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Producción de Biomasa y Fijación de CO2 Por Los Bosques Españoles
... A higher dominance of the acquisitive strategy in forests could decrease their long-term carbon sequestration capacity (i.e., non-native trees used in plantations may have high carbon sequestration rates and relatively low carbon durability; Dyderski & Jagodzinski, 2019;Hughes et al., 2014;Montero et al., 2005). Consequently, the promotion of non-native tree plantations may have profound impacts on the carbon cycle and carbon sink capacity of forested lands. ...
... In the dry climate, native forests of Q. ilex stored the largest amount of carbon (Montero et al., 2005). Q. pyrenaica also stored large amounts of carbon in the dry climate, comparable to forests dominated by E. globulus and E. camaldulensis. ...
Non-native trees may have significant impacts on the carbon sink capacity of forested lands. However, large-scale patterns of the relative capacity of native and non-native forests to uptake and store carbon remain poorly described in the literature, and this information is urgently needed to support management decisions. In this study, we analyzed 17,065 plots from the Spanish Forest Inventory (covering c. 30 years) to quantify carbon storage and sequestration of natural forests and plantations of native and non-native trees under contrasting climate types, while controlling for the effects of environmental factors (forest structure, climate, soil, topography, and management). We found that forest origin (non-native vs. native) highly influenced carbon storage and sequestration, but such effect was dependent on climate. Carbon storage was greater in non-native than in native forests in both wet and dry climates. Non-native forests also had greater carbon sequestration than native ones in the wet climate, due to higher carbon gains by tree growth. However, in the dry climate, native forests had greater carbon gains by tree ingrowth and lower carbon loss by tree mortality than non-native ones. Furthermore, forest type (classified by the dominant species) and natural forests versus tree plantations were important determinants of carbon storage and sequestration. Native and non-native Pinus spp. forests had low carbon storage, whereas non-native Eucalyptus spp. forests and native Quercus spp., Fagus sylvatica, and Eurosiberian mixed forests (especially not planted ones) had high carbon storage. Carbon sequestration was greatest in Eucalyptus globulus, Quercus ilex, and Pinus pinaster forests. Overall, our findings suggest that the relative capacity of native and non-native forests to uptake and store carbon depends on climate, and that the superiority of non-native forests over native ones in terms of carbon seques-tration declines as the abiotic filters become stronger (i.e., lower water availability and higher climate seasonality).
... LM, General Linear Model; GLMM, Generalised Linear Mixed Model; NDVI, Normalised Difference Vegetation Index; NDVI sum , integral of monthly max NDVI along SNFIs period; NDVI diff , Difference of annual mean between SNFIs; OM, Organic matter; PCA, Principal Component Analysis; SNFI, Spanish National Forest Inventory; LIDAR, Light Detection And Ranging. area, AGB) is a widely studied variable that informs about forest structure and function (Montero et al., 2005;Pecl et al., 2017;Sar and Further, 2020). Forest productivity, or the variation of aboveground biomass of trees over time, is the quantitative forest gain that determines forest biomass (Keeling and Phillips, 2007;Ruiz-Benito et al., 2014;Salazar et al., 2021). ...
... aboveground biomass, AGB, Mg ha − 1 ) in each plot applying species-specific allometric equations based on the d.b.h. (Montero et al., 2005;Supplementary Material , Table S2). We calculated total forest biomass in each plot as the sum of the biomass of trees alive per ha (AGB, Mg ha − 1 ) for the two forest inventories (SNFI_2 and SNFI_3). ...
... The assumption for assessing recovery was that burned plots that most resembled the unburned control stands would be considered as "recovered," while the remaining plots would be labeled as "not yet recovered". The degree of similarity was assessed by comparing the main characteristics of the stands including: the height of the tree layer (maximum and mean height were measured using a Haglöf Swe-den® Vertex instrument; meters), the fraction of cover along the vertical gradient of strata was assessed visually according to the Braun-Blanquet scale (Braun-Blanquet, 1979; stratum 1 <0.5 m, stratum 2 0.5-1 m, stratum 3 1-3 m, stratum 4 3-5 m, stratum 5> 5 m; percent cover), the amount of above-ground biomass of tree (based on breast height diameter at 1.3 m, using a Mantax Precision Blue diameter caliper Haglöf Sweden®) and shrub species (based on shrub mean height and canopy cover), separately (tons/ha), using the specific allometric equations proposed by Montero et al., (2013Montero et al., ( , 2005, and the abundance of species including tree, shrub, and herbaceous species (number of distinct species) present in the plot. All these variables were surveyed and measured in the field via forest inventory. ...
The accumulation of fuel and the homogenization of the landscape in Mediterranean forests are leading to an increasingly hazardous behavior of wildfires, fostering larger, more intense, severe, and frequent wildfires. The onset of climate change is intensifying this behavior, fostering the occurrence of extreme forest fires threatening the persistence of forest communities. In this study we present an assessment of the post-fire recovery potential of the most representative tree-forest communities affected by fire in Spain: Pinus halepensis, Pinus nigra, Pinus pinaster and Quercus ilex. A large database of field data collected during specific campaigns-carried out 25 years after the fire-is used in combination with remote sensing, forest inventory and geospatial data to build an empirical model capable of predicting the chances of recovery. The model, calibrated using Random Forest, combines information on burn severity (remote sensing estimates of the Composite Burn Index), local topography (slope and terrain aspect) and climatic data (mean values and trends of temperature and precipitation) to provide information on the degree of similarity (vegetation height, horizontal cover of the vegetation layer along vertical strata, aboveground biomass and species diversity) between the plots burned in the summer of 1994 and the unburned control. Overall, only 33 out of the 131 burned plots could be considered as recovered, that is, reaching a similar state to unburned stands in neighboring areas. Our results suggest a primary role played by burn severity (the higher the severity the lower the probability of recovery), but strongly modulated by local topographic features (higher probability of recovery on steep north-facing slopes). In turn, increasingly warm and wetter conditions increased the chance of recovery.
... El uso de combustibles fósiles en México es uno de los principales contribuyentes a la emisión de contaminantes atmosféricos, debido a que el 80% de ello es destinado a la generación de energía eléctrica (González, 2009). Sin embargo los ecosistemas también influyen de manera natural o inducida en la emisión de CO 2 , el cual es uno de los gases de efecto invernadero (GEI), debido a procesos biológicos naturales, deforestación e incendios forestales por mencionar algunos (Ordoñez, 2007), por otro lado son ellos los que almacenan, capturan o compensan las emisiones de dicho GEI, principalmente en forma de biomasa (CATIE, 2004;Montero et al., 2005). ...
Las áreas forestales son uno de los ecosistemas con potencial de almacenamiento de carbono debido a la diversidad florística existente, en México las áreas naturales protegidas son importantes almacenes de carbono que contribuyen a la mitigación del cambio climático. Por lo anterior, el propósito del estudio fue determinar la cantidad de dióxido de carbono capturado por la especie Pinus hartwegii Lindl. y almacenado como carbono en la biomasa aérea de la misma, descartando la masa orgánica (necromasa y hojarasca), que la especie pueda generar. Se calculó el potencial de captura de carbono anual, a través de los incrementos en volumen de la especie para generar una relación entre carbono y edad del arbolado. Se muestrearon 59 sitios de 1000 m2 a lo largo de la vertiente Nororiental del Parque Nacional Pico de Orizaba (PNPO). En esta zona la especie se presenta sobre 3400 m de altitud, algunas áreas de distribución han sido deforestadas. El carbono contenido por Pinus hartwegii Lindl. estimado por hectárea fue de 198.2 toneladas en árboles adultos y 0.1 t en renuevos. En toda el área de distribución (954 ha), los resultados arrojaron un total de 49 004.1 t de carbono con un incremento corriente anual de 0.58 t ha-1 para la vertiente nororiental del PNPO.
... From the total estimated aerial biomass, some fractions-leaves, small branches-lost because of defoliation or wildfire were subtracted. In the case of the Catalonian forest, the biomass weight equations [22] were applied to eucalypts and pines in the inventoried DBH distribution before and after the treatment, as the treated plots were measured again after thinning. The remaining dead biomass was collected and weighed, and the damages to soil and remaining stand were assessed in smaller subplots (4 m radius) following the methodologies proposed by [23] and [24]. ...
We studied two Eucalyptus globulus salvage clearcuts—after a wildfire and a Gonipterus attack—and a strong thinning on a dense Pinus pinaster stand which was regenerated 20 years after a wildfire and also affected by a Matsococcus pest. Biomass harvesting was performed using the feller-bundler Fixteri FX-15a, which was time-studied during several weeks using GNSS combined with an automatic weight/time registration system (WNexus-2®). Detailed in situ time studies were applied during shorter periods as well. The productivity equations found as main explanative factors for the salvage clearcuts the unit weight per tree and the felling reason (wildfire vs. pest); for the thinning, besides the unit weight, the percentage of extracted basal area explained the productivity. Biomass collection did not allow an economic positive balance: in the Gonipterus-affected plantation the cost was reduced to 125 €·ha−1, reaching a zero balance for unit weights greater than 33 kg (dry matter) per tree; the restoration cost in the pine stand was 265 €·ha−1, much lower than the cost without biomass harvesting. In the burned eucalypt, the zero cost would be achieved for a dry unit weight much greater than the observed values. Although Fixteri performance and utilization were remarkable, recommendations about possible improvements of its design and operation were concluded from the detailed time studies.
... Imhoff [57] reported the L-band saturation threshold to be 40 Mg ha −1 in different forest ecosystems (broad-leaved-USA, pine forests-USA, and pine forests-France). This value was closer to that observed in Mediterranean pine plantations (70 Mg ha −1 ) [71]. In contrast to more complex pine forests (e.g., boreal and hemi-boreal woods in Scandinavian countries [72]), the backscatter of Mediterranean pine forests appears to be more variable, which may be the result, considering that our assessments were made in a sparser forest [73]. ...
Currently, climate change requires the quantification of carbon stored in forest biomass. Synthetic aperture radar (SAR) data offers a significant advantage over other remote detection measurement methods in providing structural and biomass-related information about ecosystems. This study aimed to develop non-parametric Random Forest regression models to assess the changes in the aboveground forest biomass (AGB), basal area (G), and tree density (N) of Mediterranean pine forests by integrating ALOS-PALSAR, Sentinel 1, and Landsat 8 data. Variables selected from the Random Forest models were related to NDVI and optical textural variables. For 2015, the biomass models with the highest performance integrated ALS-ALOS2-Sentinel 1-Landsat 8 data (R2 = 0.59) by following the model using ALS data (R2 = 0.56), and ALOS2-Sentinel 1-Landsat 8 (R2 = 0.50). The validation set showed that R2 values vary from 0.55 (ALOS2-Sentinel 1-Landsat 8) to 0.60 (ALS-ALOS2-Sentinel 1-Landsat 8 model) with RMSE below 20 Mg ha−1. It is noteworthy that the individual Sentinel 1 (R2 = 0.49). and Landsat 8 (R2 = 0.47) models yielded equivalent results. For 2020, the AGB model ALOS2-Sentinel 1-Landsat 8 had a performance of R2 = 0.55 (validation R2 = 0.70) and a RMSE of 9.93 Mg ha−1. For the 2015 forest structural variables, Random Forest models, including ALOS PAL-SAR 2-Sentinel 1 Landsat 8 explained between 30% and 55% of the total variance, and for the 2020 models, they explained between 25% and 55%. Maps of the forests’ structural variables were generated for 2015 and 2020 to assess the changes during this period using the ALOS PALSAR 2-Sentinel 1-Landsat 8 model. Aboveground biomass (AGB), diameter at breast height (dbh), and dominant height (Ho) maps were consistent throughout the entire study area. However, the Random Forest models underestimated higher biomass levels (>100 Mg ha−1) and overestimated moderate biomass levels (30–45 Mg ha−1). The AGB change map showed values ranging from gains of 43.3 Mg ha−1 to losses of −68.8 Mg ha−1 during the study period. The integration of open-access satellite optical and SAR data can significantly enhance AGB estimates to achieve consistent and long-term monitoring of forest carbon dynamics.
... One is the proportionality factor of carbon in the CO 2 molecule, and the other one is the amount of biomass that can be fixed by the trees. The first term gives a value of 3.67, and the second term is taken as 50%, based on the experimental evaluation reported by Montero et al. 42 Figure 8 shows the basis for the calculations. Figure 9 shows the methodology used in this work for the design of the ecosystem. ...
Promoting nature-based carbon sinks may contribute to minimise global warming. Different forest types may have different carbon sink capacity. Many areas of central Spain are covered by coexisting patches of monospecific plantations of Pinus halepensis, established since the 1960’s, and native Quercus forest coppiced up to the 1960´s. We aimed to compare the carbon stock between both types of forests, considering both above and belowground compartments. In each plot, we measured the dimensions of every adult tree, the shrub cover, and we collected samples of litter and soil. The carbon pool of trees and shrubs was calculated using allometric equations, and for roots, litter, and soil, using the carbon content analysed in a laboratory or obtained from the literature. Carbon pools were analysed separately for three independent variables: plot type (Quercus/Pinus), tree basal area and slope. Overall, Quercus forests stored more carbon than Pinus plantations, thanks to a larger carbon stock in roots and shrubs in the former, which compensated for the larger aboveground carbon stock in tree biomass of Pinus plots. The carbon stock increased with basal area in all compartments except the soil. The carbon allocation pattern across compartments greatly varied between the two forest types, Pinus plots storing more than half (55%) of its carbon in the aboveground biomass of trees, while Quercus storing more carbon belowground (60%) in roots and soil. Given that belowground carbon stock is more resistant against disturbances, we conclude that native Quercus forests are more suitable for a long-term carbon storage.
Promoting nature-based carbon sinks is one of the effective ways to minimise global warming. Different types of forests, resulting from different land-use histories, may coexist under similar macro-environmental conditions, but their efficiency as carbon sinks may differ. In central Spain, many areas are covered by coexisting patches of monospecific plantations of Pinus halepensis , established since the 1950’s, and native Quercus forest coppiced up to the 1960´s. We aimed to compare the carbon stock between both types of forests, considering both above and belowground compartments, in La Alcarria region (central Spain). In each plot, the diameter at breast height and height were measured in every adult tree, along with shrub cover. Three subsamples of litter and soil were collected per plot. The carbon pool of trees and shrubs was calculated using allometric equations, and for roots, litter, and soil, using the carbon content analysed in a laboratory or obtained from the literature. Carbon pools were analysed separately for three independent variables: plot type ( Quercus / Pinus ), tree basal area (m ² /ha) and slope (°). Overall, Quercus forests stored more carbon than Pinus plantations. The carbon allocation pattern across compartments greatly varied between the two forest types, Pinus plots storing more than half (55%) of its carbon in the aboveground biomass of trees, while Quercus storing more carbon belowground (60%) in roots and soil. We conclude that native Quercus forests are more suitable for a long-term carbon storage, as belowground compartments represent an important part of its carbon storage capacity.
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