Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have becom...Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have become major challenges in forestry research.In this study,we selected the Shaanxi-Gansu-Ningxia region of Northeast China as the research area and utilized multi-source datasets from the summer of 2019 to extract information on spectral,textural,climatic,water balance,and stand characteristics.By integrating the Random Forest(RF)model with Monte Carlo(MC)simulation,we constructed six regression models based on different combina-tions of features and evaluated the uncertainty of each model.Furthermore,we investigated the driving factors influencing stand age modeling by analyzing the effects of different types of features on age inversion.Model performance and accuracy were assessed using the root mean square error(RMSE),mean absolute error(MAE),and the coefficient of determination(R^(2)),while the relative root mean square error(rRMSE)was employed to quantify model uncertainty.The results indicate that the scenarios with more obvious improve-ment in accuracy and effective reduction in uncertainty were Scenario 3 with the inclusion of climate and water balance information(RMSE=25.54 yr,MAE=18.03 yr,R^(2)=0.51,rRMSE=19.17%)and Scenario 5 with the inclusion of stand characterization informa-tion(RMSE=18.47 yr,MAE=13.05 yr,R^(2)=0.74,rRMSE=16.99%).Scenario 6,incorporating all feature types,achieved the highest accuracy(RMSE=17.60 yr,MAE=12.06 yr,R^(2)=0.77,rRMSE=14.19%).In this study,elevation,minimum temperature,and diameter at breast height(DBH)emerged as the key drivers of stand-age modeling.The proposed method can be used to identify drivers and to quantify uncertainty in stand-age estimation,providing a useful reference for improving model accuracy and uncertainty assessment.展开更多
Evaluation of water richness in sandstone is an important research topic in the prevention and control of mine water disasters,and the water richness in sandstone is closely related to its porosity.The refl ection sei...Evaluation of water richness in sandstone is an important research topic in the prevention and control of mine water disasters,and the water richness in sandstone is closely related to its porosity.The refl ection seismic exploration data have high-density spatial sampling information,which provides an important data basis for the prediction of sandstone porosity in coal seam roofs by using refl ection seismic data.First,the basic principles of the variational mode decomposition(VMD)method and the random forest method are introduced.Then,the geological model of coal seam roof sandstone is constructed,seismic forward modeling is conducted,and random noise is added.The decomposition eff ects of the empirical mode decomposition(EMD)method and VMD method on noisy signals are compared and analyzed.The test results show that the firstorder intrinsic mode functions(IMF1)and IMF2 decomposed by the VMD method contain the main eff ective components of seismic signals.A prediction process of sandstone porosity in coal seam roofs based on the combination of VMD and random forest method is proposed.The feasibility and eff ectiveness of the method are verified by trial calculation in the porosity prediction of model data.Taking the actual coalfield refl ection seismic data as an example,the sandstone porosity of the 8 coal seam roof is predicted.The application results show the potential application value of the new porosity prediction method proposed in this study.This method has important theoretical guiding significance for evaluating water richness in coal seam roof sandstone and the prevention and control of mine water disasters.展开更多
Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range ...Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.展开更多
One of the basic parameters in forest management planning is detailed knowledge of growing stock,information collected by forest inventory.Sampling methods must be accurate,inexpensive,and be easy to implement in the ...One of the basic parameters in forest management planning is detailed knowledge of growing stock,information collected by forest inventory.Sampling methods must be accurate,inexpensive,and be easy to implement in the field.This study presents a new sampling method called branching transect for use in the Iranian Zagros forests and similar forests.Features of the new method include greater accuracy,easy implementation in nature,simplicity of statistical calculations,and low cost.In this method,transect is used,which includes some subtransects(side branches).The length of the main transect,side branches,number of trees measured in each side branch,and the number of sub-branches in this method are changeable based on homogeneity,heterogeneity,and density of a forest.In this study,based on the density and heterogeneity of the forest area studied,20-m transects with four and eight side branches were used.Sampling plots(Transects)in four inventory networks(100 m×100 m,100 m×150 m,150 m×150 m and 100 m×200 m)were implemented in the GIS environment.The results of this sampling method were compared to the results of total inventory(100%count)in terms of accuracy,precision(t-test),and inventory error percentage.Branching transect results were statistially similar to total inventory counts in all cases.The results show that this method of estimating density and canopy per hectare can be used in Zagros forests and similar forests.展开更多
To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based...To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.展开更多
Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random samp...Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random sampling(SRS)and LPM with geographical coordinates has produced promising results in simulation studies.In this simulation study we compared all these sampling methods to systematic sampling.The LPM samples were selected solely using the coordinates(LPMxy)or,in addition to that,auxiliary remote sensing-based forest variables(RS variables).We utilized field measurement data(NFI-field)and Multi-Source NFI(MS-NFI)maps as target data,and independent MS-NFI maps as auxiliary data.The designs were compared using relative efficiency(RE);a ratio of mean squared errors of the reference sampling design against the studied design.Applying a method in NFI also requires a proven estimator for the variance.Therefore,three different variance estimators were evaluated against the empirical variance of replications:1)an estimator corresponding to SRS;2)a Grafström-Schelin estimator repurposed for LPM;and 3)a Matérn estimator applied in the Finnish NFI for systematic sampling design.Results:The LPMxy was nearly comparable with the systematic design for the most target variables.The REs of the LPM designs utilizing auxiliary data compared to the systematic design varied between 0.74–1.18,according to the studied target variable.The SRS estimator for variance was expectedly the most biased and conservative estimator.Similarly,the Grafström-Schelin estimator gave overestimates in the case of LPMxy.When the RS variables were utilized as auxiliary data,the Grafström-Schelin estimates tended to underestimate the empirical variance.In systematic sampling the Matérn and Grafström-Schelin estimators performed for practical purposes equally.Conclusions:LPM optimized for a specific variable tended to be more efficient than systematic sampling,but all of the considered LPM designs were less efficient than the systematic sampling design for some target variables.The Grafström-Schelin estimator could be used as such with LPMxy or instead of the Matérn estimator in systematic sampling.Further studies of the variance estimators are needed if other auxiliary variables are to be used in LPM.展开更多
In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance ...In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.展开更多
Ideal point method is one of the methods to solve multi-objective problem. It is applied to forest harvest regu-lation, and showed very good results by analyzing changes of quantitative indexes of forest resource stru...Ideal point method is one of the methods to solve multi-objective problem. It is applied to forest harvest regu-lation, and showed very good results by analyzing changes of quantitative indexes of forest resource structure before andafter the regulation. This method can be applied as one of the mathematical tools in forest harvest regulation.展开更多
Through the survey of National Nature Reserve of Tianmu Mountain,based on relevant data of tourists of Tianmu Mountain over the years,the paper had analyzed some problems about the application of contingent value meth...Through the survey of National Nature Reserve of Tianmu Mountain,based on relevant data of tourists of Tianmu Mountain over the years,the paper had analyzed some problems about the application of contingent value method(CVM) in forest recreational value evaluation.Then,it had evaluated the forest recreational value of National Nature Reserve of Tianmu Mountain in 2007 and obtained evaluation results.Through the statistics of tourists' payment targets,it had calculated the payment value of each function of Tianmu Nature Reserve.The functions were appreciating landscape,exercising,visiting historical sites,photographing,scientific research,picnic and camping,and religion ranking in order from higher to lower value.In terms of nonuse value,existence value was slightly higher than option value and heritage value.It could be known from above research that Tianmu Mountain had great tourism development potential.Finally,it had proposed some suggestions for publicity,project setting and artificial landscape construction.展开更多
Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving...Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.展开更多
As China continues to develop its ecological civilization,it is crucial to quantitatively assess the ecological value to understand its potential impact on regional sustainable development.While previous studies have ...As China continues to develop its ecological civilization,it is crucial to quantitatively assess the ecological value to understand its potential impact on regional sustainable development.While previous studies have highlighted the importance of ecological value,they have not fully reflected the value of ecological restoration work or considered social costs and benefits,lacking a people-centered approach.Hence,this study analyzes the essence of ecological value from the perspective of sustainable development.By studying emblematic ecological restoration areas such as the Saihanba Mechanized Forest Farm in Chengde City,it aims to identify the significance of ecological restoration efforts in enhancing regional sustainable development capacity.The results underscore the necessity of comprehensively considering the value chain from ecological construction to ecological output,highlighting the value of ecological restoration in the ecological construction process as well as the well-being of people in the ecological output process.This approach assigns more economic and humanistic attributes to ecological value,thereby better serving the development of ecological restoration areas.展开更多
It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covari...It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covariance between variables is serious, which can lead to a decrease in the model prediction accuracy. In this paper, the standard solutions of nitrate nitrogen(NO_(3)-N) and nitrite nitrogen(NO_(2)-N) were used as the subject to be tested, and the data of the scanned waves and absorbance were obtained by use of spectral detector. The data were processed by noise reduction first and then the random forest(RF) algorithm was adopted to establish the regression relationship between concentration and absorbance. For comparison, partial least squares(PLS) and support vector machine(SVM) algorithm models were also established. For the same given data, the three reverse models can make the projection of the concentration respectively. The experimental results show that the RF algorithm predicts NO_(2)-N concentrations significantly better than the SVM algorithm and PLS algorithm. This proves that the RF algorithm has good prediction ability in spectral water quality detection because of its high model accuracy and better adaptability, which could be a reference for similar research on continuous spectral water quality online detection.展开更多
The exploration of urban underground spaces is of great significance to urban planning,geological disaster prevention,resource exploration and environmental monitoring.However,due to the existing of severe interferenc...The exploration of urban underground spaces is of great significance to urban planning,geological disaster prevention,resource exploration and environmental monitoring.However,due to the existing of severe interferences,conventional seismic methods cannot adapt to the complex urban environment well.Since adopting the single-node data acquisition method and taking the seismic ambient noise as the signal,the microtremor horizontal-to-vertical spectral ratio(HVSR)method can effectively avoid the strong interference problems caused by the complex urban environment,which could obtain information such as S-wave velocity and thickness of underground formations by fitting the microtremor HVSR curve.Nevertheless,HVSR curve inversion is a multi-parameter curve fitting process.And conventional inversion methods can easily converge to the local minimum,which will directly affect the reliability of the inversion results.Thus,the authors propose a HVSR inversion method based on the multimodal forest optimization algorithm,which uses the efficient clustering technique and locates the global optimum quickly.Tests on synthetic data show that the inversion results of the proposed method are consistent with the forward model.Both the adaption and stability to the abnormal layer velocity model are demonstrated.The results of the real field data are also verified by the drilling information.展开更多
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec...The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.展开更多
Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability ...Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability of forests.At the same time,detailed accounts of disturbances and forest responses are not yet well quantified in Asia.This study employed the Breaks For Additive Seasonal and Trend method-an abrupt-change detection method-to analyze the Enhanced Vegetation Index time series in East Asia,South Asia,and Southeast Asia.This approach allowed us to detect forest disturbance and quantify the resilience after disturbance.Results showed that 20%of forests experienced disturbance with an increasing trend from 2000 to 2022,and Southeast Asian countries were more severely affected by disturbances.Specifically,95%of forests had robust resilience and could recover from disturbance within a few decades.The resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance magnitude.In summary,this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two decades.The authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in 2022.The findings of this study underscore the complex relationship between disturbance and resilience,contributing to comprehension of forest resilience through satellite remote sensing.展开更多
The Dahurian larch forest in northeast China is important due to its vastness and location within a transitional zone from boreal to temperate and at the southern distribution edge of the vast Siberian larch forest. T...The Dahurian larch forest in northeast China is important due to its vastness and location within a transitional zone from boreal to temperate and at the southern distribution edge of the vast Siberian larch forest. The continuous carbon fluxes were measured from May 2004 to April 2005 in the Dahurian larch forest in Northeast China using an eddy covariance method. The results showed that the ecosystem released carbon in the dormant season from mid-October 2004 to April 2005, while it assimilated CO2 from the atmosphere in the growing season from May to September 2004. The net carbon sequestration reached its peak of 112 g.m^-2.month ^-1 in June 2004 （simplified expression of g （carbon）.m^-2.month^-1） and then gradually decreased. Annually, the larch forest was a carbon sink that sequestered carbon of 146 g-m^-2.a^-1 （simplified expression of g （carbon）.m^-2.a^-1） during the measurements. The photosynthetic process of the larch forest ecosystem was largely affected by the vapor pressure deficit （VPD） and temperature. Under humid conditions （VPD 〈 1.0 kPa）, the gross ecosystem production （GEP） increased with increasing temperature. But the net ecosystem production （NEP） showed almost no change with increasing temperature because the increment of GEP was counterbalanced by that of the ecosystem respiration. Under a dry environment （VPD 〉 1.0 kPa）, the GEP decreased with the increasing VPD at a rate of 3.0 μmol.m^-2.s^-1kPa -1 and the ecosystem respiration was also enhanced simultaneously due to the increase of air temperature, which was linearly correlated with the VPD. As a result, the net ecosystem carbon sequestration rapidly decreased with the increasing VPD at a rate of 5.2 μmol.m^-2.s-1.kPa^-1. Under humid conditions （VPD 〈 1.0 kPa）, both the GEP and NEP were obviously restricted by the low air temperature but were insensitive to the high temperature because the observed high temperature value comes within the category of the optimum range.展开更多
基金Under the auspices of the Natural Science Foundation of China(No.32371875,32001249)。
文摘Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have become major challenges in forestry research.In this study,we selected the Shaanxi-Gansu-Ningxia region of Northeast China as the research area and utilized multi-source datasets from the summer of 2019 to extract information on spectral,textural,climatic,water balance,and stand characteristics.By integrating the Random Forest(RF)model with Monte Carlo(MC)simulation,we constructed six regression models based on different combina-tions of features and evaluated the uncertainty of each model.Furthermore,we investigated the driving factors influencing stand age modeling by analyzing the effects of different types of features on age inversion.Model performance and accuracy were assessed using the root mean square error(RMSE),mean absolute error(MAE),and the coefficient of determination(R^(2)),while the relative root mean square error(rRMSE)was employed to quantify model uncertainty.The results indicate that the scenarios with more obvious improve-ment in accuracy and effective reduction in uncertainty were Scenario 3 with the inclusion of climate and water balance information(RMSE=25.54 yr,MAE=18.03 yr,R^(2)=0.51,rRMSE=19.17%)and Scenario 5 with the inclusion of stand characterization informa-tion(RMSE=18.47 yr,MAE=13.05 yr,R^(2)=0.74,rRMSE=16.99%).Scenario 6,incorporating all feature types,achieved the highest accuracy(RMSE=17.60 yr,MAE=12.06 yr,R^(2)=0.77,rRMSE=14.19%).In this study,elevation,minimum temperature,and diameter at breast height(DBH)emerged as the key drivers of stand-age modeling.The proposed method can be used to identify drivers and to quantify uncertainty in stand-age estimation,providing a useful reference for improving model accuracy and uncertainty assessment.
基金National Natural Science Foundation of China(Grant No.42274180)National Key Research and Development Program of China(2021YFC2902003).
文摘Evaluation of water richness in sandstone is an important research topic in the prevention and control of mine water disasters,and the water richness in sandstone is closely related to its porosity.The refl ection seismic exploration data have high-density spatial sampling information,which provides an important data basis for the prediction of sandstone porosity in coal seam roofs by using refl ection seismic data.First,the basic principles of the variational mode decomposition(VMD)method and the random forest method are introduced.Then,the geological model of coal seam roof sandstone is constructed,seismic forward modeling is conducted,and random noise is added.The decomposition eff ects of the empirical mode decomposition(EMD)method and VMD method on noisy signals are compared and analyzed.The test results show that the firstorder intrinsic mode functions(IMF1)and IMF2 decomposed by the VMD method contain the main eff ective components of seismic signals.A prediction process of sandstone porosity in coal seam roofs based on the combination of VMD and random forest method is proposed.The feasibility and eff ectiveness of the method are verified by trial calculation in the porosity prediction of model data.Taking the actual coalfield refl ection seismic data as an example,the sandstone porosity of the 8 coal seam roof is predicted.The application results show the potential application value of the new porosity prediction method proposed in this study.This method has important theoretical guiding significance for evaluating water richness in coal seam roof sandstone and the prevention and control of mine water disasters.
基金funded by University of Zabol,Iran(Grant No.UOZ-GR-9517-24)the Vice Chancellery for Research and Technology,University of Zabol,for funding this study
文摘Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.
文摘One of the basic parameters in forest management planning is detailed knowledge of growing stock,information collected by forest inventory.Sampling methods must be accurate,inexpensive,and be easy to implement in the field.This study presents a new sampling method called branching transect for use in the Iranian Zagros forests and similar forests.Features of the new method include greater accuracy,easy implementation in nature,simplicity of statistical calculations,and low cost.In this method,transect is used,which includes some subtransects(side branches).The length of the main transect,side branches,number of trees measured in each side branch,and the number of sub-branches in this method are changeable based on homogeneity,heterogeneity,and density of a forest.In this study,based on the density and heterogeneity of the forest area studied,20-m transects with four and eight side branches were used.Sampling plots(Transects)in four inventory networks(100 m×100 m,100 m×150 m,150 m×150 m and 100 m×200 m)were implemented in the GIS environment.The results of this sampling method were compared to the results of total inventory(100%count)in terms of accuracy,precision(t-test),and inventory error percentage.Branching transect results were statistially similar to total inventory counts in all cases.The results show that this method of estimating density and canopy per hectare can be used in Zagros forests and similar forests.
基金funded by the National Natural Science Foundation of China (Grants No.51278239)
文摘To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.
基金the Ministry of Agriculture and Forestry key project“Puuta liikkeelle ja uusia tuotteita metsästä”(“Wood on the move and new products from forest”)Academy of Finland(project numbers 295100 , 306875).
文摘Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random sampling(SRS)and LPM with geographical coordinates has produced promising results in simulation studies.In this simulation study we compared all these sampling methods to systematic sampling.The LPM samples were selected solely using the coordinates(LPMxy)or,in addition to that,auxiliary remote sensing-based forest variables(RS variables).We utilized field measurement data(NFI-field)and Multi-Source NFI(MS-NFI)maps as target data,and independent MS-NFI maps as auxiliary data.The designs were compared using relative efficiency(RE);a ratio of mean squared errors of the reference sampling design against the studied design.Applying a method in NFI also requires a proven estimator for the variance.Therefore,three different variance estimators were evaluated against the empirical variance of replications:1)an estimator corresponding to SRS;2)a Grafström-Schelin estimator repurposed for LPM;and 3)a Matérn estimator applied in the Finnish NFI for systematic sampling design.Results:The LPMxy was nearly comparable with the systematic design for the most target variables.The REs of the LPM designs utilizing auxiliary data compared to the systematic design varied between 0.74–1.18,according to the studied target variable.The SRS estimator for variance was expectedly the most biased and conservative estimator.Similarly,the Grafström-Schelin estimator gave overestimates in the case of LPMxy.When the RS variables were utilized as auxiliary data,the Grafström-Schelin estimates tended to underestimate the empirical variance.In systematic sampling the Matérn and Grafström-Schelin estimators performed for practical purposes equally.Conclusions:LPM optimized for a specific variable tended to be more efficient than systematic sampling,but all of the considered LPM designs were less efficient than the systematic sampling design for some target variables.The Grafström-Schelin estimator could be used as such with LPMxy or instead of the Matérn estimator in systematic sampling.Further studies of the variance estimators are needed if other auxiliary variables are to be used in LPM.
文摘In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.
文摘Ideal point method is one of the methods to solve multi-objective problem. It is applied to forest harvest regu-lation, and showed very good results by analyzing changes of quantitative indexes of forest resource structure before andafter the regulation. This method can be applied as one of the mathematical tools in forest harvest regulation.
基金Supported by the National Natural Science Foundation of Zhejiang Province (Y304369)~~
文摘Through the survey of National Nature Reserve of Tianmu Mountain,based on relevant data of tourists of Tianmu Mountain over the years,the paper had analyzed some problems about the application of contingent value method(CVM) in forest recreational value evaluation.Then,it had evaluated the forest recreational value of National Nature Reserve of Tianmu Mountain in 2007 and obtained evaluation results.Through the statistics of tourists' payment targets,it had calculated the payment value of each function of Tianmu Nature Reserve.The functions were appreciating landscape,exercising,visiting historical sites,photographing,scientific research,picnic and camping,and religion ranking in order from higher to lower value.In terms of nonuse value,existence value was slightly higher than option value and heritage value.It could be known from above research that Tianmu Mountain had great tourism development potential.Finally,it had proposed some suggestions for publicity,project setting and artificial landscape construction.
基金financially supported by the Fundamental Research Funds for the Central Universities Nos.DL12EB01-03the planning subject of "the Twelfth Five-Year-Plan" in National Science and Technology Nos.2012AA102003-2Heilongjiang Natural Science Fund in China Nos.F201116
文摘Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.
基金supported by the National Key Research and Development Program of China under the theme“Research on the evaluation methods and standards of urban sustainable development” [Grant No.2022YFC3802901]Central Public-Interest Scientific Institution Basal Research Fund,CNIS“Research on the implementation of ISO 37101 for Sustainable cities and communities in China” [Grant No.512024Y-11450].
文摘As China continues to develop its ecological civilization,it is crucial to quantitatively assess the ecological value to understand its potential impact on regional sustainable development.While previous studies have highlighted the importance of ecological value,they have not fully reflected the value of ecological restoration work or considered social costs and benefits,lacking a people-centered approach.Hence,this study analyzes the essence of ecological value from the perspective of sustainable development.By studying emblematic ecological restoration areas such as the Saihanba Mechanized Forest Farm in Chengde City,it aims to identify the significance of ecological restoration efforts in enhancing regional sustainable development capacity.The results underscore the necessity of comprehensively considering the value chain from ecological construction to ecological output,highlighting the value of ecological restoration in the ecological construction process as well as the well-being of people in the ecological output process.This approach assigns more economic and humanistic attributes to ecological value,thereby better serving the development of ecological restoration areas.
基金supported by the National Natural Science Foundation of China (No.51205005)the Beijing Science and Technology Innovation Service Ability Building (No.PXM2017-014212-000013)。
文摘It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covariance between variables is serious, which can lead to a decrease in the model prediction accuracy. In this paper, the standard solutions of nitrate nitrogen(NO_(3)-N) and nitrite nitrogen(NO_(2)-N) were used as the subject to be tested, and the data of the scanned waves and absorbance were obtained by use of spectral detector. The data were processed by noise reduction first and then the random forest(RF) algorithm was adopted to establish the regression relationship between concentration and absorbance. For comparison, partial least squares(PLS) and support vector machine(SVM) algorithm models were also established. For the same given data, the three reverse models can make the projection of the concentration respectively. The experimental results show that the RF algorithm predicts NO_(2)-N concentrations significantly better than the SVM algorithm and PLS algorithm. This proves that the RF algorithm has good prediction ability in spectral water quality detection because of its high model accuracy and better adaptability, which could be a reference for similar research on continuous spectral water quality online detection.
基金Supported by projects of National Natural Science Foundation of China(No.42074150)National Key Research and Development Program of China(No.2023YFC3707901)Futian District Integrated Ground Collapse Monitoring and Early Warning System Construction Project(No.FTCG2023000209).
文摘The exploration of urban underground spaces is of great significance to urban planning,geological disaster prevention,resource exploration and environmental monitoring.However,due to the existing of severe interferences,conventional seismic methods cannot adapt to the complex urban environment well.Since adopting the single-node data acquisition method and taking the seismic ambient noise as the signal,the microtremor horizontal-to-vertical spectral ratio(HVSR)method can effectively avoid the strong interference problems caused by the complex urban environment,which could obtain information such as S-wave velocity and thickness of underground formations by fitting the microtremor HVSR curve.Nevertheless,HVSR curve inversion is a multi-parameter curve fitting process.And conventional inversion methods can easily converge to the local minimum,which will directly affect the reliability of the inversion results.Thus,the authors propose a HVSR inversion method based on the multimodal forest optimization algorithm,which uses the efficient clustering technique and locates the global optimum quickly.Tests on synthetic data show that the inversion results of the proposed method are consistent with the forward model.Both the adaption and stability to the abnormal layer velocity model are demonstrated.The results of the real field data are also verified by the drilling information.
基金funded by the Central University D Project(HFW230600022)National Natural Science Foundation of China(71973021)+1 种基金National Natural Science Foundation Youth Funding Project(72003022)Heilongjiang Province University Think Tank Open Topic(ZKKF2022173).
文摘The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.
基金jointly supported by the National Natural Science Foundation of China [grant number 42265012]the Funding by the Fengyun Application Pioneering Project [grant number FY-APP-ZX-2022.0221]。
文摘Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability of forests.At the same time,detailed accounts of disturbances and forest responses are not yet well quantified in Asia.This study employed the Breaks For Additive Seasonal and Trend method-an abrupt-change detection method-to analyze the Enhanced Vegetation Index time series in East Asia,South Asia,and Southeast Asia.This approach allowed us to detect forest disturbance and quantify the resilience after disturbance.Results showed that 20%of forests experienced disturbance with an increasing trend from 2000 to 2022,and Southeast Asian countries were more severely affected by disturbances.Specifically,95%of forests had robust resilience and could recover from disturbance within a few decades.The resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance magnitude.In summary,this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two decades.The authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in 2022.The findings of this study underscore the complex relationship between disturbance and resilience,contributing to comprehension of forest resilience through satellite remote sensing.
基金the Global Environment Research Fund,Ministry of the Environment,Japan (S-1: Integrated Study for Terrestrial Carbon Management of Asia in the 21st Century Based on Scientific Advancements)the Chinese Academy of Sciences (07W70000SZ)+1 种基金the National Natural Science Foundation of China (30300271)the State Key Basic Research and Development Plan of China (2004CCA02700)
文摘The Dahurian larch forest in northeast China is important due to its vastness and location within a transitional zone from boreal to temperate and at the southern distribution edge of the vast Siberian larch forest. The continuous carbon fluxes were measured from May 2004 to April 2005 in the Dahurian larch forest in Northeast China using an eddy covariance method. The results showed that the ecosystem released carbon in the dormant season from mid-October 2004 to April 2005, while it assimilated CO2 from the atmosphere in the growing season from May to September 2004. The net carbon sequestration reached its peak of 112 g.m^-2.month ^-1 in June 2004 （simplified expression of g （carbon）.m^-2.month^-1） and then gradually decreased. Annually, the larch forest was a carbon sink that sequestered carbon of 146 g-m^-2.a^-1 （simplified expression of g （carbon）.m^-2.a^-1） during the measurements. The photosynthetic process of the larch forest ecosystem was largely affected by the vapor pressure deficit （VPD） and temperature. Under humid conditions （VPD 〈 1.0 kPa）, the gross ecosystem production （GEP） increased with increasing temperature. But the net ecosystem production （NEP） showed almost no change with increasing temperature because the increment of GEP was counterbalanced by that of the ecosystem respiration. Under a dry environment （VPD 〉 1.0 kPa）, the GEP decreased with the increasing VPD at a rate of 3.0 μmol.m^-2.s^-1kPa -1 and the ecosystem respiration was also enhanced simultaneously due to the increase of air temperature, which was linearly correlated with the VPD. As a result, the net ecosystem carbon sequestration rapidly decreased with the increasing VPD at a rate of 5.2 μmol.m^-2.s-1.kPa^-1. Under humid conditions （VPD 〈 1.0 kPa）, both the GEP and NEP were obviously restricted by the low air temperature but were insensitive to the high temperature because the observed high temperature value comes within the category of the optimum range.
