Francisco Antonio García-Morote

Remote sensing technologies have been crucial in the monitoring and the assessment of forest carbon sequestration, emphasising the need for implementing Adaptive Forest management (AFM) as a vital strategy to decrease vulnerability to climate change impacts. Within this context, obtaining quantitative information on forest structure becomes necessary because AFM depends on the pre-existing forest structure and involves its subsequent modification. Consequently, this modification of forest structure has an impact on forest carbon sequestration. The main objective of this study is to validate the use of different satellite-based indices and algorithms as reliable quantitative estimators of forest structural parameters associated with its potential photosynthetic activity. Our study relies on the application of mobile terrestrial LiDAR for characterising vegetation structure at both individual tree and plot levels in Aleppo pine (Pinus halepensis L.) forests. As documented in the literature, these satellite-based indices were not consistent predictors of photosynthetic performance in evergreen species for most of the year. This was attributed to seasonal reductions in photosynthetic radiation-use efficiency that occurred without substantial declines in canopy greenness. Despite this finding, we hypothesize that the spatial information provided by these remote-based indices remains valid for capturing forest structural parameters relevant for carbon sequestration studies.To achieve this, we collected LiDAR scans from 21 forest compartments, ranging in size from 8 to 30 hectares, and 24 plots of approximately 0.2 hectares each. Thus, we captured detailed information about diameter at breast height, total tree height, and overall stand structure characteristics per hectare (i.e., number of trees, basal area, total timber volume and crown coverage). By comparing these ground-truth measurements with indices and algorithms derived from satellite imagery (i.e., NDVI, EVI, red edge index, NDWI), we evaluated their efficiency as estimators of forest structural parameters. Here, two spatial scales were considered: the 300-m resolution from Sentinel-3 for the forest compartments, and the 10-m resolution of Sentinel-2 for the plots. Our findings illustrated a good correlation between LiDAR-derived structural metrics and various selected indices. Once the robustness of these indices is confirmed, their application for downscaling satellite images related to gross primary productivity (GPP) or net ecosystem productivity (NEP) can be justified. This validation process will enhance our confidence in the use of remote sensing data to extract quantitative information about forest structure and will support its application for AFM purposes.

The recent consolidation of global carbon monitoring systems has been coupled with notable advances in methods for estimating the carbon cycle components in terrestrial ecosystems. These developments include a comprehensive assessment of the uncertainty and biases associated with these estimations. Gross primary productivity (GPP) is the most significant component of the terrestrial carbon cycle. Accurate estimation of GPP and its fluctuations over space and time is crucial not only for assessing ecosystem functioning and carbon balance but also for evaluating the resilience of ecosystems to adapt, survive and thrive in response to climate changes. Unfortunately, direct measurement of GPP through remote sensing (RS) signals is not feasible. Several RS signals associated with vegetation pigments and canopy structures can indeed function as proxies for GPP. These signals can be effectively integrated with various modelling approaches, considering different types and levels of complexity, to generate an estimation of global GPP at high spatio-temporal resolution.This study aims to explore how Sentinel satellites can improve the remote global GPP estimation. Specifically, we evaluated the quality of the 10-daily GDMP product of Sentinel-3, ensuring its reliability and credibility, with a specific focus on evergreen forests, particularly Aleppo pine stands. The outcomes of this study are expected to contribute to refining and calibrating GDMP algorithms for improved accuracy.The first aspect of our methodology involves the selection of several Aleppo pine forests across South-East Spain, where eddy covariance towers were installed, to study inter-site variability including soil characteristics, vegetation dynamics and forest management. Then, direct cross-comparisons between eddy covariance measurements and satellite observations were conducted for 4 independent study sites covering different periods (i.e., 2015-2018 and 2019-2023) to quantify uncertainties and biases in the GDMP product.The results revealed that the GDMP product exhibits improved performance during wet periods, ranging across sites from the highest R2 of 0.83 to the lowest R2 of 0.71, but it encounters challenges in accurately simulating Gross GPP under drought conditions. This funding was expected because some potentially important factors such as drought stress among others were omitted in the current computation model of Copernicus Global Land Service. Therefore, it is suggested that the product could be more accurately labelled as a potential GDMP. Similarly, our analysis showed that Aleppo pine demonstrates high plasticity in response to local conditions that is not adequately captured by this GDMP model.To address the challenges encountered in accurately simulating the GDMP product, we are working on developing a potential solution. This involves incorporating drought stress factors to enhance the model by integrating relevant physiological and environmental variables that influence specific responses of Aleppo pine to water shortage.

In this study, the effects of different stocking rates were quantified in three study areas in a Mediterranean forest (Cuenca, Spain) by applying a multiparametric soil quality index (SQI) developed from undisturbed forest soils (>40 years). The main objective was to advance the development and application of multiparametric indices that allow for soil condition assessment. To fulfill this objective, the effectiveness of the developed multiparametric soil quality index (SQI) was analyzed as an indicator of livestock impacts on soil in the Mediterranean forest. The control areas without livestock activity were forest stands of different ages (a thicket forest stand of 60 years), which were compared with areas subjected to various grazing intensities (areas with permanent livestock passage: a sheepfold that had been inactive for 2–3 years and an active sheepfold; areas with intermittent livestock passage: a bare-soil area, a pine stand and a scrubland). The applied multiparametric soil quality index (SQI) was sensitive to changes in forest ecosystems depending on the stocking rates. However, to obtain greater precision in the assessment of the effects of stocking rates, the multiparametric index was recalibrated to create a new index, the Soil Status Index by Livestock (SSI_L). The correlation between the quality ranges obtained with both indices in different study areas suggests that the SSI_L can be considered a livestock impact reference indicator in Mediterranean forest soils.

Macrochloa tenacissima (M. tenacissima), or esparto, is a perennial tussock grass that coexists with Pinus halepensis (P. halepensis) in semi-arid Mediterranean woodlands. This research was carried out to explore diurnal transpiration at leaf level in esparto grass under different levels of pine–esparto competition and in contrasting environmental soil water conditions. The measurement period spanned from the summer of 2020 to the spring of 2021. The relationship between transpiration and competition was conducted in open and closed P. halepensis stands, and the type of leaf (green, senescent) and the maturity of the esparto grass were taken into account. We observed a higher control of transpiration in green leaves, and the correlations between the transpiration and pine competition were noted exclusively in this type of leaf. Our results demonstrated a significant impact of pine competitors (closed stands) on the transpiration of esparto grass, particularly during seasons characterized by scenarios of high water demand: the summer drought period and the commencement of the growing and flowering period (spring). Furthermore, our findings revealed a greater response to transpiration in mature bushes compared to young ones under severe water stress, indicating a higher adaptation to drought by esparto as it ages. Although our results confirmed that PAR increased transpiration in all seasons and in both stands, which is attributable to the heliophilia of esparto grass, the site effects on transpiration could also be attributable to competition for water, especially during periods of drought. These results may have important implications for the dynamics and management of these semi-arid mixed woodlands, as well as the planning of reforestation programs aimed at restoring esparto grass formations.

Quantifying different stocking rates effects in three study areas placed at Mediterranean forest (Cuenca, Spain) was conducted by applying a multiparametric soil quality index, SQI, developed in undisturbed forest soils (> 40 years). The main objective is to advance in the development and application of multiparametric indexes which allow for soil condition assessment. For it, is analyse the effectiveness of a multiparametric soil quality index (SQI) as an indicator livestock impacts on the soil in mediterranean forests. Control areas without stocking rates were compared in forest stands with different age (Thicket forest stand, < 30 years; High polewood forest stand, 30-60 years; Old growth forest stand, > 60 years); with various intensity grazing areas (permanent livestock passage: inactive sheepfold for 2-3 years, and active sheepfold; intermittent livestock passage: bare soil, pine stand, scrubland). The multiparametric soil quality index (SQI) applied sensitive to changes in forest ecosystems depending of different stocking rates. However, for even more preci-sion to assess cattle alteration, multiparameter index recalibrated, creating a new one; Soil Status Index by Livestock (SSIL). Correlation between quality ranges obtained with both indexes in dif-ferent study areas suggest that SSIL can be considered a livestock impact reference indicator in Mediterranean forest soils.

Stipa tenacissima (S. tenacissima), or esparto, is a perennial tussock grass that coexists with Pinus halepensis (P. halepensis) in semi-arid mediterranean woodlands. This research was carried out to explore diurnal transpiration at leaf level in esparto grass under different levels of pine-esparto competition and in contrasting environmental conditions of soil water. The measurements were spanned from the summer 2020 to spring 2021. The relationship between transpiration and competence was conducted in open and closed P. halepensis stands and taken into account the type of leave (green, senescent) and the maturity of the esparto grass. We observed a higher control of transpiration in green leaves, and correlations between transpiration and soil water were noted exclusively in this type of leaf. Our results substantiated a significant impact of pine competitors on transpiration of esparto grass, particularly during seasons characterized by high water-demand scenarios: the summer drought period and the commencement of the growing and flowering period (spring). Furthermore, our findings confirmed a greater response to transpiration in mature bushes compared to young ones under severe water stress, denoting higher adaptation to drought as esparto ages. Our results may have important implications for the dynamics and management of these semi-arid mixed woodlands, as well as the planning of reforestation programs aimed at restoring esparto grass steppes.

This research analyzes how enzymatic and microbiological soil properties relate to site index (SI) and forest maturity (stand age) in Pinus nigra (P. nigra) even-aged forests. The soil parameters selected for multivariate analysis were four enzymatic activities (β-glucosidase, urease, dehydrogenase, and alkaline phosphatase), two microbiological properties (microbial biomass C and basal respiration), and five physicochemical parameters (TOC, N, P, pH, and soil water content). We used LiDAR, the digital elevation model, and the terrain model to obtain a result for the dominant height in each plot. The soil parameters were analyzed in the function of five site index classes (8, 11, 14, 17, and 20) and six age classes (50, 70, 90, 110, 170, and 210 years). Our findings emphasize that the dehydrogenase enzyme exhibited variations in response to both the site index and stand age. The activity of dehydrogenase positively correlated with sites characterized by a higher nutrient demand, particularly on young and poor-quality sites (lower SI), indicating activation. Therefore, dehydrogenase could serve as an index to elucidate both site quality and stand development in P. nigra stands, making it a potential indicator of forest ecosystem development.

Juniperus sabina L. (J. sabina L.) represents a compelling forest species due to the presence of metabolites in its leaves, which possess diverse applications in the fields of cosmetics, pharmaceuticals, and medicine. However, the species presents difficulties with regard to natural regeneration. This research aimed to improve the propagation conditions of J. sabina by using cuttings to enhance both the rooting percentage and essential oil (EO) content in the leaves. To do this, sampled cuttings underwent pretreatment with four different doses of coconut juice (25%, 50%, 75%, and 100%) within four substrates or rooting media, namely perlite, mixed substrate, pumice, and perlite–cocopeat. The study was carried out over the course of all four growing seasons to examine the impact of harvesting time as well. The best results for rooting were observed with the pretreatment of coconut juice at 25% in spring and in the substrate of perlite–cocopeat (37.10% rooting). The coconut juice also significantly increased the percentage of EOs in spring (0.82% of essential oil yield). Beta-pinene was the essential oil component with the highest representation (34.7% in fall), whereas in the spring, the best season to collect cuttings, the dominant component was nerodiol. Our study can contribute to the planning of culture systems using cuttings and to the control of the production of EOs from the leaves of J. sabina.