented the development of new management methods aimed at increasing functional trait diversity and thus ecological resilience.Methods:In this study, we mapped functional diversity distributions using a Kriging Interpolation Method. A specific random forest model approach was adopted to test the importance ranking of 18 variables in explaining the spatial variation of functional diversity. Three piecewise structural equation models (pSEMs) with forest types as random effects were constructed for testing the direct effects of climate, and the indirect effects of stand structure on functional diversity across the large study region. Specific causal relationships in each forest type were also examined using 15 linear structural equation models.Results:Although environmental filtering by climate is important, stand structure explains most of the functional variation of the forest ecosystems in northeastern China. Our study thus only partially supports the stressdominance hypothesis. Several abundant species determine most of the functional diversity, which supports the mass ratio hypothesis.Conclusions:Our results suggest that forest management aimed at increasing structural complexity can contribute to increased functional diversity, especially regarding the mixing of coniferous and broad-leaved tree species.
文摘Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for individual forest stands may be fairly poor. An extension of validation efforts to different forest biomes could therefore provide more comprehensive assessment and understanding of the Bitterlich sampling technique. In this study, this technique was quantitatively evaluated by using simulated sparse boreal forests and dense tropical forests from an empirical forest structure model (EFSM). Theoretical estimation of basal areas and practical estimation influenced by the hidden-tree effect were both compared with true basal areas of the simulated forests. The evaluation results indicated that: 1) Bitterlich sampling can yield acceptable accuracy and precision when the count number (CN) of trees was set to 10 for the studied boreal and tropical forests with distinct characteristics, 2) the theoretical estimation of basal area can be improved by increasing the CN values for both forests, and 3) when the hidden-tree effect is encountered, the accuracy for tropical forests will be decreased by increasing the CN values, whereas the accuracy for boreal forests can still be improved. Accordingly, a relatively high CN, at a reasonable cost, is recommended for sparse boreal forests to improve the accuracy of basal area estimation. In contrast, for dense tropical forests, a CN of ten is appropriate to mitigate the hidden-tree effect.
文摘According to the unification principle of system structure and system function of the Water Resource Conservation Forests,seven factors were selected from stand spatial structure,trees structure and healthy of woods,the multifunction management optimization model target was confirmed by using nonlinearity multi-objective programming approach, and the target function-stand spatial structure homogeneity index was defined to establish spatial optimization models with restraining conditions set up in diversity of stand structure and spatial structure.The spatial structure of available typical stand in the wet land area in southern Donting Lake was optimized by means of selective cutting and reinforcement planting.The results showed that the spatial structure was improved obviously and trees diversity and stand health were not weakened.It’s suggested that the established optimization model can effectively guide multifunction management,stand structure optimization and the steadiness of ecological ecosystem and it is convenient and operable in practice,and it’s very important to protect and recover ecosystem of Water Resource Conservation Forests.
