Vegetative Functions Research Articles

Chronic treatment with corticosterone increases the number of tyrosine hydroxylase-expressing cells within specific nuclei of the brainstem reticular formation.

Cushing's syndrome is due to increased glucocorticoid levels in the body, and it is characterized by several clinical alterations which concern both vegetative and behavioral functions. The anatomical correlates of these effects remain largely unknown. Apart from peripheral effects induced by corticosteroids as counter-insular hormones, only a few reports are available concerning the neurobiology of glucocorticoid-induced vegetative and behavioral alterations. In the present study, C57 Black mice were administered daily a chronic treatment with corticosterone in drinking water. This treatment produces a significant and selective increase of TH-positive neurons within two nuclei placed in the lateral column of the brainstem reticular formation. These alterations significantly correlate with selective domains of Cushing's syndrome. Specifically, the increase of TH neurons within area postrema significantly correlates with the development of glucose intolerance, which is in line with the selective control by area postrema of vagal neurons innervating the pancreas. The other nucleus corresponds to the retrorubral field, which is involved in the behavioral activity. In detail, the retrorubral field is likely to modulate anxiety and mood disorders, which frequently occur following chronic exposure to glucocorticoids. To our knowledge, this is the first study that provides the neuroanatomical basis underlying specific symptoms occurring in Cushing's syndrome.

Analysis of water quality indexes and their relationships with vegetation using self-organizing map and geographically and temporally weighted regression

Natural vegetation has been proved to promote water purification in previous studies, while the relevant laws has not been excavated systematically. This research explored the relationships between vegetation cover and water quality indexes in Liaohe River Basin in China combined with self-organizing map (SOM) and geographically and temporally weighted regression (GTWR) innovatively and systematically based on the distributing heterogeneity of water quality conditions. Results showed that the central and northeast regions of the study area had serious organic and nutrient pollution, which needed targeted treatment. And SOM verified that high vegetation coverage with retention potential of organic and inorganic pollutants as well as nutrients improved water quality to some degree, while the excessive discharges of pollutants still had serious threats to nearby water environment despite the purification function of vegetation. GTWR indicated that the waterside vegetation was beneficial for dissolved oxygen increasing and contributed to the decreasing of organic pollutants and inorganic pollutants with reducibility. Natural vegetation also obsorbed nutrients like TN and TP to some degree. However, the retential potential of nitrogen and organic pollutants became not obvious when there were heavy pollution, which demonstrated that pollution sources should be controlled despite the purification function of vegetation. This study implied that natural vegetation purified water quality to some degree, while this function could not be revealed when there was too heavy pollution. These findings underscore that the pollutant discharge should be controlled though the natural vegetation in ecosystem promoted the purification of water bodies.

Non-linear interactions between vegetation and terrestrial water storage in Australia

• Revisit analysis shows that vegetation growth is water-limited in 60% of Australia. • Non-linear interactions between NDVI and TWS occur in 58% of Australia. • The area where high temperatures limit vegetation growth has nearly tripled recently. Vegetation conditions are deeply dependent on water availability. Conversely, vegetation can also affect terrestrial water conditions by modifying evapotranspiration and other hydrological processes. Knowledge of the interactions between vegetation and land water conditions are required for understanding and simulating terrestrial water and carbon budgets in response to climate change. For the first time, in this study, a non-linear Granger causality approach is applied to investigate the water-vegetation interactions over Australia. They are characterized by respectively the normalized difference vegetation index (NDVI) and the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS). The results indicate that non-linear interactions between TWS and NDVI occur in over half (58.4%) of the continent, which are more likely to take place for grasslands, followed by shrublands, agricultural lands, savannas, and forests. A revisit-analysis of the dominant driver among water, temperature, and radiation for vegetation conditions confirms that Australia is mostly water limited. Although the total area of primarily water-limited regions has slightly decreased from 67.0% in the earlier sub-period (1985–1999) to 65.2% in the more recent sub-period (2000–2015), it accounts for a much larger proportion of the continent than that of temperature- and radiation-limited regions in both sub-periods. The spatial coverage of regions where temperature is the dominant factor has nearly tripled for the recent sub-period. This could most likely be due to the warmer climate that exacerbates the limitation of high temperature on vegetation growth and functioning. These results contribute to an improved understanding of Australia’s terrestrial water and carbon cycles. The GRACE TWS shows to be highly relevant data for such investigations at a continental scale.

Dynamic Global Vegetation Models: Searching for the balance between demographic process representation and computational tractability

Vegetation is subject to multiple pressures in the 21st century, including changes in climate, atmospheric composition and human land-use. Changes in vegetation type, structure, and function also feed back to the climate through their impact on the surface-atmosphere fluxes of carbon and water. Dynamic Global Vegetation Models (DGVMs), are therefore key component of the latest Earth System Models (ESMs). Model projections for the future land carbon sink still span a wide range, in part due to the difficulty of representing complex ecosystem and biogeochemical processes at large scales (i.e. grid lengths ≈ 100km). The challenge for developers of DGVMs is therefore to find an optimal balance between detailed process representation and the ability to scale-up. We categorise DGVMs into four groups; Individual, Average Area, Two Dimensional Cohort and One Dimensional Cohort models. From this we review popular methods used to represent dynamic vegetation within the context of Earth System modelling. We argue that the minimum level of complexity required to effectively model changes in carbon storage under changing climate and disturbance regimes, requires a representation of tree size distributions within forests. Furthermore, we find that observed size distributions are consistent with Demographic Equilibrium Theory, suggesting that One Dimensional Cohort models with a focus on tree size, offer the best balance between computational tractability and realism for ESM applications.

Development of a Fermented Bitter Gourd (Momordica charantia)–Grape Beverage Using Optimized Conditions

Bitter gourd beverages are well acclaimed for their health benefits, which have propelled their consumption. The beverages are prepared through a fermentation process, which is one of the oldest means of preserving and enhancing the flavour of many foods. Optimized conditions for the fermentation of a bitter gourd–grape beverage were investigated in our previous study. In the present study, a statistical comparison (one-way analysis of variance (ANOVA), Tukey’s honestly significant difference (HSD) test and an independent t-test)) of grape juice, bitter gourd juice and the fermented bitter gourd–grape beverage (with and without enzymes) was carried out to find significant differences among the products. Alcohol was found to be consistent for the four products with p > 0.05, whereas significant differences (p ≤ 0.05) in the pH, antioxidant activity (ferric reducing antioxidant assay (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2-azinobis (3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS)), total titratable acidity (TTA), total soluble solids (TSS), total flavonoid content (TFC) and total phenolic content (TPC) were observed. The fermented bitter gourd–grape beverage (FBGGB) with enzymes had the highest antidiabetic potential content (27.07). The data obtained demonstrate that fermentation indeed enhances the biochemical function of vegetables (in this case, bitter gourd) and could thus be considered for the commercial processing of bitter gourd.

From vegetation ecology to vegetation science: current trends and perspectives

Vegetation is a key biosphere component to supporting biodiversity on Earth, and its maintenance and proper functioning are essential to guarantee the well-being of humankind. From a broad perspective, a fundamental goal of vegetation ecology is to understand the roles of abiotic and biotic factors that affect vegetation structure, distribution, diversity, and functioning, considering the relevant spatial and temporal scales. In this contribution, we reflect on the difficulties and opportunities to accomplish this grand objective by reviewing recent advances in the main areas of vegetation ecology. We highlight theoretical and methodological challenges and point to alternatives to overcome them. Our hope is that this contribution will motivate the development of future research efforts that will strengthen the field of vegetation ecology. Ultimately, vegetation science will continue to provide a strong knowledge basis and multiple theoretical and technological tools to better face the current global environmental crisis and to address the urgent need to sustainably conserve the vegetation cover of our planet in the Anthropocene.

Responses of intraspecific and interspecific variations of plant functional traits to grazing in degraded grassland

Understanding the responses of functional trait variation for grassland plants to grazing disturbance is highly helpful to clarify the community assembly mechanism, functional diversity maintenance, plant adaptation and their strategies. We investigated plant functional traits (plant height, root length, leaf area, root area, leaf dry matter content, shoot dry matter content, root dry matter content, specific leaf area, specific root length and root/ shoot ratio) and the responses of their variation characteristics to grazing disturbance in enclosure and grazing grasslands in Horqin Sandy Land. The results showed that the interspecific variation of functional trait was obviously higher than the intraspecific variation in degraded grassland. The relative contribution of interspecific variation to the overall trait variation ranged from 70.2% to 95.1%, while that of intraspecific variation only contributed 4.9% to 29.8%. However, that did not imply the intraspecific variation could be ignored in the community assembly. The interspecific variation in grazing grassland was lower than that in enclosed grassland, while the intraspecific variation increased but the interspecific variation decreased in grazing grassland. Grazing resulted in the decrease of leaf area and leaf dry matter content but the increase of specific root length for pastoral-resistant grasses. However, pastoral-tolerant forbs would improve their dominance in the community by decreasing specific root length and increa-sing leaf area and leaf dry matter content. The traits sensitive to grazing were leaf area, leaf dry matter content, specific root length, and specific leaf area. Leaf traits and root traits were significantly positively correlated within and with each other. Grazing would enhance the synergy of root traits while reduce the synergy of leaf traits. That meant grazing could change the trade-off strategy of functional traits in individual and population levels, and thus affect vegetation structure and function in community level.

Fires, vegetation, and human—The history of critical transitions during the last 1000 years in Northeastern Mongolia

Fires are natural phenomena that impact human behaviors, vegetation, and landscape functions. However, the long-term history of fire, especially in the permafrost marginal zone of Central Asia (Mongolia), is poorly understood. This paper presents the results of radiocarbon and short-lived radionuclides (210Pb and 137Cs) dating, pollen, geochemical, charcoal, and statistical analyses (Kohonen's artificial neural network) of sediment core obtained from Northern Mongolia (the Khentii Mountains region). Therefore, we present the first high-resolution fire history from Northern Mongolia covering the last 1000 years, based on a multiproxy analysis of peat archive data. The results revealed that most of the fires in the region were likely initiated by natural factors, which were probably related to heatwaves causing prolonged droughts. We have demonstrated the link between enhanced fires and "dzud", a local climatic phenomenon. The number of livestock, which has been increasing for several decades, and the observed climatic changes are superimposed to cause "dzud", a deadly combination of droughts and snowy winter, which affects fire intensity. We observed that the study area has a sensitive ecosystem that reacts quickly to climate change. In terms of changes in the vegetation, the reconstruction reflected climate variations during the last millennium, the degradation of permafrost and occurrence of fires. However, more sites with good chronologies are needed to thoroughly understand the spatial relationships between changing climate, permafrost degradation, and vegetation change, which ultimately affect the nomadic societies in the region of Central and Northern Mongolia.

Population and habitat connectivity of Grevy's zebra Equus grevyi, a threatened large herbivore in degraded rangelands

Land degradation, competition with livestock, infrastructure development, and climate change have reduced habitat availability and reduced population connectivity for many wildlife species. Large herbivores are particularly vulnerable, and approximately 90 % of global large herbivore diversity is in Africa. The endangered Grevy's zebra illustrates the decline and fragmentation of large mammalian herbivore populations, with extensive population loss across their range in northern Kenya and Ethiopia. A better understanding of the factors influencing population connectivity and movement patterns of Grevy's zebra, highlighted in national strategies, offers valuable insights for other threatened species.Using location and movement data for Grevy's zebra from GPS collars deployed between 2010 and 2017, seasonally-explicit landscape resistance was modelled as a function of water availability, vegetation, cattle density, topography and proximity to roads and settlements. Maximum entropy models identified habitat suitability during wet and dry seasons respectively. Population connectivity analyses using least-cost paths and circuit theory determined landscape resistance to movement and highlighted linkage pathways. Movement was modelled over a range of distances, using GPS data.Grevy's zebra reliance on water was confirmed, with an apparent trade-off between habitat suitability and proximity to people. Connectivity models highlighted potentially isolated populations, with reduced seasonal connectivity being most apparent between north to south distribution areas. These results can inform sustainable land management planning in northern Kenya and offer support for Grevy's zebra conservation actions. These results also provide insights that can be applied to other large herbivores occurring in this region and in arid or degraded environments elsewhere.

Day's periodicity of vegetative functions for swimmers taking into account the phases of days-long biorhythms

In this work we studied day's periodicity of indexes of cardiovascular and respiratory systems for swimmers depending on the phases of physical multi-day biorhythms at the beginning of the competitive stage of preparation. In a sports camp 5 girls and 11 young men age 15-17 masters of sports and candidates for master of sports at swimming, took part at scientific research. The presence of two peaks of sizes of indexes of vegetative functions which are observed after the first and third training is educed. According to the level of functional readiness, the subjects were divided into 3 groups: with a good functional state, with its deterioration as a result of an acute respiratory disease or overwork, and with a satisfactory state. An assessment of the functional state of each athlete was made at the beginning and end of the training camp. Health status, sleep, well-being assessment, etc. about swimmers was taken into account in the analysis of the material. During the exchange of rest, the indicators of vegetative functions most fully reflect the state of the athlete on the day of the examination.

Impact of the numerical solution approach of a plant hydrodynamic model (v0.1) on vegetation dynamics

Abstract. Numerous plant hydrodynamic models have started to be implemented in vegetation dynamics models, reflecting the central role of plant hydraulic traits in driving water, energy, and carbon cycles, as well as plant adaptation to climate change. Different numerical approximations of the governing equations of the hydrodynamic models have been documented, but the numerical accuracy of these models and its subsequent effects on the simulated vegetation function and dynamics have rarely been evaluated. Using different numerical solution methods (including implicit and explicit approaches) and vertical discrete grid resolutions, we evaluated the numerical performance of a plant hydrodynamic module in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES-HYDRO version 0.1) based on single-point and global simulations. Our simulation results showed that when near-surface vertical grid spacing is coarsened (grid size >10 cm), the model significantly overestimates aboveground biomass (AGB) in most of the temperate forest locations and underestimates AGB in the boreal forest locations, as compared to a simulation with finer vertical grid spacing. Grid coarsening has a small effect on AGB in the tropical zones of Asia and South America. In particular, coarse surface grid resolution should not be used when there are large and prolonged water content differences among soil layers at depths due to long dry-season duration and/or well-drained soil or when soil evaporation is a dominant fraction of evapotranspiration. Similarly, coarse surface grid resolution should not be used when there is lithologic discontinuity along the soil depth. This information is useful for uncertainty quantification, sensitivity analysis, or the training of surrogate models to design the simulations when computational cost limits the use of ensemble simulations.

Consequences of Grazing Cessation for Soil Environment and Vegetation in a Subalpine Grassland Ecosystem.

Areas covered by seminatural grasslands have been in constant decline for decades in Europe. This trend is particularly strong for mountain territories, where such traditional agricultural practices as cattle grazing are no longer economically feasible. This study was conducted in the subalpine pasture of Cinte Tesino (TN, Italy), where local farmers have applied the following different management strategies: shorter and longer grazing durations during the season and a complete abandonment for the last 15 years. We aimed to study how these different management strategies impact the functioning and diversity of vegetation and the chemical and biological characteristics of the soil. Species richness was higher in plots subjected to longer grazing with a prevalence of D. caespitosa in terms of biomass share. A decline in species richness in abandoned plots was accompanied by an increase in the share of other graminoids in collected biomass. A concomitant increase in leaf N concentration and light availability in grazed plots resulted in higher photosynthetic efficiency in some species, as revealed by the δ13C of plant tissues. Soils under grazing were characterised by a higher concentration of total and extractable N, almost doubled microbial biomass C and increased extracellular enzymes activity, evidencing nutrient cycling mobilization. While the microbial pool was characterised by lower mineralization rates, C was lost from the soil with 15 years of abandonment. The longer grazing season demonstrated to be the most beneficial, promoting species richness, C accumulation and better soil microbial functioning. A change in soil pH from strongly acidic to moderately acidic with longer grazing is likely one of the important factors adding to the success in the functioning of primary producers and decomposers in this site.

Remote sensing from unoccupied aerial systems: Opportunities to enhance Arctic plant ecology in a changing climate

AbstractThe Arctic is warming at a faster rate than any other biome on Earth, resulting in widespread changes in vegetation composition, structure and function that have important feedbacks to the global climate system. The heterogeneous nature of arctic landscapes creates challenges for monitoring and improving understanding of these ecosystems, as current efforts typically rely on ground, airborne or satellite‐based observations that are limited in space, time or pixel resolution.The use of remote sensing instruments on small unoccupied aerial systems (UASs) has emerged as an important tool to bridge the gap between detailed, but spatially limited ground‐level measurements, and lower resolution, but spatially extensive high‐altitude airborne and satellite observations. UASs allow researchers to view, describe and quantify vegetation dynamics at fine spatial scales (1–10 cm) over areas much larger than typical field plots. UASs can be deployed with a high degree of temporal flexibility, enabling observation across diurnal, seasonal and annual time‐scales.Here we review how established and emerging UAS remote sensing technologies can enhance arctic plant ecological research by quantifying fine‐scale vegetation patterns and processes, and by enhancing the ability to link ground‐based measurements with broader‐scale information obtained from airborne and satellite platforms.Synthesis. Improved ecological understanding and model representation of arctic vegetation is needed to forecast the fate of the Arctic in a rapidly changing climate. Observations from UASs provide an approach to address this need, however, the use of this technology in the Arctic currently remains limited. Here we share recommendations to better enable and encourage the use of UASs to improve the description, scaling and model representation of arctic vegetation.

Physiological dynamics dominate the response of canopy far-red solar-induced fluorescence to herbicide treatment

Solar-induced chlorophyll fluorescence (SIF) has shown great potential for detecting changes in vegetation function under herbicide stress. However, how physiological (ΦF, canopy SIF emission efficiency) and non-physiological (e.g., structure and illumination) dynamics regulate canopy SIF, and the coupling between SIF and gross primary production (GPP) under herbicide stress remains unclear. Here, we conducted continuous eddy covariance flux and far-red SIF measurements during the early stage of maize in an herbicide-resistant maize field, where herbicide exclusively affects weeds. We investigated the performance of SIF, GPP, and vegetation indices (VIs) in capturing herbicide stress and then explored the sensitivity of SIF to the effects of herbicide treatments by disentangling canopy SIF into the physiological (ΦF) and non-physiological components (NIRvP). We found that SIF rapidly increased in response to the herbicide and that GPP decreased, and that both were more responsive than VIs in capturing the early effects of herbicides. Thus, the opposing responses in SIF and GPP disrupted their otherwise linear relationship during herbicide treatment. More importantly, we found that the increased ΦF dominated the variation of SIF during the early stages of herbicide stress, while the influence of NIRvP was prominent in the variability of SIF in the absence of herbicide. By unraveling its physiological and non-physiological contributions, our findings advance our understanding of how SIF responds to herbicide stress in heterogeneous cropland and will improve our interpretation of SIF as a tool for monitoring photosynthesis.

Ecosystem Gross Primary Productivity After Autumn Snowfall and Melt Events in a Mountain Meadow

AbstractVegetation productivity is increasing in the U.S. Northern Great Plains but decreasing in some nearby Northern Rocky Mountain grasslands due to increases in aridity. It is unclear if decreases to montane grassland productivity from drying autumns can be partly offset by late‐season green‐ups after precipitation events. These include the multiple snowfall and snowmelt periods that often characterize the summer‐to‐winter transition, but are difficult to observe due to logistical constraints. Here, we quantify changes to vegetation indices and ecosystem carbon uptake that occurs after snowfall and melt in climatological autumn in a montane grassland in Montana, USA using eddy covariance, phenological camera, and remote sensing analyses. Carbon dioxide flux follows a diurnal pattern after autumn snowmelt events despite overall ecosystem C loss, suggesting that post‐snowmelt photosynthesis helps dampen C loss during autumn and provides fresh photosynthate to support ecosystem functioning. Light‐saturated photosynthesis after three snow events was not statistically different than before snowfall (∼6 μmol CO2 m−2 s−1 in 2016 and ∼2.5 μmol CO2 m−2 s−1 in 2017). Observations are consistent with the notion that canopy photosynthesis is resistant, rather than resilient, to autumn snow. MODIS indicates that post‐snow greenups can occur, but not every year. Such events likely play a small role in the annual ecosystem carbon balance but may be disproportionately important for organisms faced with dwindling late‐season forage. Future efforts should seek to understand the community and ecosystem consequences of vegetation functioning during autumn as part of an expanded effort to understand phenological changes during this under‐studied and changing time of year.

Climatic and edaphic‐based predictors of normalized difference vegetation index in tropical dry landscapes: A pantropical analysis

AbstractAimSpatial patterns in resource supply drive variability in vegetation structure and function, yet quantification of this variability for tropical dry forests (TDFs) remains rudimentary. Several climate‐driven indices have been developed to classify and delineate TDFs globally, but there has not been a climo‐edaphic synthesis of these indices to assess and delineate the extent of TDFs. A statistical climo‐edaphic synthesis of these indices is therefore required.LocationPantropical.Time periodModern.Major taxa studiedVascular plants.MethodsWe assembled most known prior descriptions of TDFs into a single data layer and assessed statistically how the TDF biome, which we call tropical dry landscapes (TDLs) composed of forest and non‐forest vegetation, varied with respect to the normalized difference vegetation index (NDVI) sensed by MODIS (250 m pixel resolution). We examined how the NDVI varied with respect to mean annual temperature (MAT) and rainfall (MAR), precipitation regime, evapotranspiration and the physical, chemical and biological properties of TDL soils.ResultsOverall, the NDVI varied widely across TDLs, and we were able to identify five principal NDVI categories. A regression tree model captured 90% of NDVI variation across TDLs, with 14 climate and soil metrics as predictors. The model was then pruned to use only the three strongest metrics. These included the Lang aridity index, total evapotranspiration (ET) and MAT, which aligned with identified NDVI thresholds and accounted for 70% of the variation in NDVI. We found that across a global TDL distribution, ET was the strongest positive predictor and MAT the strongest negative predictor of the NDVI.Main conclusionsThe remote sensing‐based approach described here provides a comprehensive and quantitative biogeographical characterization of global TDL occurrence and the climatic and edaphic drivers of these landscapes.

Predicting resilience through the lens of competing adjustments to vegetation function

There is a pressing need to better understand ecosystem resilience to droughts and heatwaves. Eco-evolutionary optimization approaches have been proposed as means to build this understanding in land surface models and improve their predictive capability, but competing approaches are yet to be tested together. Here, we coupled approaches that optimize canopy gas exchange and leaf nitrogen investment, respectively, extending both approaches to account for hydraulic impairment. We assessed model predictions using observations from a native Eucalyptus woodland that experienced repeated droughts and heatwaves between 2013 and 2020, whilst exposed to an elevated [CO2 ] treatment. Our combined approaches improved predictions of transpiration and enhanced the simulated magnitude of the CO2 fertilization effect on gross primary productivity. The competing approaches also worked consistently along axes of change in soil moisture, leaf area, and [CO2 ]. Despite predictions of a significant percentage loss of hydraulic conductivity due to embolism (PLC) in 2013, 2014, 2016, and 2017 (99th percentile PLC > 45%), simulated hydraulic legacy effects were small and short-lived (2 months). Our analysis suggests that leaf shedding and/or suppressed foliage growth formed a strategy to mitigate drought risk. Accounting for foliage responses to water availability has the potential to improve model predictions of ecosystem resilience.

Soil properties and geomorphic processes influence vegetation composition, structure, and function in the Cerrado Domain

Soil properties and geomorphic processes influence vegetation composition, structure, and function in the Cerrado Domain

Penyerapan Karbon Pada Ekosistem Lamun Di Kawasan Perairan Gili Maringkik Lombok, Provinsi Nusa Tenggara Barat, Indonesia

Seagrass beds are an important vegetation for reducing the impact of global warming besides the function of forest and mangroves vegetation. The research aims to find the composition of seagrass species, density, seagrass coverage, seagrass standing biomass, seagrass standing carbon and substrate carbon.The research was conducted in Gili Maringkik, Lombok, Indonesia. The research included observation of species composition and the sample was collected from 0.5 ×0.5 m plot area. Total plot area was 25 on five lanes with the space between plots 25 m and between lanes100 m.The researcher found that there were eight seagrass species (two families, six genera): Cymodocea rotundata, Cymodocea serrulata, Enhalus acoroides, Halodule pinifolia, Halophila minor, Halophila spinulosa, Syringodium isoetifolium and Thalassia hemprichii. Cymodocea rotundata(506.40±187.809 stand.m-2) was the species of highest density and while the species of Thalassia hemprichii (36.52±30.004 %) wasthe species of highest coverage. Total of seagrass standing biomass in Gili Maringkik was1081.85 g.DW.m-2with the carbon stock of seagrass beds was 483.86g.C.m-2 and substrate carbon content was0.09%–0.49%. The total carbon stock of seagrass beds in Gili Maringkik has 153.96 ton.C(4.84 ton.C.Ha-1).

Spatio-temporal assessment of drought in the semi-arid region of Algerian steppe through index and remote sensing

The scarcity of annual rainfall, which sometimes spreads over successive years, causes persistent droughts. In order to study the drought severity on the Algerian steppe, we analysed precipitation data (1985–2015) from the weather stations of Ain Sefra, El Bayadh, Tiaret and Djelfa, using drought meteorological indices: the mean deviation, the standardised precipitation index, the rainfall index and the frequency analysis of the rainfall series. Thus, we adopted the diachronic study by satellite remote sensing for the years 2002 (the driest year) and 2009 (the wettest year), which allowed us to better understand the evolution of the steppe rangelands surface and to better interpret their spatial-temporal changes. Drought, as determined by the mean deviation index, occurred during two periods (in sequence and corresponds to 55% the sequences of deficit years), one over 12 years (from 1994/1993 to 2006/2005) and the other over 5 years (1985–1990) and with isolated years. The results of the diachronic study of the vegetation change demonstrate the obvious divergence of the vegetation cover between 2002 and 2009. Drought has impacts on vegetation composition, growth, productivity, structure and functioning of ecosystems, which limits regeneration of vegetation cover.