Forests worldwide are experiencing increasingly intense biotic disturbances;however,assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions am...Forests worldwide are experiencing increasingly intense biotic disturbances;however,assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them.This particularly applies to invasive species,which can greatly alter ecological processes in their invaded territories.Here we focus on the pine wood nematode(PWN,Bursaphelenchus xylophilus),an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe.It is expected to expand its range into continental Europe with heavy impacts possible.Given the unknown dynamics of PWN in continental Europe,we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine(BITE),a model designed to implement a variety of forest biotic agents,from fungi to large herbivores.To simulate dynamically changing host availability and conditions,BITE was coupled with the forest landscape model iLand.The potential impacts of introducing PWN were assessed in a Central European forest landscape(40,928ha),likely within PWN’s reach in future decades.A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal,colonization,and vegetation impact,whereas parameters related to population growth manifested a minor effect.Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave,eliminating 40%–95%of pine trees within 100 years post-introduction,with a maximum annual carbon loss between 1.3%and 4.2%.PWN-induced tree mortality reduced the Gross Primary Productivity,increased heterotrophic respiration,and generated a distinct legacy sink effect in the recovery period.This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.展开更多
Urban forests being part of the Natural Capital,they provide goods and services for humans,the ecosystem services that are necessary for their survival.Over recent years,the importance of ecosystem services within urb...Urban forests being part of the Natural Capital,they provide goods and services for humans,the ecosystem services that are necessary for their survival.Over recent years,the importance of ecosystem services within urban landscapes has grown steadily.Determining the amount and the value of the ecosystem services provided by the Urban Forest is the main goal of the“Digital Green Cadastre”(DGC),a project in progress of survey,classification and mapping of the urban,agricultural and natural green assets.The DGC records the types of green cover and soil characteristics and utilizes the calculation of the total leaf area for the quantitative analysis of the botanical heritage,environmental performance and ecosystem benefits,such as water runoff management,air pollutant removal and urban heat island reduction.The case study of Abbiategrasso-a small town in Italy-is reported.展开更多
Background The conversion of forests into agricultural lands can be a threat because the forests carbon stored could be a source of emissions. The capacity to improve the predictions on the consequences of land use ch...Background The conversion of forests into agricultural lands can be a threat because the forests carbon stored could be a source of emissions. The capacity to improve the predictions on the consequences of land use change depends on the identification of factors that influence carbon pools. We investigated the key driving factors of tree biomass and soil carbon pools in xerophytic forests in northeastern Argentina. Based on analyses of forest structure variables and abiotic factors (topography and soil properties) from 18 mature forests, we evaluated carbon pools using uniand multivariate (redundancy analysis) methods. Results The total carbon pool was estimated at 102.4 ± 24.0 Mg ha−1. Soil organic carbon storage is the single largest carbon pool relative to tree biomass, representing 73.1% of total carbon. Tree canopy cover and basal area were positively correlated with biomass carbon pool (r = 0.77 and r = 0.73, p < 0.001, respectively), proving to be significant drivers of carbon storage in this compartment. Slope, soil clay content and cation-exchange capacity had a better explanation for the variability in soil carbon pools, and all showed significant positive correlations with soil carbon pools (r = 0.64, 0.60 and 0.50;p < 0.05, respectively). The vertisols showed a 27.8% higher soil carbon stock than alfisols. Conclusions The relevance of our study stems from a dearth of information on carbon pools and their drivers in xerophytic forests, and in particular, the importance of this ecosystems’ type for Argentina, because they cover 81.9% of native forest area. Basal area and tree canopy cover exert a strong effect on the carbon pool in tree biomass but not in the soil. The results suggests that there is a potentially major SOC accumulation in forests located in slightly sloping areas and soils with higher topsoil clay content, such as vertisols. This could provide an important reference for implementing forestry carbon sink projects.展开更多
目前,估算高分辨率叶面积指数LAI(Leaf Area Index)的常用方法是采用大量地面测量数据和遥感数据建立统计模型,再用统计模型估算LAI。然而,与农田地面测量实验相比,森林地面测量实验获取的观测数据更加有限,这使得基于统计模型的森林高...目前,估算高分辨率叶面积指数LAI(Leaf Area Index)的常用方法是采用大量地面测量数据和遥感数据建立统计模型,再用统计模型估算LAI。然而,与农田地面测量实验相比,森林地面测量实验获取的观测数据更加有限,这使得基于统计模型的森林高分辨率LAI的估算精度低,难以满足应用需求。为此,本文提出一种基于森林模型参数先验知识、使用森林研究区少量的LAI地面测量数据和归一化植被指数NDVI数据估算森林高分辨率LAI的方法。首先,获取全球20个森林实验区的LAI地面测量数据和NDVI数据,建立LAI-NDVI统计模型并提取森林模型参数的先验知识。然后,以一个新的森林站点Concepción作为研究区,将该研究区的数据分为建模数据和验证数据两个部分。使用研究区有限的建模数据对森林模型参数先验知识进行本地化校正得到优化模型,优化模型用于估算森林高分辨率LAI,使用验证数据评价LAI的估算精度。同时,选取了Camerons站点、Gnangara站点、Hirsikangas站点评价本文方法的LAI估算精度。使用地面测量LAI验证基于森林模型参数先验知识估算高分辨率LAI的结果精度,经验证4个森林站点的均方根误差分别为0.6680,0.4449,0.2863,0.5755。研究结果表明:在仅有少量观测数据时,采用本方法能有效地提高森林高分辨率LAI的估算精度。因此,本方法可为森林高分辨率LAI的遥感估算提供参考。展开更多
基金supported by the project“EVA4.0”,No.CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE of the Czech Republicthe H2020 project RESONATE under grant agreement No.101000574.
文摘Forests worldwide are experiencing increasingly intense biotic disturbances;however,assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them.This particularly applies to invasive species,which can greatly alter ecological processes in their invaded territories.Here we focus on the pine wood nematode(PWN,Bursaphelenchus xylophilus),an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe.It is expected to expand its range into continental Europe with heavy impacts possible.Given the unknown dynamics of PWN in continental Europe,we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine(BITE),a model designed to implement a variety of forest biotic agents,from fungi to large herbivores.To simulate dynamically changing host availability and conditions,BITE was coupled with the forest landscape model iLand.The potential impacts of introducing PWN were assessed in a Central European forest landscape(40,928ha),likely within PWN’s reach in future decades.A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal,colonization,and vegetation impact,whereas parameters related to population growth manifested a minor effect.Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave,eliminating 40%–95%of pine trees within 100 years post-introduction,with a maximum annual carbon loss between 1.3%and 4.2%.PWN-induced tree mortality reduced the Gross Primary Productivity,increased heterotrophic respiration,and generated a distinct legacy sink effect in the recovery period.This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.
文摘Urban forests being part of the Natural Capital,they provide goods and services for humans,the ecosystem services that are necessary for their survival.Over recent years,the importance of ecosystem services within urban landscapes has grown steadily.Determining the amount and the value of the ecosystem services provided by the Urban Forest is the main goal of the“Digital Green Cadastre”(DGC),a project in progress of survey,classification and mapping of the urban,agricultural and natural green assets.The DGC records the types of green cover and soil characteristics and utilizes the calculation of the total leaf area for the quantitative analysis of the botanical heritage,environmental performance and ecosystem benefits,such as water runoff management,air pollutant removal and urban heat island reduction.The case study of Abbiategrasso-a small town in Italy-is reported.
基金funded by projects PID UNER 2223“Carbon capture and fixation as an environmental service of the Espinal forests”National Observatory of Land Degradation and Desertification of ArgentinaPD INTA I040“Design and implementation of a national system for degradation monitoring system at different scales for land degradation neutrality”.
文摘Background The conversion of forests into agricultural lands can be a threat because the forests carbon stored could be a source of emissions. The capacity to improve the predictions on the consequences of land use change depends on the identification of factors that influence carbon pools. We investigated the key driving factors of tree biomass and soil carbon pools in xerophytic forests in northeastern Argentina. Based on analyses of forest structure variables and abiotic factors (topography and soil properties) from 18 mature forests, we evaluated carbon pools using uniand multivariate (redundancy analysis) methods. Results The total carbon pool was estimated at 102.4 ± 24.0 Mg ha−1. Soil organic carbon storage is the single largest carbon pool relative to tree biomass, representing 73.1% of total carbon. Tree canopy cover and basal area were positively correlated with biomass carbon pool (r = 0.77 and r = 0.73, p < 0.001, respectively), proving to be significant drivers of carbon storage in this compartment. Slope, soil clay content and cation-exchange capacity had a better explanation for the variability in soil carbon pools, and all showed significant positive correlations with soil carbon pools (r = 0.64, 0.60 and 0.50;p < 0.05, respectively). The vertisols showed a 27.8% higher soil carbon stock than alfisols. Conclusions The relevance of our study stems from a dearth of information on carbon pools and their drivers in xerophytic forests, and in particular, the importance of this ecosystems’ type for Argentina, because they cover 81.9% of native forest area. Basal area and tree canopy cover exert a strong effect on the carbon pool in tree biomass but not in the soil. The results suggests that there is a potentially major SOC accumulation in forests located in slightly sloping areas and soils with higher topsoil clay content, such as vertisols. This could provide an important reference for implementing forestry carbon sink projects.
文摘目前,估算高分辨率叶面积指数LAI(Leaf Area Index)的常用方法是采用大量地面测量数据和遥感数据建立统计模型,再用统计模型估算LAI。然而,与农田地面测量实验相比,森林地面测量实验获取的观测数据更加有限,这使得基于统计模型的森林高分辨率LAI的估算精度低,难以满足应用需求。为此,本文提出一种基于森林模型参数先验知识、使用森林研究区少量的LAI地面测量数据和归一化植被指数NDVI数据估算森林高分辨率LAI的方法。首先,获取全球20个森林实验区的LAI地面测量数据和NDVI数据,建立LAI-NDVI统计模型并提取森林模型参数的先验知识。然后,以一个新的森林站点Concepción作为研究区,将该研究区的数据分为建模数据和验证数据两个部分。使用研究区有限的建模数据对森林模型参数先验知识进行本地化校正得到优化模型,优化模型用于估算森林高分辨率LAI,使用验证数据评价LAI的估算精度。同时,选取了Camerons站点、Gnangara站点、Hirsikangas站点评价本文方法的LAI估算精度。使用地面测量LAI验证基于森林模型参数先验知识估算高分辨率LAI的结果精度,经验证4个森林站点的均方根误差分别为0.6680,0.4449,0.2863,0.5755。研究结果表明:在仅有少量观测数据时,采用本方法能有效地提高森林高分辨率LAI的估算精度。因此,本方法可为森林高分辨率LAI的遥感估算提供参考。
