In order to compare between experiments, central and public data storage is fundamental. The use of standardized metadata combined with open controlled vocabularies or ontologies is crucial to being able to interoperate between different data types. The “findable, accessible, interoperable, reusable” data principles are aimed at improving the data ecosystem to allow researchers to better locate and integrate data. In the phytobiome sphere, the National Microbiome Data Collaborative is a new initiative to make microbiome data FAIR and aims to use standards such as the Environment Ontology to describe environmental characteristics of samples and the microbial ecosystems embedded within them. One of those limitations surrounding reference databases is the paucity of experimentally validated data that links microbial and plant metabolism, protein function, and DNA sequence. As an example, whereas microbial genes are assigned putative functions based on sequence homology, their actual activity may deviate from these annotations leading, to incorrect interpretations and predictions of ecosystem function . Furthermore, standardized analysis is critical and can be achieved by using centrally updated, state-of-the-art software tools. KBase, the U.S. Department of Energy Systems Biology Knowledge base, has offered a public data storage and analysis dashboard that allows the generation of so-called narratives in which a dataset undergoes a string of analyses . In addition,vertical farming tower for sale large-scale field datasets are increasingly taking advantage of supercomputer resources and ML algorithms that are required to filter noise and generate sensible interpretations from billions of data points.The development of the above mentioned technologies and experimental platforms will improve our understanding of the plant–microbe–atmosphere–soil ecosystem at high spatial and temporal resolution. The combination and integrated use of the discussed tools will further provide opportunities for novel approaches to plant root microbiome research.
An example of an integrated approach is the combination of UAVs equipped with advanced imaging capabilities to study QTL or GWAS populations growing in the field. This would streamline and scale current experimental procedures, so that new genetic markers for various above- and below ground phenotypic characteristics could be identified. These, in turn, could be correlated to microbiome community profiles in roots and leaves. Another example is the combined usage of SynComs and single plants in EcoFabs for advanced root and microbe imaging resolved over space and time complemented with metabolite analysis,enabling systematic examination of the role of specific microbes and metabolites in modifying root architecture. This approach can help identify novel, specific microbial products that can be used to influence important plant traits known to affect field performance . Microbial model systems can then be engineered to produce promising compounds for tests on plants in soil. Finally, we foresee EcoPODs and EcoTrons being used for time-series experiments that span several weeks and months, possibly years, in which high-throughput omics together with continuous environmental sensor measurements can provide in depth yet broad-scale datasets that can be used for training artificial intelligence algorithms related to biogeochemical cycling in relationship to climate. Due to the many direct and indirect ties between local plant– microbe–soil–ecosystem well-being and systems-wide ecological health, technological improvements in phytobiome research are directly translatable to improvements in climate change research. The above mentioned advances in instrumentation and methodology push precision agriculture and precision phytobiome research forward and allow for improved and more sustainable crop productivity under rapidly changing and increasingly extreme climatic conditions. These advances will have impacts in food and energy security and bio-safety as well as environmental conservation and bio-remediation.Seasonally dry tropical forests are dominated by deciduous species coexisting with a small number of evergreen species . Trees withstand the dry season through two mechanisms of drought resistance: desiccation delay and desiccation tolerance .
Two important traits related to desiccation delay are leaf shedding which reduces water loss, and depth of rooting , which determines the sources of water and nutrients used by vegetation . Although previous reports suggested that evergreen species access relatively deeper water sources than deciduous species ,more recent reports suggest that access to water is more related to tree size than phenology . However, there is relatively little information regarding differences among deciduous species having different timing or leaf shedding behavior, even though it is well known that leaf senescence behavior varies greatly among tropical dry forest tree species. Flushing and leaf abscission result from complex interactions between plants and their environment; in many species, the main abiotic factors driving these processes are solar radiation, air relative humidity, vapor pressure deficit, precipitation and soil water content . Four main categories of leaf shedding phenology have been proposed by Williams et al. : evergreen species, which retain a full canopy throughout the year; partially deciduous species, which lose up to 50 % of their canopy during the dry season; semi-deciduous species, which lose more than 50 % of their canopy during the dry season; and deciduous species, in which all leaves are lost during the dry season as they remain leafless for at least 1 month. Most tropical dry forest species are thought to deploy the majority of their root systems relatively deep in the soil profile where moisture tends to be greater and of longer duration . However, in northern Yucatan the hard upper limestone layer, beginning immediately below the shallow soil, impedes root growth, limiting downward growth to crevices and rhizoliths, and the occasional cavities filled with soil material . Rock crevices allow roots to grow far deeper than they would in unfractured bedrock . Thus, in the seasonally dry tropical forests of northern Yucatan, the ability of tree species to grow deep roots and access additional sources of water beyond topsoil could be a crucial characteristic related to variation in phenology and the relative abundance of contrasting tree species. Sources of water used by trees can often be identified by comparing the isotopic composition of water from stems with potential water sources, because there is usually no isotopic fractionation of either hydrogen or oxygen isotopes during water uptake . When trees take water from more than one source, the proportion of water absorbed from each source can be calculated using isotope mixing models .
Such models were developed to cope with multiple sources and allow the input of ancillary data that are known about the system to constrain model outputs, thereby providing results that are restricted to real possibilities. Sources of water used by native trees in northern Yucatan have been studied using these approaches, and large variation in the depth of water uptake among deciduous and evergreen species has been observed . Furthermore,hydroponic vertical farm using these same isotopic approaches along a forest age chronosequence in northeastern Yucatan, evergreen trees were found to access deeper water sources than deciduous species in early succession . Thus, integrating rooting depth as a component of tropical dry forest tree strategies appears especially promising in complex karstic Yucatecan soils. Water-use efficiency , the ratio of carbon gained in photosynthesis relative to water loss during transpiration , is another key factor when considering the costs and benefits of a deep rooting system. Leaf carbon isotopic composition can be used to assess WUE in certain circumstances, and is often positively related to WUE because a high photosynthetic rate per unit stomatal conductance is usually associated with relatively low internal CO2 concentration and reduces discrimination against 13CO2 by rubisco . Although d13C has been used alone to infer WUE, its combination with analysis of isotopic composition leaf organic oxygen improves interpretation of leaf d13C values by allowing analysis of whether variation in d13C is due to changes on the photosynthetic activity or stomatal activity . When humidity increases, the isotopic enrichment of leaf water decreases, causing a reduction in d18O . Theory and empirical data also demonstrate that d18O correlated negatively with stomatal conductance . In shallow soils of northern Yucatan, Querejeta et al. showed that individuals of the same tree species differing in age had different WUE, with younger trees having greater WUE than older ones, indicating that these techniques hold promise for integrating potential differences in water sources with leaf physiological activity. This study focuses on phenological variation between two dominant tropical dry forest species in relation to the depth of water uptake. We hypothesize that the late deciduous habit in P. piscipula and the early deciduous habit in G. floribundum may be determined by their ability to take water from different sources. P. piscipula may have access to deeper sources than G. floribundum. However, due to the restrictions for root growth imposed by the hard bedrock, both species will likely extract most of their water from shallow sources. We also hypothesize that differential use of water sources is linked to key ecophysiological measures of plant performance, including the timing of leaf fall, leaf size, leaf water potential and the balance of carbon gain and water loss as interpreted by leaf stable isotopic composition.Topsoil, calcium carbonate rock layers, soil pockets and plant tissue samples were collected in three sampling campaigns: October 2007 , January 2008 and May 2008 . Topsoil, bedrock and soil pocket samples were obtained from recently exposed walls. Sampling of the lower portion of the walls was restricted by the rock materials produced during blasting events, moreover, roots were not often observed growing in this layer; thus, soil pockets and rock samples were taken only from 0 to 5 m depth.
Because topsoil was removed before rock blasting, soil samples were taken from areas up to 40 m away from the wall being sampled. In addition, gravimetric water content was evaluated by taking 20 samples from topsoil and each rock layer, and a variable number of samples from soil pockets depending on presence of these features in the wall being sampled and drying at 105 C. The eight water sources considered go down from the upper soil layer down to the ground water . Non-transpiring woody shoots were collected from five individuals of each species from vegetation within the quarry. Four stem samples of 5–10 mm width and 50–80 mm long were obtained from each tree. The same trees were sampled at each sampling campaign. No leaves or green tissue were included in the sample to avoid contamination of xylem water by isotopically enriched water that had undergone evaporation from the plant . Samples were preserved in hermetic capped vials wrapped with parafilm and stored in the freezer until processed. Groundwater samples were taken from an open well 2 km from the quarry. Water was extracted from topsoil, soil from pockets, rock and plant stem samples using a cryogenic vacuum distillation line for at least 60 min for stems and 40 min for soil and rocks . Water content of soil, bedrock and tree stems was calculated from sub-samples taken right before the water extraction and oven dried for 24 h at 80 C and 105 C . Stable isotopic composition of oxygen and hydrogen analyses were conducted at the Centre for Stable Isotope Bio-geochemistry at the University of California, Berkeley using a chromiumreactor interfaced with a continuous flow isotope ratio mass spectrometer . d18O and d2 H values were reported in delta notation relative to the Vienna Standard Mean Ocean Water . Values of substrate and stem water d18O and d2 H were plotted in a bi-variate relationship with the Meteoric Water Line determined for this region by Socki et al. , to evaluate the role of water sources across seasons. The contribution to tree water uptake from the different sources during the three sampling campaigns was calculated using Iso-Source software . This software calculates ranges of source-proportional contributions to a mixture based on the isotopic signatures of the mixture and each of the sources. Both d18O and d2 H data were used for model calculations. The data set for modeling was grouped as follows: Laja 0–200 cm was disregarded because is not a significant source of water at any time , February data were not analyzed to avoid misinterpretations due to unsampled water sources , ground water was taken out of the analyses because root systems of P. piscipula and G. floribundum were not observed growing beyond 5-m depths and, bedrock from 200–400 cm was grouped as a single source because their isotopic values were very similar. Because sampled trees were growing \1 km from where rock samples were taken, we assumed that the isotopic compositions of rock were similar in both places.