Biodiversity Assessment and Conservation of Threatened Plant Species Belonging to the Unique Steppe with Trees in Tunisian Drylands

Biodiversity conservation from heavy grazing impacts, through the creation of national parks, is usually considered to sustain higher ecosystem resilience and to protect the natural plant cover as well as the threatened species. The study was carried out in Bou Hedma national park, a biosphere reserve containing the unique Acacia tortilis (Forssk.) Hayne subsp. raddiana (Savi) Brenan steppe with trees in Tunisia. Several functional traits of seven (7) rare and threatened plant species are used to highlight their adaptive strategies in order to understand the evolution of plant communities and the overall ecosystems functioning inside the park. Such results may provide many environmental benefits and maintain the flora biodiversity under harsh dryland conditions

CMIP5 Model Intercomparison of Freshwater Budget and Circulation in the North Atlantic

ABSTRACT The subpolar North Atlantic is a center of variability of ocean properties, wind stress curl, and air–sea exchanges. Observations and hindcast simulations suggest that from the early 1970s to the mid-1990s the subpolar gyre became fresher while the gyre and meridional circulations intensified. This is opposite to the relationship of freshening causing a weakened circulation, most often reproduced by climate models. The authors hypothesize that both these configurations exist but dominate on different time scales: a fresher subpolar gyre when the circulation is more intense, at interannual frequencies (configuration A), and a saltier subpolar gyre when the circulation is more intense, at longer periods (configuration B). Rather than going into the detail of the mechanisms sustaining each configuration, the authors’ objective is to identify which configuration dominates and to test whether this depends on frequency, in preindustrial control runs of five climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). To this end, the authors have developed a novel intercomparison method that enables analysis of freshwater budget and circulation changes in a physical perspective that overcomes model specificities. Lag correlations and a cross-spectral analysis between freshwater content changes and circulation indices validate the authors’ hypothesis, as configuration A is only visible at interannual frequencies while configuration B is mostly visible at decadal and longer periods, suggesting that the driving role of salinity on the circulation depends on frequency. Overall, this analysis underscores the large differences among state-of-the-art climate models in their representations of the North Atlantic freshwater budget

Spatial patterns and intensity of the surface storm tracks in CMIP5 models

Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 30 (2017): 4965-4981, doi:10.1175/JCLI-D-16-0228.1.To improve the understanding of storm tracks and western boundary current (WBC) interactions, surface storm tracks in 12 CMIP5 models are examined against ERA-Interim. All models capture an equatorward displacement toward the WBCs in the locations of the surface storm tracks’ maxima relative to those at 850 hPa. An estimated storm-track metric is developed to analyze the location of the surface storm track. It shows that the equatorward shift is influenced by both the lower-tropospheric instability and the baroclinicity. Basin-scale spatial correlations between models and ERA-Interim for the storm tracks, near-surface stability, SST gradient, and baroclinicity are calculated to test the ability of the GCMs’ match reanalysis. An intermodel comparison of the spatial correlations suggests that differences (relative to ERA-Interim) in the position of the storm track aloft have the strongest influence on differences in the surface storm-track position. However, in the North Atlantic, biases in the surface storm track north of the Gulf Stream are related to biases in the SST. An analysis of the strength of the storm tracks shows that most models generate a weaker storm track at the surface than 850 hPa, consistent with observations, although some outliers are found. A linear relationship exists among the models between storm-track amplitudes at 500 and 850 hPa, but not between 850 hPa and the surface. In total, the work reveals a dual role in forcing the surface storm track from aloft and from the ocean surface in CMIP5 models, with the atmosphere having the larger relative influence.JFB was partially supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections program (Grant NA15OAR4310094). Y-OK was supported by NSF Division of Atmospheric and Geospace Science Climate and Large-scale Dynamics Program (AGS-1355339), NASA Physical Oceanography Program (NNX13AM59G), and DOE Office of Biological and Environmental Research Regional and Global Climate Modeling Program (DE-SC0014433). RJS was supported by DOE Office of Biological and Environmental Research (DE-SC0006743) and NSF Directorate for Geosciences Division of Ocean Sciences (1419584),2017-10-0

CtsR, the Master Regulator of Stress-Response in Oenococcus oeni, Is a Heat Sensor Interacting With ClpL1

Oenococcus oeni is a lactic acid bacterium responsible for malolactic fermentation of wine. While many stress response mechanisms implemented by O. oeni during wine adaptation have been described, little is known about their regulation. CtsR is the only regulator of stress response genes identified to date in O. oeni. Extensively characterized in Bacillus subtilis, the CtsR repressor is active as a dimer at 37°C and degraded at higher temperatures by a proteolytic mechanism involving two adapter proteins, McsA and McsB, together with the ClpCP complex. The O. oeni genome does not encode orthologs of these adapter proteins and the regulation of CtsR activity remains unknown. In this study, we investigate CtsR function in O. oeni by using antisense RNA silencing in vivo to modulate ctsR gene expression. Inhibition of ctsR gene expression by asRNA leads to a significant loss in cultivability after heat shock (58%) and acid shock (59%) highlighting the key role of CtsR in the O. oeni stress response. Regulation of CtsR activity was studied using a heterologous expression system to demonstrate that O. oeni CtsR controls expression and stress induction of the O. oeni hsp18 gene when produced in a ctsR-deficient B. subtilis strain. Under heat stress conditions, O. oeni CtsR acts as a temperature sensor and is inactivated at growth temperatures above 33°C. Finally, using an E. coli bacterial two-hybrid system, we showed that CtsR and ClpL1 interact, suggesting a key role for ClpL1 in controlling CtsR activity in O. oeni

Impact of Grazing Regimes, Landscape Aspect, and Elevation on Plant Life Form Types in Managed Arid Montane Rangelands

Arid steppes, with scattered vegetation, are commonly qualified as degraded ecosystems. Their natural vegetation cover is affected by both abiotic stresses and human activities and, therefore, suitable managements are needed for their sustainability. This study was carried out in the mountain rangeland chain of Matmata (southern dryland of Tunisia) during the springs of 2 rainy yr, 2019 and 2020. Our aims were to evaluate the impact of three grazing regimes (grazing exclusion [over 42 ys; 1978−2020]; seasonal [protected in spring and summer and grazed in autumn and winter, since the 1960s]; and continuous grazing [control; grazed over time]) on the cover of some plant life forms (Raunkiaer, Noy-Meir, and Grime types), under various conditions (sites, aspects, and elevations). To achieve this goal, the pseudoreplicated-nested design was applied, taking into account the site locations (grazing regimes), aspects (exposure to sunlight), and elevations. The cover of the retained plant life forms was measured using the quadrat point method. The main results showed that plant life forms are strongly affected by the grazing regime since the chamephytes (Ch_R), arido-active (AA_NM), and competitive stress-tolerant species (CS_G) are higher under seasonal grazing than control. All these species are qualified as less resistant to grazing. However, arido-passive (AP_NM), ruderal stress-tolerant (RS_G), and therophytes (Th_R) seem to be more resistant to grazing. Studying the impact of grazing management on the plant life form types provides useful information to find the most adapted species for rangeland sustainability all around the world

A review of the role of the Atlantic meridional overturning circulation in Atlantic multidecadal variability and associated climate impacts

By synthesizing recent studies employing a wide range of approaches (modern observations, paleo reconstructions, and climate model simulations), this paper provides a comprehensive review of the linkage between multidecadal Atlantic Meridional Overturning Circulation (AMOC) variability and Atlantic Multidecadal Variability (AMV) and associated climate impacts. There is strong observational and modeling evidence that multidecadal AMOC variability is a crucial driver of the observed AMV and associated climate impacts and an important source of enhanced decadal predictability and prediction skill. The AMOC‐AMV linkage is consistent with observed key elements of AMV. Furthermore, this synthesis also points to a leading role of the AMOC in a range of AMV‐related climate phenomena having enormous societal and economic implications, for example, Intertropical Convergence Zone shifts; Sahel and Indian monsoons; Atlantic hurricanes; El Niño–Southern Oscillation; Pacific Decadal Variability; North Atlantic Oscillation; climate over Europe, North America, and Asia; Arctic sea ice and surface air temperature; and hemispheric‐scale surface temperature. Paleoclimate evidence indicates that a similar linkage between multidecadal AMOC variability and AMV and many associated climate impacts may also have existed in the preindustrial era, that AMV has enhanced multidecadal power significantly above a red noise background, and that AMV is not primarily driven by external forcing. The role of the AMOC in AMV and associated climate impacts has been underestimated in most state‐of‐the‐art climate models, posing significant challenges but also great opportunities for substantial future improvements in understanding and predicting AMV and associated climate impacts

The Arctic predictability and prediction on seasonal-to-interannual timescales (APPOSITE) data set version 1

This is the final version of the article. Available from the publisher via the DOI in this record. Discussion paper (published on 15 Oct 2015)Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi- 5 model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model 10 intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate vari15 ability on these timescales, such as the El Niño Southern Oscillation.This work was supported by the Natural Environment Research Council (grant NE/I029447/1). Helge Goessling was supported by a fellowship of the German Research Foundation (DFG grant GO 2464/1-1). Data storage and processing capacity was kindly provided by the British Atmospheric Data Centre (BADC). Thanks to Yanjun Jiao (CCCma) for his assistance with the CanCM4 simulations and to Bill Merryfield for his comments on a draft of the pape

Have Aerosols Caused the Observed Atlantic Multidecadal Variability?

Identifying the prime drivers of the twentieth-century multidecadal variability in the Atlantic Ocean is crucial for predicting how the Atlantic will evolve in the coming decades and the resulting broad impacts on weather and precipitation patterns around the globe. Recently, Booth et al. showed that the Hadley Centre Global Environmental Model, version 2, Earth system configuration (HadGEM2-ES) closely reproduces the observed multidecadal variations of area-averaged North Atlantic sea surface temperature in the twentieth century. The multidecadal variations simulated in HadGEM2-ES are primarily driven by aerosol indirect effects that modify net surface shortwave radiation. On the basis of these results, Booth et al. concluded that aerosols are a prime driver of twentieth-century North Atlantic climate variability. However, here it is shown that there are major discrepancies between the HadGEM2-ES simulations and observations in the North Atlantic upper-ocean heat content, in the spatial pattern of multidecadal SST changes within and outside the North Atlantic, and in the subpolar North Atlantic sea surface salinity. These discrepancies may be strongly influenced by, and indeed in large part caused by, aerosol effects. It is also shown that the aerosol effects simulated in HadGEM2-ES cannot account for the observed anticorrelation between detrended multidecadal surface and subsurface temperature variations in the tropical North Atlantic. These discrepancies cast considerable doubt on the claim that aerosol forcing drives the bulk of this multidecadal variability

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1

Abstract. Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño–Southern Oscillation