Severe dry winter affects plant phenology and carbon balance of a cork oak woodland understorey

Forest Conservation and Restoration Using the Emberger Index: Cork Oak as Study Case

The Mediterranean Basin is frequently stricken by huge disasters, and it represents an important biodiversity hotspot. Designing a synthetic approach, which is user-friendly with a low cost, that aims to summarize the main climatic factors that determine vegetation geographical ranges is a strategic solution to plan forest restoration actions and quickly act in cases of urgency. Here, we propose an updated version of the Emberger Index, applied to Quercus suber, an emblematic species of many ecosystems in the Mediterranean. Our investigation couples the latest spatially continuous climatic data, a high-resolution distribution map, and modelling techniques. The results evidence the effective benefits of the updated process, with insights into the optimal climatic requirements of a species within its real spatial domain, including projections for the next decades and the detection of putative refugia. Those outputs were not possible before because of a lack of data covering a certain area. Cork oak revealed an excellent study case, able to highlight the potentiality of Emberger’s approach, and understand the ecological amplitude and vulnerabilities of the target species. If genetic information is available, the Emberger Index can even be applied at the haplotype scale, thus benefitting the applied research. Such an index mirrors the optimal plasticity and physiologic characteristics of a species, supporting the decision makers in selecting the correct plants to use in future reforestation and restoration activities.

Spectral-Based Monitoring of Climate Effects on the Inter-Annual Variability of Different Plant Functional Types in Mediterranean Cork Oak Woodlands

Using remotely sensed data to estimate the biophysical properties of vegetation in woodlands is a challenging task due to their heterogeneous nature. The objective of this study was to assess the biophysical parameters of different vegetation types (cork oak trees, shrubs and herbaceous vegetation) in cork oak woodland through the analysis of temporal trends in spectral vegetation indices (VIs). A seven-year database (from 2011 until 2017) of in situ observations collected with a field spectroradiometer with a monthly basis was used and four VIs were derived, considered as proxies for several biophysical properties of vegetation such as biomass (Normalized Difference Vegetation Index—NDVI); chlorophyll content (MERIS Terrestrial Chlorophyll Index-MTCI), tissue water content (Normalized Difference Water Index—NDWI) and the carotenoid/chlorophyll ratio (Photochemical Reflectance Index—PRI). During the analyzed period, some key meteorological data (precipitation, temperature, relative air humidity and global radiation) were collected for the study site, aggregated at three different time-lags (short period (30 d), medium period (90 d) and hydrological period (HIDR)), and their relationship with VIs was analyzed. The results showed different trends for each vegetation index and vegetation type. In NDVI and NDWI, herbaceous vegetation showed a highly marked seasonal trend, whereas for MTCI, it was the cork oak and Cistus salvifolius, and for PRI, it was Ulex airensis that showed the marked seasonal trend. Shrubs have large differences depending on the species: the shallow-rooted Cistus salvifolius showed a higher seasonal variability than the deep-rooted Ulex airensis. Our results revealed the importance of temperature and precipitation as the main climatic variables influencing VI variability in the four studied vegetation types. This study sets up the relationships between climate and vegetation indices for each vegetation type. Spectral vegetation indices are useful tools for assessing the impact of climate on vegetation, because using these makes it easier to monitor the amount of “greenness”, biomass and water stress of vegetation than assessing the photosynthetic efficiency. Proximal remote sensing measurements are fundamental for the correct use of remote sensing in monitoring complex agroforest ecosystems, largely used to inform policies to improve resilience to drought, particularly in the Mediterranean region.

Using Digital Photography to Track Understory Phenology in Mediterranean Cork Oak Woodlands

Monitoring vegetation is extremely relevant in the context of climate change, and digital repeat photography is a method that has gained momentum due to a low cost–benefit ratio. This work aims to demonstrate the possibility of using digital cameras instead of field spectroradiometers (FS) to track understory vegetation phenology in Mediterranean cork oak woodlands. A commercial camera was used to take monthly photographs that were processed with the Phenopix package to extract green chromatic coordinates (GCC). GCC showed good agreement with the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) obtained with FS data. The herbaceous layer displayed a very good fit between GCC and NDVI (coefficient of determination, represented by r2 = 0.89). On the contrary, the GCC of shrubs (Cistus salviifolius and Ulex airensis) showed a better fit with NDWI (r2 = 0.78 and 0.55, respectively) than with NDVI (r2 = 0.60 and 0.30). Models show that grouping shrub species together improves the predictive results obtained with ulex but not with cistus. Concerning the relationship with climatic factors, all vegetation types showed a response to rainfall and temperature. Grasses and cistus showed similar responses to meteorological drivers, particularly mean maximum temperature (r = −0.66 and −0.63, respectively). The use of digital repeat photography to track vegetation phenology was found to be very suitable for understory vegetation with the exception of one shrub species. Thus, this method proves to have the potential to monitor a wide spectrum of understory vegetation at a much lower cost than FS.

Drought and heatwave impacts on semi-arid ecosystems' carbon fluxes along a precipitation gradient

The inter-annual variability (IAV) of the terrestrial carbon cycle is tightly linked to the variability of semi-arid ecosystems. Thus, it is of utmost importance to understand what the main meteorological drivers for the IAV of such ecosystems are, and how they respond to extreme events such as droughts and heatwaves. To shed light onto these questions, we analyse the IAV of carbon fluxes, its relation with meteorological variables, and the impact of compound drought and heatwave on the carbon cycle of two similar ecosystems, along a precipitation gradient. A four-year long dataset from 2016 to 2019 was used for the FLUXNET sites ES-LMa and ES-Abr, located in central (39°56'25″ N 5°46'28″ W) and southeastern (38°42'6″ N 6°47'9″ W) Spain. We analyse the physiological impact of compound drought and heatwave on the dominant tree species, Quercus ilex. Our results show that the gross primary productivity of the wetter ecosystem was less sensitive to changes in soil water content, compared to the dryer site. Still, the wetter ecosystem was a source of CO₂ each year, owing to large ecosystem respiration during summer; while the dry site turned into a CO₂ sink during wet years. Overall, the impact of the summertime compound event on annual CO₂ fluxes was marginal at both sites, compared to drought events during spring or autumn. This highlights that drought timing is crucial to determine the annual carbon fluxes in these semi-arid ecosystems. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Carbon Stock Estimations in a Mediterranean Riparian Forest: A Case Study Combining Field Data and UAV Imagery

This study aims to estimate the total biomass aboveground and soil carbon stocks in a Mediterranean riparian forest and identify the contribution of the different species and ecosystem compartments to the overall riparian carbon reservoir. We used a combined field and object-based image analysis (OBIA) approach, based on unmanned aerial vehicle (UAV) multispectral imagery, to assess C stock of three dominant riparian species. A linear discriminator was designed, based on a set of spectral variables previously selected in an optimal way, permitting the classification of the species corresponding to every object in the study area. This made it possible to estimate the area occupied by each species and its contribution to the tree aboveground biomass (AGB). Three uncertainty levels were considered, related to the trade-off between the number of unclassified and misclassified objects, leading to an error control associated with the estimated tree AGB. We found that riparian woodlands dominated by Acacia dealbata Link showed the highest average carbon stock per unit area (251 ± 90 tC ha−1) followed by Alnus glutinosa (L.) Gaertner (162 ± 12 tC ha−1) and by Salix salviifolia Brot. (73 ± 17 tC ha−1), which are mainly related to the stem density, vegetation development and successional stage of the different stands. The woody tree compartment showed the highest inputs (79%), followed by the understory vegetation (12%) and lastly by the soil mineral layer (9%). Spectral vegetation indices developed to suppress saturation effects were consistently selected as important variables for species classification. The total tree AGB in the study area varies from 734 to 1053 tC according to the distinct levels of uncertainty. This study provided the foundations for the assessment of the riparian carbon sequestration and the economic value of the carbon stocks provided by similar Mediterranean riparian forests, a highly relevant ecosystem service for the regulation of climate change effects.