Adaptive tracking of EEG oscillations.

Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception. However, measuring this activity and its influence requires precise extraction of frequency components. This processing is not straightforward. Particularly, difficulties with extracting oscillations arise due to their time-varying characteristics. Moreover, when phase information is needed, it is of the utmost importance to extract narrow-band signals. This paper presents a novel method using adaptive filters for tracking and extracting these time-varying oscillations. This scheme is designed to maximize the oscillatory behavior at the output of the adaptive filter. It is then capable of tracking an oscillation and describing its temporal evolution even during low amplitude time segments. Moreover, this method can be extended in order to track several oscillations simultaneously and to use multiple signals. These two extensions are particularly relevant in the framework of EEG data processing, where oscillations are active at the same time in different frequency bands and signals are recorded with multiple sensors. The presented tracking scheme is first tested with synthetic signals in order to highlight its capabilities. Then it is applied to data recorded during a visual shape discrimination experiment for assessing its usefulness during EEG processing and in detecting functionally relevant changes. This method is an interesting additional processing step for providing alternative information compared to classical time-frequency analyses and for improving the detection and analysis of cross-frequency couplings.

Evolution of proteins after whole-genome duplication

Evolution of proteins after whole-genome duplicationGene and genome duplication are considered major mechanisms in the creation of newfunctions in genomes, or in the refinement of networks by the division of function amongmore genes. In animals, the best demonstrated whole genome duplication occurred at theorigin of Teleost fishes. This makes fishes an ideal model to study the consequences ofgenome duplication, particularly since we have a good sampling of genome sequences,abundant functional information, and a very well studied outgroup: the tetrapodes (includinghuman). More specifically, I studied the consequences of duplication on proteins usingevolutionary models to infer adaptive events. I analysed the influence of positive selection invertebrate genes, by contrasting singleton genes and duplicated genes. The conclusion of theanalyses was threefold: (i) positive selection affects diverse phylogenetic branches anddiverse gene categories during vertebrate evolution; (ii) it concerns only a small proportion ofsites (1%-5%); and (iii) whole genome duplication had no detectable impact on theprevalence of this positive selection.I also studied evolution at the amino acid level with different methods to detect functionalshifts (covarion process and constant-but-different process). As in my previous research, Ifound similar numbers of functional shifts between duplicates and between orthologs.The accepted framework for studies of molecular evolution is that orthologs share the samefunction, whereas the function of paralogs diverges. This framework gives a special place togene duplication in evolution, as the main mechanism for generating novelty. With myprevious results showing that duplication and speciation are not so different, we investigatedthe literature to question the evidence for similar or divergent evolution of gene function afterduplication relative to speciation genes. This led us to propose a more rigorous design offuture studies of gene duplication.Finally, based on my automated protocol, we built a database of positive selection invertebrates' genes, Selectome. This database is freely available on the web and will helpfuture evolutionary as well as biochemical studies.

Life-history evolution and the polyphenic regulation of somatic maintenance and survival.

Here we discuss life-history evolution from the perspective of adaptive phenotypic plasticity, with a focus on polyphenisms for somatic maintenance and survival. Polyphenisms are adaptive discrete alternative phenotypes that develop in response to changes in the environment. We suggest that dauer larval diapause and its associated adult phenotypes in the nematode (Caenorhabditis elegans), reproductive dormancy in the fruit fly (Drosophila melanogaster) and other insects, and the worker castes of the honey bee (Apis mellifera) are examples of what may be viewed as the polyphenic regulation of somatic maintenance and survival. In these and other cases, the same genotype can--depending upon its environment--express either of two alternative sets of life-history phenotypes that differ markedly with respect to somatic maintenance, survival ability, and thus life span. This plastic modulation of somatic maintenance and survival has traditionally been underappreciated by researchers working on aging and life history. We review the current evidence for such adaptive life-history switches and their molecular regulation and suggest that they are caused by temporally and/or spatially varying, stressful environments that impose diversifying selection, thereby favoring the evolution of plasticity of somatic maintenance and survival under strong regulatory control. By considering somatic maintenance and survivorship from the perspective of adaptive life-history switches, we may gain novel insights into the mechanisms and evolution of aging.

Origins, evolution, and phenotypic impact of new genes.

Ever since the pre-molecular era, the birth of new genes with novel functions has been considered to be a major contributor to adaptive evolutionary innovation. Here, I review the origin and evolution of new genes and their functions in eukaryotes, an area of research that has made rapid progress in the past decade thanks to the genomics revolution. Indeed, recent work has provided initial whole-genome views of the different types of new genes for a large number of different organisms. The array of mechanisms underlying the origin of new genes is compelling, extending way beyond the traditionally well-studied source of gene duplication. Thus, it was shown that novel genes also regularly arose from messenger RNAs of ancestral genes, protein-coding genes metamorphosed into new RNA genes, genomic parasites were co-opted as new genes, and that both protein and RNA genes were composed from scratch (i.e., from previously nonfunctional sequences). These mechanisms then also contributed to the formation of numerous novel chimeric gene structures. Detailed functional investigations uncovered different evolutionary pathways that led to the emergence of novel functions from these newly minted sequences and, with respect to animals, attributed a potentially important role to one specific tissue--the testis--in the process of gene birth. Remarkably, these studies also demonstrated that novel genes of the various types significantly impacted the evolution of cellular, physiological, morphological, behavioral, and reproductive phenotypic traits. Consequently, it is now firmly established that new genes have indeed been major contributors to the origin of adaptive evolutionary novelties.

The adaptive function of melanin-based coloration in the tawny owl (Strix aluco) ; the proximate role of the melanocortin system

Colour polymorphism is common in wild population. One of the main questioning of evolutionary biologists is to understand how different colour variants could have evolved and be maintained in fluctuating environments, a selective process that forces individuals to constantly adapt their strategies in order to survive. This issue is particularly true for traits that are genetically inherited. Natural selection erodes genotypes with lowest fitness (less adapted), reducing in turn global genetic variation within population. In this context, the study of the evolution and maintenance of melanin- based coloration is relevant since inter-individual variation in the deposition of these pigments is common in animal and plant kingdoms and is under strong genetic control. In this thesis, I focus on the specific case of the tawny owl (Strix aluco), a species displaying continuous variation in reddish pheomelanin-based coloration. Interestingly, empirical studies highlighted covariations between melanin-based coloration and important behavioural, physiological and life history traits. Recently, a genetic model pointed out the melanocortin system and their pleiotropic effects as a potential regulator of these covariations. Accordingly, this PhD thesis further investigates colour-specific behavioural, physiological, or life history strategies, while examining the proximate mechanisms underlying these reaction norms. We found that differently coloured tawny owls differently resolve fundamental trade-off between offspring number and quality (Chapter 1), light melanic individuals producing many low- quality offspring and dark, melanic ones producing few high-quality offspring. These reproductive strategies are likely to induce alternative physiological constraints. Indeed, we demonstrated that light melanic individuals produced higher levels of reactive oxygen species (ROS, Chapter 2), but also expressed higher levels of antioxidant (GSH, Chapters 2 & 3). Interestingly, we showed that light melanic breeding females could modulate their POMC prohormone levels according to the environmental conditions, while dark reddish ones produced constant levels of this prohormone {Chapter 4). Finally, we highlighted colour-specific patterns of prohormone convertase 1 (PCI) gene expression (Chapter 5), an enzyme responsible for POMC prohormone processing to ACTH and a- MSH, for instance. Altogether, these results provide strong evidence of colour-specific strategies, light and melanic tawny owls better coping with stressful and relaxed environments, respectively. Variation in melanin-based coloration is likely to be maintained by the heterogeneity of our study area and strong environmental stochasticity within and between years, these process favouring differently coloured tawny owls at different periods of time. From a proximate point of view, this PhD thesis supports the hypothesis that covariations between phenotypic traits and melanin-based coloration stems from the melanocortin system, especially the fundamental role of POMC gene expression and its processing to melanocortin peptides. - Le polymorphisme de couleur est une variation phénotypique très fréquente dans la nature. En biologie évolutive, une des problématiques clés est donc de comprendre comment différent morphes de couleur peuvent être apparus et maintenus au cours du temps dans des environnements aussi variables que les nôtres, surtout que ces fluctuations forcent ces morphes à s'adapter constamment pour assurer leur survie. Cette thématique est particulièrement réelle lorsque les variations phénotypiques sont héréditaires et donc sous forte influence génétique. La sélection naturelle a en effet le pouvoir d'éroder rapidement la variation génétique en éliminant les génotypes mal adaptés. Dans ce sens, l'étude de l'évolution, et de la maintenance de la coloration mélanique est donc tout à fait pertinente car la variation de coloration entre individus est très répandue à travers les règnes animal et végétal et sous forte influence génétique. Dans cette thèse, je me suis concentré sur le cas spécifique de la chouette hulotte (Strix aluco), une espèce présentant une variation continue dans la déposition de pigments pheomélaniques roux. De précédentes études ont déjà montré que cette variation de coloration était associée avec des variations de traits comportementaux, physiologiques ou d'histoire de vie. Récemment, une étude a souligné l'importance du système des mélanocortines et de leurs effets pléiotropes dans la régulation de ces covariations. En conséquence, cette thèse de doctoral a pour but d'étudier un peu plus les stratégies comportementales, physiologiques ou d'histoire de vie spécifiques à chaque morphe de couleur, tout en examinant un peu plus les mécanismes proximaux potentiellement à la base de ces normes de réactions. Nous constatons tout d'abord que les morphes de couleurs étaient associés à différentes stratégies dans la résolution de compromis telle que la production de beaucoup de jeunes ou des jeunes de qualité (Chapitre 1). Les morphes gris (dit peu mélaniques) ont tendance à produire beaucoup de jeunes mains de moindre qualité, alors que les morphes roux (dit fortement mélaniques) produisent moins de jeunes mais de meilleure qualité. Ces stratégies sont susceptibles alors d'induire certaines contraintes physiologiques. Par exemple, nous montrons que les morphes gris produisent plus de dérivés réactifs de l'oxygène (ROS, Chapitre 2), mais aussi plus d'antioxydants (GSH, Chapitres 2 & 3). Nous montrons ensuite que les femelles grises ont une plus grande capacité à moduler leur niveau de POMC prohormone dans le sang en fonction des conditions environnementales, alors que les femelles rousses gardent un niveau constant (Chapitre 4). Finalement, nous démontrons que les patterns d'expression du gène codant pour la prohormone convertase 1 varient chez des jeunes issus de parents gris ou roux (Chapitre 5). Ceci est particulièrement intéressant car cette enzyme permet de scinder la POMC prohormone en plusieurs peptides importants tels que l'ACTH ou l'a-MSH. En conclusion, ces résultats démontrent qu'il y a bel et bien des stratégies évolutives différentes entre les morphes de couleurs, les chouettes hulottes grises et rousses étant respectivement plus adaptés à des environnements stressants ou favorables. L'hétérogénéité de notre zone d'étude et la stochasticité environnementale qui caractérise ses habitats pourraient donc agir comme une source de sélection temporelle, laquelle favoriserait les différents morphes de couleurs à diverses périodes. D'un point de vue plus proximale maintenant, cette thèse de doctorat soutient l'hypothèse que les covariations observées entre la coloration mélanique et des traits phénotypiques importants sont modulées par les effets pléiotropes du système des mélanocortines, et met en avant le rôle prépondérant que pourrait jouer l'expression du gène POMC et sa post traduction en mélanocortines.

Insights from insects about adaptive social information use.

Copying others can greatly improve individual fitness and is fundamental for the organisation of societies. Yet in some situations it is better to ignore social information and either explore the world individually or use personal information obtained through prior experience. Insects provide excellent models to study the strategic use of social information, but insights from recent research have rarely been viewed in the light of social learning strategies. Here we discuss how insects tailor their reliance on social information to those circumstances for which it is most beneficial, and suggest that insects and vertebrates use similar information-use strategies. We highlight future research avenues, including the use of molecular tools to study the genetic and genomic basis of social information use.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

MHC Class II Transactivator Is an In Vivo Regulator of Osteoclast Differentiation and Bone Homeostasis Co-opted From Adaptive Immunity.

The molecular networks controlling bone homeostasis are not fully understood. The common evolution of bone and adaptive immunity encourages the investigation of shared regulatory circuits. MHC Class II Transactivator (CIITA) is a master transcriptional co-activator believed to be exclusively dedicated for antigen presentation. CIITA is expressed in osteoclast precursors, and its expression is accentuated in osteoporotic mice. We thus asked whether CIITA plays a role in bone biology. To this aim, we fully characterized the bone phenotype of two mouse models of CIITA overexpression, respectively systemic and restricted to the monocyte-osteoclast lineage. Both CIITA-overexpressing mouse models revealed severe spontaneous osteoporosis, as assessed by micro-computed tomography and histomorphometry, associated with increased osteoclast numbers and enhanced in vivo bone resorption, whereas osteoblast numbers and in vivo bone-forming activity were unaffected. To understand the underlying cellular and molecular bases, we investigated ex vivo the differentiation of mutant bone marrow monocytes into osteoclasts and immune effectors, as well as osteoclastogenic signaling pathways. CIITA-overexpressing monocytes differentiated normally into effector macrophages or dendritic cells but showed enhanced osteoclastogenesis, whereas CIITA ablation suppressed osteoclast differentiation. Increased c-fms and receptor activator of NF-κB (RANK) signaling underlay enhanced osteoclast differentiation from CIITA-overexpressing precursors. Moreover, by extending selected phenotypic and cellular analyses to additional genetic mouse models, namely MHC Class II deficient mice and a transgenic mouse line lacking a specific CIITA promoter and re-expressing CIITA in the thymus, we excluded MHC Class II expression and T cells from contributing to the observed skeletal phenotype. Altogether, our study provides compelling genetic evidence that CIITA, the molecular switch of antigen presentation, plays a novel, unexpected function in skeletal homeostasis, independent of MHC Class II expression and T cells, by exerting a selective and intrinsic control of osteoclast differentiation and bone resorption in vivo. © 2014 American Society for Bone and Mineral Research.

Evidence for adaptive radiation from a phylogenetic study of plant defenses.

One signature of adaptive radiation is a high level of trait change early during the diversification process and a plateau toward the end of the radiation. Although the study of the tempo of evolution has historically been the domain of paleontologists, recently developed phylogenetic tools allow for the rigorous examination of trait evolution in a tremendous diversity of organisms. Enemy-driven adaptive radiation was a key prediction of Ehrlich and Raven's coevolutionary hypothesis [Ehrlich PR, Raven PH (1964) Evolution 18:586-608], yet has remained largely untested. Here we examine patterns of trait evolution in 51 North American milkweed species (Asclepias), using maximum likelihood methods. We study 7 traits of the milkweeds, ranging from seed size and foliar physiological traits to defense traits (cardenolides, latex, and trichomes) previously shown to impact herbivores, including the monarch butterfly. We compare the fit of simple random-walk models of trait evolution to models that incorporate stabilizing selection (Ornstein-Ulenbeck process), as well as time-varying rates of trait evolution. Early bursts of trait evolution were implicated for 2 traits, while stabilizing selection was implicated for several others. We further modeled the relationship between trait change and species diversification while allowing rates of trait evolution to vary during the radiation. Species-rich lineages underwent a proportionately greater decline in latex and cardenolides relative to species-poor lineages, and the rate of trait change was most rapid early in the radiation. An interpretation of this result is that reduced investment in defensive traits accelerated diversification, and disproportionately so, early in the adaptive radiation of milkweeds.

C4 Photosynthesis evolved in grasses via parallel adaptive genetic changes.

Phenotypic convergence is a widespread and well-recognized evolutionary phenomenon. However, the responsible molecular mechanisms remain often unknown mainly because the genes involved are not identified. A well-known example of physiological convergence is the C4 photosynthetic pathway, which evolved independently more than 45 times [1]. Here, we address the question of the molecular bases of the C4 convergent phenotypes in grasses (Poaceae) by reconstructing the evolutionary history of genes encoding a C4 key enzyme, the phosphoenolpyruvate carboxylase (PEPC). PEPC genes belong to a multigene family encoding distinct isoforms of which only one is involved in C4 photosynthesis [2]. By using phylogenetic analyses, we showed that grass C4 PEPCs appeared at least eight times independently from the same non-C4 PEPC. Twenty-one amino acids evolved under positive selection and converged to similar or identical amino acids in most of the grass C4 PEPC lineages. This is the first record of such a high level of molecular convergent evolution, illustrating the repeatability of evolution. These amino acids were responsible for a strong phylogenetic bias grouping all C4 PEPCs together. The C4-specific amino acids detected must be essential for C4 PEPC enzymatic characteristics, and their identification opens new avenues for the engineering of the C4 pathway in crops.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Minimization of biosynthetic costs in adaptive gene expression responses of yeast to environmental changes

Yeast successfully adapts to an environmental stress by altering physiology and fine-tuning metabolism. This fine-tuning is achieved through regulation of both gene expression and protein activity, and it is shaped by various physiological requirements. Such requirements impose a sustained evolutionary pressure that ultimately selects a specific gene expression profile, generating a suitable adaptive response to each environmental change. Although some of the requirements are stress specific, it is likely that others are common to various situations. We hypothesize that an evolutionary pressure for minimizing biosynthetic costs might have left signatures in the physicochemical properties of proteins whose gene expression is fine-tuned during adaptive responses. To test this hypothesis we analyze existing yeast transcriptomic data for such responses and investigate how several properties of proteins correlate to changes in gene expression. Our results reveal signatures that are consistent with a selective pressure for economy in protein synthesis during adaptive response of yeast to various types of stress. These signatures differentiate two groups of adaptive responses with respect to how cells manage expenditure in protein biosynthesis. In one group, significant trends towards downregulation of large proteins and upregulation of small ones are observed. In the other group we find no such trends. These results are consistent with resource limitation being important in the evolution of the first group of stress responses.

Idiosyncratic evolution of maternal effects in response to juvenile malnutrition in Drosophila.

Maternal effects often affect fitness traits, but there is little experimental evidence pertaining to their contribution to response to selection imposed by novel environments. We studied the evolution of maternal effects in Drosophila populations selected for tolerance to chronic larval malnutrition. To this end, we performed pairwise reciprocal F1 crosses between six selected (malnutrition tolerant) populations and six unselected control populations and assessed the effect of cross direction on larval growth and developmental rate, adult weight and egg-to-adult viability expressed under the malnutrition regime. Each pair of reciprocal crosses revealed large maternal effects (possibly including cytoplasmic genetic effects) on at least one trait, but the magnitude, sign and which traits were affected varied among populations. Thus, maternal effects contributed significantly to the response to selection imposed by the malnutrition regime, but these changes were idiosyncratic, suggesting a rugged adaptive landscape. Furthermore, although the selected populations evolved both faster growth and higher viability, the maternal effects on growth rate and viability were negatively correlated across populations. Thus, genes mediating maternal effects can evolve to partially counteract the response to selection mediated by the effects of alleles on their own carriers' phenotype, and maternal effects may contribute to evolutionary trade-offs between components of offspring fitness.

A macro-ecological perspective on crassulacean acid metabolism (CAM) photosynthesis evolution in Afro-Madagascan drylands: Eulophiinae orchids as a case study.

Crassulacean acid metabolism (CAM) photosynthesis is an adaptation to water and atmospheric CO2 deficits that has been linked to diversification in dry-adapted plants. We investigated whether CAM evolution can be associated with the availability of new or alternative niches, using Eulophiinae orchids as a case study. Carbon isotope ratios, geographical and climate data, fossil records and DNA sequences were used to: assess the prevalence of CAM in Eulophiinae orchids; characterize the ecological niche of extant taxa; infer divergence times; and estimate whether CAM is associated with niche shifts. CAM evolved in four terrestrial lineages during the late Miocene/Pliocene, which have uneven diversification patterns. These lineages originated in humid habitats and colonized dry/seasonally dry environments in Africa and Madagascar. Additional key features (variegation, heterophylly) evolved in the most species-rich CAM lineages. Dry habitats were also colonized by a lineage that includes putative mycoheterotrophic taxa. These findings indicate that the switch to CAM is associated with environmental change. With its suite of adaptive traits, this group of orchids represents a unique opportunity to study the adaptations to dry environments, especially in the face of projected global aridification.