The effect of drought and subsequent precipitation pulse on productivity, species composition, and carbon fluxes of the herbaceous understorey in a cork oak woodland

In the Iberian Peninsula, the cork oak woodlands are of great ecological and socio-economic importance. These savanna-type woodlands are characterized by an herbaceous understorey, dominated by C3 annual species. The productivity and related ecosystem processes of this understorey are highly dependent on timing and magnitude of precipitation events. 

Climate change scenarios for the Iberian Peninsula suggest not only increasing air temperatures, but also the possibility of decreasing spring precipitation, accompanied by an increase in the interval between precipitation events, which might cause drought conditions to occur, with more severe effects on productivity and ecosystem processes. 

An experiment was carried out in southern Portugal to assess the effect of a drought treatment, with a subsequent extreme precipitation event, on the herbaceous component of managed cork oak woodland. The facility consisted of five plots with rainout shelters (2.5 x 2.5 m), which exclude normal rainfall inputs (drought treatment), and five non-sheltered control plots (control treatment). In the drought treatment, 193 mm of precipitation was excluded in the period from mid March to mid May, with a subsequent precipitation pulse of 50 mm in the middle of May. Variables measured included productivity, plant community composition, soil respiration and soil microbial activity. 

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Sensitivity of temperate grassland species to elevated atmospheric CO2 and the interaction with temperature and water stress

The annual cycle of growth of many temperate grasses is limited by low temperatures during the winter and spring and water stress during the summer. Climate change, induced by increase in the concentration of greenhouse gases in the atmosphere, can affect the growth and community structure of temperate grasslands in two ways. The first is directly through changes in atmospheric concentration of CO2 and the second is indirectly through changes in temperature and rainfall. At higher latitudes, where growth is largely temperature limited, it is probable that the direct effects of enhanced CO2 will be less than at low latitudes. However, interactions with increasing temperature and water stress are complex. Temperate grasslands range from intensively managed monocultures of sown species to species rich natural and semi-natural communities whose local distributions are controlled by variations in soil type and drainage. The different species can show marked differences in their responses to increasing CO2 concentrations, rising temperatures and water stress. This will probably result in major alterations in the community structure of temperate grasslands in the future. In addition to impacts on primary productivity and community structure, a long-term effect of elevated CO2 on grasslands is likely to be a significant increase in soil carbon storage. However, this may be counteracted by increases in temperature

The impact of changes in the timing of precipitation on the herbaceous understorey of Mediterranean evergreen oak woodlands

Climate change scenarios for the Iberian Peninsula predict increasing temperatures and increasingly variable precipitation regimes, which will challenge the sustainability and biodiversity of Mediterranean ecosystems such as the semi-natural evergreen oak woodlands. To assess the effects of precipitation variability on productivity, species composition and vegetation gas exchange of the understorey vegetation in a typical managed cork oak woodland, a large-scale rainfall manipulation experiment was established. We studied the impacts of a change in the timing of precipitation events on this ecosystem, without altering total annual precipitation inputs. The two water manipulation treatments were: ‘weekly watering treatment’, where natural conditions were simulated with a normal dry period of 7 days, and ‘3-weekly watering treatment’, with the normal dry period increased three-fold to 21 days. Our experimental precipitation patterns resulted in significant differences in temporal soil moisture dynamics between the two treatments. Average soil water content (SWC) at 3 cm depth during the growing season was 16.1 ± 0.17% and 15.8 ± 0.18% in the weekly and 3-weekly watering treatments, respectively, with a mere 5% increase in the variability of SWC when extending the dry period from one to three weeks. Water infiltration into deeper soil layers (>50 cm) was significantly higher in the 3-weekly watering treatment as compared to the weekly watering treatment. This might be beneficial to Quercus suber, the tree component in this ecosystem, as its extensive tree root system enables water acquisition from deeper soil layers. However, manipulation of the within-season precipitation variability, with a shift to fewer, but larger rain events, without change in total precipitation amount, had no significant effect on aboveground net primary productivity (ANPP), belowground net primary productivity (BNPP) and species composition, with average values of peak biomass of 385 g m−2 and 222 g m−2 for ANPP and BNPP, respectively. The experimental precipitation patterns did not result in significant differences in the vegetation gas exchange between the two watering treatments. The CO2 and H2O exchange parameters correlated well with air temperature. In addition, evapotranspiration showed a good correlation with SWC. Incorporating the data of SWC in the conceptual ‘bucket model’ showed that, independently of the watering regime, soil water availability during the life-cycle of these annual plants did not reach severe water stress conditions, which can explain the lack of a significant treatment effect in our study. In addition, our results showed that the annual plant community in these Mediterranean ecosystems is well adapted to short-term drought, through their phenological patterns and physiological adaptations

Modeling soil water dynamics and pasture growth in the montado ecosystem using MOHID land

The southern Iberian Peninsula is characterized by evergreen oak woodlands (locally known as montado), which constitute an important savanna-type agro-silvo-pastoral ecosystem. This ecosystem is facing a progressive decline for several reasons, with the foremost being overgrazing. Better management tools are necessary to accurately quantify the systems’ carrying capacity and the sustainable stocking rates that prevent land degradation. The purpose of this study was to determine whether the MOHID-Land model could adequately simulate soil water dynamics and pasture growth in the montado ecosystem. The study area was located in the Alentejo region of southern Portugal. The model successfully simulated soil water contents and aboveground biomass during the 2010–2011 and 2011–2012 growing seasons, producing acceptable errors of the estimates (0.015 RMSE 0.026 cm3 cm3; 279 RMSE 1286.5 kg ha1), and relatively high modeling efficiencies (0.481 EF 0.882). The model was further used to simulate the same variables for a longer period (1979/2009 seasons), to account for the effect of climate variability on model estimates. Water balance and dry biomass estimates were found to be significantly different between rainfed and irrigated pastures, as well as between the ten driest and ten wettest seasons, with the model responding well to climate variability. The results showed the potential of using the MOHID-Land model for improving pasture management in the montado ecosysteminfo:eu-repo/semantics/publishedVersio

Satellite-based estimation of soil organic carbon in Portuguese grasslands

Soil organic carbon (SOC) sequestration is one of the main ecosystem services provided by well-managed grasslands. In the Mediterranean region, sown biodiverse pastures (SBP) rich in legumes are a nature-based, innovative, and economically competitive livestock production system. As a co-benefit of increased yield, they also contribute to carbon sequestration through SOC accumulation. However, SOC monitoring in SBP require time-consuming and costly field work. Methods: In this study, we propose an expedited and cost-effective indirect method to estimate SOC content. In this study, we developed models for estimating SOC concentration by combining remote sensing (RS) and machine learning (ML) approaches. We used field-measured data collected from nine different farms during four production years (between 2017 and 2021). We utilized RS data from both Sentinel-1 and Sentinel-2, including reflectance bands and vegetation indices. We also used other covariates such as climatic, soil, and terrain variables, for a total of 49 inputs. To reduce multicollinearity problems between the different variables, we performed feature selection using the sequential feature selection approach. We then estimated SOC content using both the complete dataset and the selected features. Multiple ML methods were tested and compared, including multiple linear regression (MLR), random forests (RF), extreme gradient boosting (XGB), and artificial neural networks (ANN). We used a random cross-validation approach (with 10 folds). To find the hyperparameters that led to the best performance, we used a Bayesian optimization approach. Results: Results showed that the XGB method led to higher estimation accuracy than the other methods, and the estimation performance was not significantly influenced by the feature selection approach. For XGB, the average root mean square error (RMSE), measured on the test set among all folds, was 2.78 g kg−1 (r2 equal to 0.68) without feature selection, and 2.77 g kg−1 (r2 equal to 0.68) with feature selection (average SOC content is 13 g kg−1). The models were applied to obtain SOC content maps for all farms. Discussion: This work demonstrated that combining RS and ML can help obtain quick estimations of SOC content to assist with SBP managementinfo:eu-repo/semantics/publishedVersio

Clinical, electrophysiological, and cutaneous innervation changes in patients with bortezomib-induced peripheral neuropathy reveal insight into mechanisms of neuropathic pain

Bortezomib is a mainstay of therapy for multiple myeloma, frequently complicated by painful neuropathy. The objective of this study was to describe clinical, electrophysiological, and pathological changes of bortezomib-induced peripheral neuropathy (BiPN) in detail and to correlate pathological changes with pain descriptors. Clinical data, nerve conduction studies, and lower leg skin biopsies were collected from 22 BiPN patients. Skin sections were immunostained using anti-protein gene product 9.5 (PGP9.5) and calcitonin gene-related peptide (CGRP) antibodies. Cumulative bortezomib dose and clinical assessment scales indicated light-moderate sensory neuropathy. Pain intensity >4 (numerical rating scale) was present in 77% of the patients. Median pain intensity and overall McGill Pain Questionnaire (MPQ) sum scores indicated moderate to severe neuropathic pain. Sural nerve sensory nerve action potentials were abnormal in 86%, while intraepidermal nerve fiber densities of PGP9.5 and CGRP were not significantly different from healthy controls. However, subepidermal nerve fiber density (SENFD) of PGP9.5 was significantly decreased and the axonal swelling ratio, a predictor of neuropathy, and upper dermis nerve fiber density (UDNFD) of PGP9.5, presumably representing sprouting of parasympathetic fibers, were significantly increased in BiPN patients. Finally, significant correlations between UDNFD of PGP9.5 versus the evaluative Pain Rating Index (PRI) and number of words count (NWC) of the MPQ, and significant inverse correlations between SENFD/UDNFD of CGRP versus the sensory-discriminative MPQ PRI/NWC were found. BiPN is a sensory neuropathy, in which neuropathic pain is the most striking clinical finding. Bortezomib-induced neuropathic pain may be driven by sprouting of parasympathetic fibers in the upper dermis and impaired regeneration of CGRP fibers in the subepidermal layer

Climate control of terrestrial carbon exchange across biomes and continents

Peer reviewe

Sensitivity of temperate grassland species to elevated atmospheric CO2 and the interaction with temperature and water stress

Monien lauhkean vyöhykkeen nurmikasvien kasvua rajoittavat talvella ja keväällä kylmyys ja kesällä kuivuus. Ilmaston muutos, jonka aiheuttaa ilmakehän kasvihuonekaasujen pitoisuuden kasvu, voi vaikuttaa suoraan ja epäsuorasti nurmien kasvuun ja niiden lajikoostumukseen. Ilmakehän hiilidioksidipitoisuuden muutos vaikuttaa suoraan kasvien kasvuun. Toisaalta ilmaston lämpeneminen ja sademäärän muutokset vaikuttavat epäsuorasti. On todennäköistä, että hiilidioksidipitoisuuden nousu vaikuttaa enemmän matalilla leveysasteilla kuin korkeammilla leveysasteilla, missä lämpötila usein rajoittaa kasvua. Lämpötilan ja veden saannin muutosten yhteisvaikutukset ovat kuitenkin monimutkaisia. Lauhkean kasvuvyöhykkeen nurmet vaihtelevat voimaperäisesti viljellyistä monokulttuureista monilajisiin kasvustoihin, joiden paikalliseen esiintymiseen vaikuttavat maalaji ja maan kuivatusolosuhteet. Kohonnut hiilidioksidipitoisuus, lämpötila ja kuivuus voivat vaikuttaa hyvin eri tavoin eri nurmikasveihin, mikä todennäköisesti tulee muuttamaan suuresti nurmien lajikoostumusta tulevaisuudessa. Kohonnut hiilidioksidipitoisuus saattaa pitkällä aikavälillä merkittävästi lisätä maahan varastoituneen hiilen määrää. Lämpötilan kohoaminen voi kuitenkin kumota tätä ilmiötä.The annual cycle of growth of many temperate grasses is limited by low temperatures during the winter and spring and water stress during the summer. Climate change, induced by increase in the concentration of greenhouse gases in the atmosphere, can affect the growth and community structure of temperate grasslands in two ways. The first is directly through changes in atmospheric concentration of CO2 and the second is indirectly through changes in temperature and rainfall. At higher latitudes, where growth is largely temperature limited, it is probable that the direct effects of enhanced CO2 will be less than at low latitudes. However, interactions with increasing temperature and water stress are complex. Temperate grasslands range from intensively managed monocultures of sown species to speciesrich natural and semi-natural communities whose local distributions are controlled by variations in soil type and drainage. The different species can show marked differences in their responses to increasing CO2 concentrations, rising temperatures and water stress. This will probably result in major alterations in the community structure of temperate grasslands in the future. In addition to impacts on primary productivity and community structure, a long-term effect of elevated CO2 on grasslands is likely to be a significant increase in soil carbon storage. However, this may be counteracted by increases in temperature.vokKohonneen hiilidioksidipitoisuuden, lämpötilan ja kuivuuden vaikutus nurmikasveihi

Sensitivity of temperate grassland species to elevated atmospheric CO2 and the interaction with temperature and water stress

Selostus: Kohonneen hiilidioksidipitoisuuden, lämpötilan ja kuivuuden vaikutus nurmikasveihi