Growth decline assessment in Pinus sylvestris L. and Pinus nigra Arnold. forest by using 3-PG model.

Navarro-Cerrillo, Rafael M.; Beira, Jesus; Suárez, Juan Carlos Pinilla; Xenakis, Georgios; Sánchez‐Salguero, Raúl; Hernández-Clemente, Rocío

doi:10.5424/fs/2016253-08610

Cited by 7 publications

(6 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In homogeneous canopies such as those of pine plantations, higher LAI values are expected for healthy vegetation. These results are consistent with other studies in P. sylvestris plantations under Mediterranean conditions [66]; although, a significant reduction in leaf area may be expected due to defoliation [20].…”

Section: Tree Crown Biochemical Variables At the Plot Levelsupporting

confidence: 93%

Stand Delineation of Pinus sylvestris L. Plantations Suffering Decline Processes Based on Biophysical Tree Crown Variables: A Necessary Tool for Adaptive Silviculture

Varo-Martínez

Navarro-Cerrillo

2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Many planted Pinus forests are severely affected by defoliation and mortality processes caused by pests and droughts. The mapping of forest tree crown variables (e.g., leaf area index and pigments) is particularly useful in stand delineation for the management of declining forests. This work explores the potential of integrating multispectral WorldView-2 (WV-2) and Airborne Laser Scanning (ALS) data for stand delineation based on selected tree crown variables in Pinus sylvestris plantations in southern Spain. Needle pigments (chlorophyll and carotenes) and leaf area index (LAI) were quantified. Eight vegetation indices and ALS-derived metrics were produced, and seven predictors were selected to estimate and map tree crown variables using a Random Forest method and Gini index. Chlorophylls a and b (Chla and Chlb) were significantly higher in the non-defoliated and moderately defoliated trees than in severely defoliated trees (F = 14.02, p < 0.001 for Chla; F = 13.09, p < 0.001 for Chlb). A similar response was observed for carotenoids (Car) (F = 14.13, p < 0.001). The LAI also showed significant differences among the defoliation levels (F = 26.5, p < 0.001). The model for the chlorophyll a pigment used two vegetation indices, Plant Senescence Reflectance Index (PSRI) and Carotenoid Reflectance Index (CRI); three WV-2 band metrics, and three ALS metrics. The model built to describe the tree Chlb content used similar variables. The defoliation classification model was established with a single vegetation index, Green Normalized Difference Vegetation Index (GNDVI); two metrics of the blue band, and two ALS metrics. The pigment contents models provided R2 values of 0.87 (Chla, RMSE = 12.98%), 0.74 (Chlb, RMSE = 10.39%), and 0.88 (Car, RMSE = 10.05%). The cross-validated confusion matrix achieved a high overall classification accuracy (84.05%) and Kappa index (0.76). Defoliation and Chla showed the validation values for segmentations and, therefore, in the generation of the stand delineation. A total of 104 stands were delineated, ranging from 6.96 to 54.62 ha (average stand area = 16.26 ha). The distribution map of the predicted severity values in the P. sylvestris plantations showed a mosaic of severity patterns at the stand and individual tree scales. Overall, the findings of this work underscore the potential of WV-2 and ALS data integration for the assessment of stand delineation based on tree health status. The derived cartography is a relevant tool for developing adaptive silvicultural practices to reduce Pinus sylvestris mortality in planted forests at risk due to climate change.

show abstract

Section: Tree Crown Biochemical Variables At the Plot Levelsupporting

confidence: 93%

Stand Delineation of Pinus sylvestris L. Plantations Suffering Decline Processes Based on Biophysical Tree Crown Variables: A Necessary Tool for Adaptive Silviculture

Varo-Martínez

Navarro-Cerrillo

2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…The results of this research are very different from those of the other related studies in forest decline (Temiño-Villota et al 2016;Navarro-Cerrillo et al 2016) because of using the managerial and mathematical methods and the previous forest decline models (Kabrick et al 2008;Ríos-Saldaña et al 2018). Compared to the previous forestry model studies, this study has targeted a different field of study in forest management.…”

Section: Resultsmentioning

confidence: 69%

Application of time-cost trade-off model in forest management projects: The case of Oak decline project

Zandebasiri¹,

Vacik²,

Etongo³

et al. 2019

J. For. Sci.

View full text Add to dashboard Cite

Oak decline has been observed periodically in the different parts of the world. We conducted this study to evaluate the project control in this phenomenon. In this paper, the project control methods have proposed to be useful tools to deal with oak decline. The aim of the study is twofold: (i) define and schedule a set of activities and determine times for those activities in the Control of Forest Decline Project (CFDP) using the Project Evaluation and Review Technique (PERT) method; (ii) apply the Critical Path Method (CPM) within the context on how to reduce the project time by increasing operating costs and crashing the activities. In crisis management, “golden time” is defined for doing activities and controlling the crisis, which has a greater role than other times. The analysis confirmed that the problem of forest decline is an ecological problem and its root lies in participatory management with the local community. We also found that the time crashing is not economically efficient to the CFDP except for two activities: public information and stakeholder analysis.

show abstract

“…alphaCx, pFS20, gammaF1), and minimal to parameters to which 3-PG outputs are relatively insensitive (e.g. Tmax, CoeffCond, Max-Intcptn) (for 3-PG sensitivity analyses, see Almeida et al 2004;Esprey et al 2004;Forrester and Tang 2016;Law et al 2000;Mathys et al 2014;Meyer et al 2017;Navarro-Cerrillo et al 2016;Pérez-Cruzado et al 2011;Potithep and Yasuoka 2011;Xenakis et al 2008). The largest reduction in uncertainty for all species was for parameters associated with biomass partitioning (pFS20), root or foliage litterfall (gammaF1, gammaR) and light-use efficiency (alphaCx).…”

Section: Discussionmentioning

confidence: 99%

“…Bayesian inference was used to derive parameter estimates and uncertainties for 18 parameters (Table 2). These 18 parameters were selected because they could not be calculated directly from our data, such as those in step 1, and sensitivity analyses have shown that 3-PG is sensitive to these parameters (Almeida et al 2004;Esprey et al 2004;Forrester and Tang 2016;Law et al 2000;Mathys et al 2014;Meyer et al 2017;Navarro-Cerrillo et al 2016;Pérez-Cruzado et al 2011;Potithep and Yasuoka 2011;Xenakis et al 2008). This step was based on 161 EFM and 152 NFI plots.…”

Section: Step 2-bayesian Calibrationmentioning

confidence: 99%

Calibration of the process-based model 3-PG for major central European tree species

et al. 2021

View full text Add to dashboard Cite

Process-based forest models are important tools for predicting forest growth and their vulnerability to factors such as climate change or responses to management. One of the most widely used stand-level process-based models is the 3-PG model (Physiological Processes Predicting Growth), which is used for applications including estimating wood production, carbon budgets, water balance and susceptibility to climate change. Few 3-PG parameter sets are available for central European species and even fewer are appropriate for mixed-species forests. Here we estimated 3-PG parameters for twelve major central European tree species using 1418 long-term permanent forest monitoring plots from managed forests, 297 from un-managed forest reserves and 784 Swiss National Forest Inventory plots. A literature review of tree physiological characteristics, as well as regression analyses and Bayesian inference, were used to calculate the 3-PG parameters.The Swiss-wide calibration, based on monospecific plots, showed a robust performance in predicting forest stocks such as stem, foliage and root biomass. The plots used to inform the Bayesian calibration resulted in posterior ranges of the calibrated parameters that were, on average, 69% of the prior range. The bias of stem, foliage and root biomass predictions was generally less than 20%, and less than 10% for several species. The parameter sets also provided reliable predictions of biomass and mean tree sizes in mixed-species forests. Given that the information sources used to develop the parameters included a wide range of climatic, edaphic and management conditions and long time spans (from 1930 to present), these species parameters for 3-PG are likely to be appropriate for most central European forests and conditions.

show abstract

Growth decline assessment in Pinus sylvestris L. and Pinus nigra Arnold. forest by using 3-PG model.

Cited by 7 publications

References 47 publications

Stand Delineation of Pinus sylvestris L. Plantations Suffering Decline Processes Based on Biophysical Tree Crown Variables: A Necessary Tool for Adaptive Silviculture

Stand Delineation of Pinus sylvestris L. Plantations Suffering Decline Processes Based on Biophysical Tree Crown Variables: A Necessary Tool for Adaptive Silviculture

Application of time-cost trade-off model in forest management projects: The case of Oak decline project

Calibration of the process-based model 3-PG for major central European tree species

Contact Info

Product

Resources

About