Watershed management is an ever-evolving practice involving the management of land, water, biota, and other resources in a defined area for ecological, social, and economic purposes. In this paper, we explore the foll...Watershed management is an ever-evolving practice involving the management of land, water, biota, and other resources in a defined area for ecological, social, and economic purposes. In this paper, we explore the following questions： How has watershed management evolved？ What new tools are available and how can they be integrated into sustainable watershed management？ To address these questions, we discuss the process of developing integrated watershed management strategies for sustainable manage- ment through the incorporation of adaptive management techniques and traditional ecological knowledge. We address the numerous benefits from integration acrossdisciplines and jurisdictional boundaries, as well as the incorporation of technological advancements, such as remote sensing, GIS, big data, and multi-level social-eco- logical systems analysis, into watershed management strategies. We use three case studies from China, Europe, and Canada to review the success and failure of integrated watershed management in addressing different ecological, social, and economic dilemmas in geographically diverse locations. Although progress has been made in watershed management strategies, there are still numerous issues impeding successful management outcomes; many of which can be remedied through holistic management approaches, incorporation of cutting-edge science and technology, and cross-jurisdictional coordination. We conclude by high- lighting that future watershed management will need to account for climate change impacts by employing techno- logical advancements and holistic, cross-disciplinary approaches to ensure watersheds continue to serve their ecological, social, and economic functions. We present three case studies in this paper as a valuable resource for scientists, resource managers, government agencies, and other stakeholders aiming to improve integrated watershed management strategies and more efficiently and successfully achieve ecological and socio-economic management objectives.展开更多
Numerous land-use policies have been implemented in China in recent decades for ecological restoration and conservation to reduce environmental disasters and promote environmental sustainability.Many of these policies...Numerous land-use policies have been implemented in China in recent decades for ecological restoration and conservation to reduce environmental disasters and promote environmental sustainability.Many of these policies follow a top-down approach to implementation and as such,emphasize the hierarchical control within government structures.An understanding of local perceptions of land-use policies is important if the disconnect between policy makers and the target population is to be reduced and if program support is to improve.This study aimed to help improve local implementation,attitude toward,and engagement by examining the influence of socio-economic characteristics on the target population’s(local farmers)perception of the conversion of cropland to forestland program(CFPP)land use policy in Jiangxi,Sichuan,and Shaanxi provinces.It uses logistical regression models,with robust aspects of perception including confidence,support,transparency,prospects,fairness,and willingness to participate.Results indicate that social aspects as well as economic aspects are most important in influencing farmers’perceptions towards the CFPP.The farmers who have received technical support,rural male habitants,educated,and non-middle-aged farmers exhibit more positive perceptions of the program and are much more likely to support it,whereas farmers without any technical support or formal education,and female and middle-aged farmers are less likely to support the program.Importantly,this study also reveals the differences in responses,experiences and perceptions of the farmers living across different provinces.These empirical results provide insight into the influence of socio-economic characteristics on the perception of farmers towards land-use policies,which has important implications for designing targeted policy instruments and increasing farmer support for these policies.This knowledge can be harnessed and further evaluated in future research to improve citizen engagement,support,and understanding in order to help ecological restoration and conservation objectives be more effectively achieved.展开更多
Climate change is a threat to the stability and productivity of forest ecosystems throughout the AsiaPacific region. The loss of forests due to climate-induced stress will have extensive adverse impacts on biodiversit...Climate change is a threat to the stability and productivity of forest ecosystems throughout the AsiaPacific region. The loss of forests due to climate-induced stress will have extensive adverse impacts on biodiversity and an array of ecosystem services that are essential for the maintenance of local economies and public health. Despite their importance, there is a lack of decision-support tools required to evaluate the potential effects of climate change on Asia-Pacific ecosystems and economies and to aid in the development of regionally appropriate adaptation and mitigation strategies. The project Adaptation of AsiaPacific Forests to Climate Change, summarized herein,aims to address this lack of knowledge and tools and to provide support for regional managers to develop effective policy to increase the adaptive capacity of Asia-Pacific forest ecosystems. This objective has been achieved through the following activities：（1） development of a highresolution climate downscaling model, Climate AP, applicable to any location in the region;（2） development of climate niche models to evaluate how climate change might affect the distribution of suitable climatic conditions for regionally important tree species;（3） development and application of forest models to assess alternative management strategies in the context of management objectives and the projected impacts of climate change;（4） evaluation of models to assess forest fire risk and the relationship between forest fire and climate change;（5） development of a technique to assess ecosystem carbon storage using Li DAR; and（6） evaluation of how vegetation dynamics respond to climate change using remote sensing technology. All project outputs were developed with a focus on communication and extension to facilitate the dissemination of results to regional forest resource managers to support the development of effective mitigation and adaptation policy.展开更多
While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial ac...While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, Climate AP, to generate scale-free(i.e., specific to point locations) climate data for historical(1901–2015) and future(2011–2100)years and periods. Climate AP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways(RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, Climate AP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the Climate AP output was evaluated through comparisons of Climate AP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. Climate AP reduced prediction error by up to27% and 60% for monthly temperature and precipitation,respectively, relative to the original baselines data. The improvements for baseline portions of historical and futurewere more substantial. Applications and limitations of the software are discussed.展开更多
Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire management.The aims of the study were:(i)to describe the history of human-caused fires by season and ...Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire management.The aims of the study were:(i)to describe the history of human-caused fires by season and size of burned area over time;(ii)to identify the spatial patterns of human-caused fires and test for the existence of‘hotspots’to determine their exact locations in the Daxing’an mountains;(iii)to determine the driving factors that determine the spatial distribution and the possibility of human-caused fire occurrence.Methods In this study,K-function and Kernel density estimation were used to analyze the spatial pattern of human-caused fires.The analysis was conducted in s-plus and arcgIs environments,respectively.The analysis of driving factors was performed in SPSS 19.0 based on a logistic regression model.The variables used to identify factors that influence fire occurrence included vegetation types,meteorological conditions,socioeconomic factors,topography and infrastructure factors,which were extracted and collected through the spatial analysis mode of arcgIs and from official statistics,respectively.Important Findings The annual number of human-caused fires and the area burnt have declined since 1987 due to the implementation of a forest fire protection act.There were significant spatial heterogeneity and seasonal variations in the distribution of human-caused fires in the Daxing’an mountains.The heterogeneity was caused by elevation,distance to the nearest railway,forest type and temperature.a logistic regression model was developed to predict the likelihood of human-caused fire occurrence in the Daxing’an mountains;its global accuracy attained 64.8%.The model was thus comparable to other relevant studies.展开更多
Forestry in China has changed drastically since the country was affected by devastating floods in 1998.The government has launched a series of nationwide ecological restoration programs,promulgated new forest policies...Forestry in China has changed drastically since the country was affected by devastating floods in 1998.The government has launched a series of nationwide ecological restoration programs,promulgated new forest policies and tax reforms,and heavily compensated forest owners.These policies and programs have already produced tangible benefits in improving forest cover,supporting the wood industry and supplementing rural livelihoods.Large areas are now protected展开更多
基金supported by Canadian SSHRC Standard Research Grant:entitled ‘‘Application of sustainable forest management in a culturally modified landscape’’the Asia–Pacific Forests Network’s project entitled‘‘Adaptation of Asia–Pacific Forests to Climate Change’’(APFNET/2010/FPF/001)
文摘Watershed management is an ever-evolving practice involving the management of land, water, biota, and other resources in a defined area for ecological, social, and economic purposes. In this paper, we explore the following questions： How has watershed management evolved？ What new tools are available and how can they be integrated into sustainable watershed management？ To address these questions, we discuss the process of developing integrated watershed management strategies for sustainable manage- ment through the incorporation of adaptive management techniques and traditional ecological knowledge. We address the numerous benefits from integration acrossdisciplines and jurisdictional boundaries, as well as the incorporation of technological advancements, such as remote sensing, GIS, big data, and multi-level social-eco- logical systems analysis, into watershed management strategies. We use three case studies from China, Europe, and Canada to review the success and failure of integrated watershed management in addressing different ecological, social, and economic dilemmas in geographically diverse locations. Although progress has been made in watershed management strategies, there are still numerous issues impeding successful management outcomes; many of which can be remedied through holistic management approaches, incorporation of cutting-edge science and technology, and cross-jurisdictional coordination. We conclude by high- lighting that future watershed management will need to account for climate change impacts by employing techno- logical advancements and holistic, cross-disciplinary approaches to ensure watersheds continue to serve their ecological, social, and economic functions. We present three case studies in this paper as a valuable resource for scientists, resource managers, government agencies, and other stakeholders aiming to improve integrated watershed management strategies and more efficiently and successfully achieve ecological and socio-economic management objectives.
基金supported by the Ministry of Science and Technology of Chinathe Canadian International Council
文摘Numerous land-use policies have been implemented in China in recent decades for ecological restoration and conservation to reduce environmental disasters and promote environmental sustainability.Many of these policies follow a top-down approach to implementation and as such,emphasize the hierarchical control within government structures.An understanding of local perceptions of land-use policies is important if the disconnect between policy makers and the target population is to be reduced and if program support is to improve.This study aimed to help improve local implementation,attitude toward,and engagement by examining the influence of socio-economic characteristics on the target population’s(local farmers)perception of the conversion of cropland to forestland program(CFPP)land use policy in Jiangxi,Sichuan,and Shaanxi provinces.It uses logistical regression models,with robust aspects of perception including confidence,support,transparency,prospects,fairness,and willingness to participate.Results indicate that social aspects as well as economic aspects are most important in influencing farmers’perceptions towards the CFPP.The farmers who have received technical support,rural male habitants,educated,and non-middle-aged farmers exhibit more positive perceptions of the program and are much more likely to support it,whereas farmers without any technical support or formal education,and female and middle-aged farmers are less likely to support the program.Importantly,this study also reveals the differences in responses,experiences and perceptions of the farmers living across different provinces.These empirical results provide insight into the influence of socio-economic characteristics on the perception of farmers towards land-use policies,which has important implications for designing targeted policy instruments and increasing farmer support for these policies.This knowledge can be harnessed and further evaluated in future research to improve citizen engagement,support,and understanding in order to help ecological restoration and conservation objectives be more effectively achieved.
基金funded by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation(APFNet)(APFNET/2010/FPF/001)
文摘Climate change is a threat to the stability and productivity of forest ecosystems throughout the AsiaPacific region. The loss of forests due to climate-induced stress will have extensive adverse impacts on biodiversity and an array of ecosystem services that are essential for the maintenance of local economies and public health. Despite their importance, there is a lack of decision-support tools required to evaluate the potential effects of climate change on Asia-Pacific ecosystems and economies and to aid in the development of regionally appropriate adaptation and mitigation strategies. The project Adaptation of AsiaPacific Forests to Climate Change, summarized herein,aims to address this lack of knowledge and tools and to provide support for regional managers to develop effective policy to increase the adaptive capacity of Asia-Pacific forest ecosystems. This objective has been achieved through the following activities：（1） development of a highresolution climate downscaling model, Climate AP, applicable to any location in the region;（2） development of climate niche models to evaluate how climate change might affect the distribution of suitable climatic conditions for regionally important tree species;（3） development and application of forest models to assess alternative management strategies in the context of management objectives and the projected impacts of climate change;（4） evaluation of models to assess forest fire risk and the relationship between forest fire and climate change;（5） development of a technique to assess ecosystem carbon storage using Li DAR; and（6） evaluation of how vegetation dynamics respond to climate change using remote sensing technology. All project outputs were developed with a focus on communication and extension to facilitate the dissemination of results to regional forest resource managers to support the development of effective mitigation and adaptation policy.
基金funded by a research grant"Adaptation of Asia-Pacific Forests to Climate Change"(APFNet/2010/PPF/001)funded by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation
文摘While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, Climate AP, to generate scale-free(i.e., specific to point locations) climate data for historical(1901–2015) and future(2011–2100)years and periods. Climate AP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways(RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, Climate AP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the Climate AP output was evaluated through comparisons of Climate AP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. Climate AP reduced prediction error by up to27% and 60% for monthly temperature and precipitation,respectively, relative to the original baselines data. The improvements for baseline portions of historical and futurewere more substantial. Applications and limitations of the software are discussed.
文摘Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire management.The aims of the study were:(i)to describe the history of human-caused fires by season and size of burned area over time;(ii)to identify the spatial patterns of human-caused fires and test for the existence of‘hotspots’to determine their exact locations in the Daxing’an mountains;(iii)to determine the driving factors that determine the spatial distribution and the possibility of human-caused fire occurrence.Methods In this study,K-function and Kernel density estimation were used to analyze the spatial pattern of human-caused fires.The analysis was conducted in s-plus and arcgIs environments,respectively.The analysis of driving factors was performed in SPSS 19.0 based on a logistic regression model.The variables used to identify factors that influence fire occurrence included vegetation types,meteorological conditions,socioeconomic factors,topography and infrastructure factors,which were extracted and collected through the spatial analysis mode of arcgIs and from official statistics,respectively.Important Findings The annual number of human-caused fires and the area burnt have declined since 1987 due to the implementation of a forest fire protection act.There were significant spatial heterogeneity and seasonal variations in the distribution of human-caused fires in the Daxing’an mountains.The heterogeneity was caused by elevation,distance to the nearest railway,forest type and temperature.a logistic regression model was developed to predict the likelihood of human-caused fire occurrence in the Daxing’an mountains;its global accuracy attained 64.8%.The model was thus comparable to other relevant studies.
文摘Forestry in China has changed drastically since the country was affected by devastating floods in 1998.The government has launched a series of nationwide ecological restoration programs,promulgated new forest policies and tax reforms,and heavily compensated forest owners.These policies and programs have already produced tangible benefits in improving forest cover,supporting the wood industry and supplementing rural livelihoods.Large areas are now protected
