Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study...Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.展开更多
Background： Capturing the response of forest ecosystems to inter-annual climate variability is a great challenge.In this study, we tested the capability of an individual-based forest gap model to display carbon fluxe...Background： Capturing the response of forest ecosystems to inter-annual climate variability is a great challenge.In this study, we tested the capability of an individual-based forest gap model to display carbon fluxes at yearly and daily time scales.The forest model was applied to a spruce forest to simulate the gross primary production（GPP）, respiration and net ecosystem exchange（NEE）.We analyzed how the variability in climate affected simulated carbon fluxes at the scale of the forest model.Results： Six years were simulated at a daily time scale and compared to the observed eddy covariance（EC） data.In general, the seasonal cycle of the individual carbon fluxes was correctly described by the forest model.However, the estimated GPP differed from the observed data on the days of extreme climatic conditions.Two new parameterizations were developed： one resulting from a numerical calibration, and the other resulting from a filtering method.We suggest new parameter values and even a new function for the temperature limitation of photosynthesis.Conclusions： The forest model reproduced the observed carbon fluxes of a forest ecosystem quite wel.Of the three parameterizations, the calibrated model version performed best.However, the filtering approach showed that calibrated parameter values do not necessarily correctly display the individual functional relations.The concept of simulating forest dynamics at the individual base is a valuable tool for simulating the NEE, GPP and respiration of forest ecosystems.展开更多
Background： Tropical forests play an important role in the global carbon（C） cycle.However, tropical montane forests have been studied less than tropical lowland forests, and their role in carbon storage is not well...Background： Tropical forests play an important role in the global carbon（C） cycle.However, tropical montane forests have been studied less than tropical lowland forests, and their role in carbon storage is not well understood.Montane forests are highly endangered due to logging, land-use and climate change.Our objective was to analyse how the carbon balance changes during forest succession.Methods： In this study, we used a method to estimate local carbon balances that combined forest inventory data with process-based forest models.We utilised such a forest model to study the carbon balance of a tropical montane forest in South Ecuador, comparing two topographical slope positions（ravines and lower slopes vs upper slopes and ridges）.Results： The simulation results showed that the forest acts as a carbon sink with a maximum net ecosystem exchange（NEE） of 9.3 Mg C？（ha？yr）-1during its early successional stage（0–100 years）.In the late successional stage, the simulated NEE fluctuated around zero and had a variation of 0.77 Mg C？（ha？yr）–1.The simulated variability of the NEE was within the range of the field data.We discovered several forest attributes（e.g., basal area or the relative amount of pioneer trees） that can serve as predictors for NEE for young forest stands（0–100 years） but not for those in the late successional stage（500–1,000 years）.In case of young forest stands these correlations are high, especially between stand basal area and NEE.Conclusion： In this study, we used an Ecuadorian study site as an example of how to successfully link a forest model with forest inventory data, for estimating stem-diameter distributions, biomass and aboveground net primary productivity.To conclude, this study shows that process-based forest models can be used to investigate the carbon balance of tropical montane forests.With this model it is possible to find hidden relationships between forest attributes and forest carbon fluxes.These relationships promote a better understanding of the role of tropical montane forests in the context of global carbon cycle, which in future will become more relevant to a society under global change.展开更多
基金the University of Milan for funding the“ProForesta”project through the 2020 Research Support Planthe“Ente Parco Nazionale dell'Appennino Tosco-Emiliano”for having financed the project“First urgent measures to promote the adaptation of the silver fir forests of the Tuscan-Emilian Apennine National Park to the effects of climate change”。
文摘Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.
基金supported by the Helmholtz-Alliance Remote Sensing and Earth System Dynamicssupported by the Helmholtz Impulse and Networking Fund through the Helmholtz Interdisciplinary Graduate School for Environmental Research(HIGRADE)
文摘Background： Capturing the response of forest ecosystems to inter-annual climate variability is a great challenge.In this study, we tested the capability of an individual-based forest gap model to display carbon fluxes at yearly and daily time scales.The forest model was applied to a spruce forest to simulate the gross primary production（GPP）, respiration and net ecosystem exchange（NEE）.We analyzed how the variability in climate affected simulated carbon fluxes at the scale of the forest model.Results： Six years were simulated at a daily time scale and compared to the observed eddy covariance（EC） data.In general, the seasonal cycle of the individual carbon fluxes was correctly described by the forest model.However, the estimated GPP differed from the observed data on the days of extreme climatic conditions.Two new parameterizations were developed： one resulting from a numerical calibration, and the other resulting from a filtering method.We suggest new parameter values and even a new function for the temperature limitation of photosynthesis.Conclusions： The forest model reproduced the observed carbon fluxes of a forest ecosystem quite wel.Of the three parameterizations, the calibrated model version performed best.However, the filtering approach showed that calibrated parameter values do not necessarily correctly display the individual functional relations.The concept of simulating forest dynamics at the individual base is a valuable tool for simulating the NEE, GPP and respiration of forest ecosystems.
基金financial support of the German Research Foundation(DFG,Research Unit 816)for initializing the forest plots and the plot census as well as a first model parameterisationthe Helmholtz Alliance:Remote Sensing and Earth System Dynamics for financing the work on the further parameterisation of the model and analysis of the data
文摘Background： Tropical forests play an important role in the global carbon（C） cycle.However, tropical montane forests have been studied less than tropical lowland forests, and their role in carbon storage is not well understood.Montane forests are highly endangered due to logging, land-use and climate change.Our objective was to analyse how the carbon balance changes during forest succession.Methods： In this study, we used a method to estimate local carbon balances that combined forest inventory data with process-based forest models.We utilised such a forest model to study the carbon balance of a tropical montane forest in South Ecuador, comparing two topographical slope positions（ravines and lower slopes vs upper slopes and ridges）.Results： The simulation results showed that the forest acts as a carbon sink with a maximum net ecosystem exchange（NEE） of 9.3 Mg C？（ha？yr）-1during its early successional stage（0–100 years）.In the late successional stage, the simulated NEE fluctuated around zero and had a variation of 0.77 Mg C？（ha？yr）–1.The simulated variability of the NEE was within the range of the field data.We discovered several forest attributes（e.g., basal area or the relative amount of pioneer trees） that can serve as predictors for NEE for young forest stands（0–100 years） but not for those in the late successional stage（500–1,000 years）.In case of young forest stands these correlations are high, especially between stand basal area and NEE.Conclusion： In this study, we used an Ecuadorian study site as an example of how to successfully link a forest model with forest inventory data, for estimating stem-diameter distributions, biomass and aboveground net primary productivity.To conclude, this study shows that process-based forest models can be used to investigate the carbon balance of tropical montane forests.With this model it is possible to find hidden relationships between forest attributes and forest carbon fluxes.These relationships promote a better understanding of the role of tropical montane forests in the context of global carbon cycle, which in future will become more relevant to a society under global change.
