Background: Coupling biomass models with nutrient concentrations can provide sound estimations of carbon and nutrient contents, enabling the improvement of carbon and nutrient balance in forest ecosystems. Although nu...Background: Coupling biomass models with nutrient concentrations can provide sound estimations of carbon and nutrient contents, enabling the improvement of carbon and nutrient balance in forest ecosystems. Although nutrient concentrations are often assumed to be constant for some species and specific tree components, at least in mature stands,the concentrations usually vary with age, site index and even with tree density. The main objective of this study was to evaluate the sources of variation in nutrient concentrations in biomass compartments usually removed during harvesting operations, covering a range of species and management conditions: semi-natural forest, conventional forest plantations and short rotation forestry(SRF). Five species(Betula pubescens, Quercus robur, Eucalyptus globulus, Eucalyptus nitens and Populus spp.) and 14 genotypes were considered. A total of 430 trees were sampled in 61 plots to obtain 6 biomass components:leaves, twigs, thin branches, thick branches, bark and wood. Aboveground leafless biomass was pooled together forpoplar.The concentrations of C, N, K, P, Ca, Mg, S, Fe, Mn, Cu, Zn and B were measured and the total biomass of each sampled tree and plot were determined. The data were analysed using boosted regression trees and conventional techniques.Results: The main sources of variation in nutrient concentrations were biomass component > > genotype(species) ≈ age >tree diameter. The concentrations of Ca, Mg and K were most strongly affected by genotype and age. The concentrations of P, K, Ca, Mg, S and Cu in the wood component decreased with age, whereas C concentrations increased, with a trend to reach 50% in the older trees. In the SRF, interamerican poplar and P. trichocarpa genotypes were comparatively more efficient in terms of Ca and K nutrient assimilation index(NAI)(+65-85%) than eucalypts, mainly because leafless biomass can be removed. In the conventional eucalypt plantations(rotation 15 years), debarking the wood at logging(savings of225% of Ca and 254% of Mg for E. globulus) or the use of selected genotypes(savings of 45% of P and 35% of Ca) will provide wood at a relatively lower nutrient cost. Considering all the E. globulus genotypes together, the management for pulp with removal of debarked wood shows NAI values well above(x 1.7-x 3.9) the ones found for poplar or eucalypt SRF and also higher(x 1.6-x4.0) than the ones found for oak and birch managed in medium or long rotations.The annual rates of nutrient removal were low in the native broadleaved species but the rates of available soil nutrients removed were high as compared to poplar or eucalypts. Management of native broadleaved species should consider nutrient stability through selection of the biomass compartments removed.(Continued on next page)(Continued from previous page)Conclusions: The nutrient assimilation index is higher in poplar grown under short rotation forestry management than in the other systems considered. Nutrient management of fast growing eucalyptus plantations could be improved by selecting efficient genotypes and limiting removal of wood. The values of the nutrient assimilation index are lower in the natural stands of native broadleaved species than in the other systems considered.展开更多
Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Ph...Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Phytopththora”.Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity.Data obtained by unmanned aerial vehicles(UAVs)may be particularly useful for such tasks due to the high resolution,flexibility of acquisition and cost efficiency of this type of data.In this study,A.glutinosa decline was assessed by considering four categories of tree health status in the field:asymptomatic,dead and defoliation above and below a 50%threshold.A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles-red green blue(RGB)data were analysed using classical random forest(RF)and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony.A total of 34 remote sensing variables were considered,including a set of vegetation indices,texture features from the normalized difference vegetation index(NDVI)and a digital surface model(DSM),topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level.Results:The four categories identified by the RF yielded an overall accuracy of 67%,while aggregation of the legend to three classes(asymptomatic,defoliated,dead)and to two classes(alive,dead)improved the overall accuracy to 72%and 91%respectively.On the other hand,the confusion matrix,computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%,80%and 94%for four-,three-and two-level classifications,respectively.Discussion:The study findings provide forest managers with an alternative robust classification method for the rapid,effective assessment of areas affected and non-affected by the disease,thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forests.展开更多
Four generalised diameter-height equations were developed and compared for pure and even-aged stands of Tecomella undulata in hot arid region of Rajasthan State in India. The data used to fit the equations consisted o...Four generalised diameter-height equations were developed and compared for pure and even-aged stands of Tecomella undulata in hot arid region of Rajasthan State in India. The data used to fit the equations consisted of 1 540 diameter-height observations collected from the plots laid out in uniformly stocked stands of varying age and density. The performance of four equations was tested by non-linear least squares regression and evaluated using different statistical criteria. Finally, these equations, with the same values of coefficients ob- tained during the fitting phase, were validated by an independent data set consisting of 854 diameter-height observations. Overall, equation （4） （Hui and Gadow function） was found to perform best for both the fitting data set as well as validation data set.展开更多
This paper presents equations for estimating limiting stand density for Z undulata plantations grown in hot desert areas of Raj asthan State in India. Five different stand level basal area projection models, belonging...This paper presents equations for estimating limiting stand density for Z undulata plantations grown in hot desert areas of Raj asthan State in India. Five different stand level basal area projection models, belonging to the path invariant algebraic difference form of a non-linear growth function, were also tested and compared. These models can be used to predict future basal area as a function of stand variables like dominant height and stem number per hectare and are necessary for reviewing different silvicultural treatment options. Data from 22 sample plots were used for modelling. An all possible growth intervals data structure was used. Both, qualitative and quantitative criteria were used to compare alternative models. The Akaike＇s information criteria differ- ence statistic was used to analyze the predictive ability of the models. Results show that the model proposed by Hui and Gadow performed best and hence this model is recommended for use in predicting basal area development in 12 undulata plantations in the study area. The data used were not from thinned stands, and hence the models may be less accurate when used for predictions when natural mortality is very significant.展开更多
基金Funding for this research was obtained from MINECO(Spain)through the project RTA2014-00007-C03-02Additional funding was derived from the projects AGL2010-22308-C02-01 and AGL2007-66739-C02-01/FOR
文摘Background: Coupling biomass models with nutrient concentrations can provide sound estimations of carbon and nutrient contents, enabling the improvement of carbon and nutrient balance in forest ecosystems. Although nutrient concentrations are often assumed to be constant for some species and specific tree components, at least in mature stands,the concentrations usually vary with age, site index and even with tree density. The main objective of this study was to evaluate the sources of variation in nutrient concentrations in biomass compartments usually removed during harvesting operations, covering a range of species and management conditions: semi-natural forest, conventional forest plantations and short rotation forestry(SRF). Five species(Betula pubescens, Quercus robur, Eucalyptus globulus, Eucalyptus nitens and Populus spp.) and 14 genotypes were considered. A total of 430 trees were sampled in 61 plots to obtain 6 biomass components:leaves, twigs, thin branches, thick branches, bark and wood. Aboveground leafless biomass was pooled together forpoplar.The concentrations of C, N, K, P, Ca, Mg, S, Fe, Mn, Cu, Zn and B were measured and the total biomass of each sampled tree and plot were determined. The data were analysed using boosted regression trees and conventional techniques.Results: The main sources of variation in nutrient concentrations were biomass component > > genotype(species) ≈ age >tree diameter. The concentrations of Ca, Mg and K were most strongly affected by genotype and age. The concentrations of P, K, Ca, Mg, S and Cu in the wood component decreased with age, whereas C concentrations increased, with a trend to reach 50% in the older trees. In the SRF, interamerican poplar and P. trichocarpa genotypes were comparatively more efficient in terms of Ca and K nutrient assimilation index(NAI)(+65-85%) than eucalypts, mainly because leafless biomass can be removed. In the conventional eucalypt plantations(rotation 15 years), debarking the wood at logging(savings of225% of Ca and 254% of Mg for E. globulus) or the use of selected genotypes(savings of 45% of P and 35% of Ca) will provide wood at a relatively lower nutrient cost. Considering all the E. globulus genotypes together, the management for pulp with removal of debarked wood shows NAI values well above(x 1.7-x 3.9) the ones found for poplar or eucalypt SRF and also higher(x 1.6-x4.0) than the ones found for oak and birch managed in medium or long rotations.The annual rates of nutrient removal were low in the native broadleaved species but the rates of available soil nutrients removed were high as compared to poplar or eucalypts. Management of native broadleaved species should consider nutrient stability through selection of the biomass compartments removed.(Continued on next page)(Continued from previous page)Conclusions: The nutrient assimilation index is higher in poplar grown under short rotation forestry management than in the other systems considered. Nutrient management of fast growing eucalyptus plantations could be improved by selecting efficient genotypes and limiting removal of wood. The values of the nutrient assimilation index are lower in the natural stands of native broadleaved species than in the other systems considered.
基金co-funded by the European Commission LIFE program-Project LIFE FLUVIAL,LIFE16 NAT/ES/000771supported by the Portuguese Foundation for Science and Technology(FCT)through FCT the Investigador FCT Programme(IF/00059/2015)+2 种基金through the CEEC Individual Programme(2020.03356.CEECIND)CEF was supported through the FCT UIDB/00239/2020supported by the‘National Programme for the Promotion of Talent and Its Employability’of the Ministry of Economy,Industry,and Competitiveness(Torres-Quevedo program)through a postdoctoral grant(PTQ2018-010043).
文摘Background:Black alder(Alnus glutinosa)forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex(class Oomycetes),“alder Phytopththora”.Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity.Data obtained by unmanned aerial vehicles(UAVs)may be particularly useful for such tasks due to the high resolution,flexibility of acquisition and cost efficiency of this type of data.In this study,A.glutinosa decline was assessed by considering four categories of tree health status in the field:asymptomatic,dead and defoliation above and below a 50%threshold.A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles-red green blue(RGB)data were analysed using classical random forest(RF)and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony.A total of 34 remote sensing variables were considered,including a set of vegetation indices,texture features from the normalized difference vegetation index(NDVI)and a digital surface model(DSM),topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level.Results:The four categories identified by the RF yielded an overall accuracy of 67%,while aggregation of the legend to three classes(asymptomatic,defoliated,dead)and to two classes(alive,dead)improved the overall accuracy to 72%and 91%respectively.On the other hand,the confusion matrix,computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%,80%and 94%for four-,three-and two-level classifications,respectively.Discussion:The study findings provide forest managers with an alternative robust classification method for the rapid,effective assessment of areas affected and non-affected by the disease,thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forests.
文摘Four generalised diameter-height equations were developed and compared for pure and even-aged stands of Tecomella undulata in hot arid region of Rajasthan State in India. The data used to fit the equations consisted of 1 540 diameter-height observations collected from the plots laid out in uniformly stocked stands of varying age and density. The performance of four equations was tested by non-linear least squares regression and evaluated using different statistical criteria. Finally, these equations, with the same values of coefficients ob- tained during the fitting phase, were validated by an independent data set consisting of 854 diameter-height observations. Overall, equation （4） （Hui and Gadow function） was found to perform best for both the fitting data set as well as validation data set.
基金the State Forest Department,Rajasthan for providing financial support for conducting this study and to their officials for rendering necessary assistance during fieldwork
文摘This paper presents equations for estimating limiting stand density for Z undulata plantations grown in hot desert areas of Raj asthan State in India. Five different stand level basal area projection models, belonging to the path invariant algebraic difference form of a non-linear growth function, were also tested and compared. These models can be used to predict future basal area as a function of stand variables like dominant height and stem number per hectare and are necessary for reviewing different silvicultural treatment options. Data from 22 sample plots were used for modelling. An all possible growth intervals data structure was used. Both, qualitative and quantitative criteria were used to compare alternative models. The Akaike＇s information criteria differ- ence statistic was used to analyze the predictive ability of the models. Results show that the model proposed by Hui and Gadow performed best and hence this model is recommended for use in predicting basal area development in 12 undulata plantations in the study area. The data used were not from thinned stands, and hence the models may be less accurate when used for predictions when natural mortality is very significant.
