Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

Summary1. Quantification of stomatal responses to environmental variables, in particular to soil water status, is needed to model carbon and water exchange rates between plants and the atmosphere. 2. Models based on stomatal optimality theory successfully describe leaf gas exchange under different environmental conditions, but the effects of water availability on the key optimization parameter [the marginal water use efficiency (WUE), k = ¶A ⁄ ¶E] has resisted complete theoretical treatment. Building on previous optimal leaf gas exchange models, we developed an analytical equation to estimate k from gas exchange observations along gradients of soil water availability. This expression was then used in a meta-analysis of about 50 species to investigate patterns of variation in k. 3. Assuming that cuticular water losses are negligible k increases under mild water stress but decreases when severe water stress limits photosynthesis. When cuticular conductance is considered, however, k increases monotonically with increasing water stress, in agreement with previous theoretical predictions. Moreover, the shape of these response curves to soil water availability changes with plant functional type and climatic conditions. In general, k is lower in species grown in dry climates, indicating lower marginal WUE. 4. The proposed parameterization provides a framework to assess the responses of leaf gas exchange to changes in water availability. Moreover, the model can be extended to scale leaflevel fluxes to the canopy and ecosystem level.

Summary• Understory plants are subjected to highly intermittent light availability and their leaf gas exchanges are mediated by delayed responses of stomata and leaf biochemistry to light fluctuations. In this article, the patterns in stomatal delays across biomes and plant functional types were studied and their effects on leaf carbon gains and water losses were quantified.• A database of more than 60 published datasets on stomatal responses to light fluctuations was assembled. To interpret these experimental observations, a leaf gas exchange model was developed and coupled to a novel formulation of stomatal movement energetics. The model was used to test whether stomatal delays optimize light capture for photosynthesis, whilst limiting transpiration and carbon costs for stomatal movement.• The data analysis showed that stomatal opening and closing delays occurred over a limited range of values and were strongly correlated. Plant functional type and climate were the most important drivers of stomatal delays, with faster responses in graminoids and species from dry climates.• Although perfectly tracking stomata would maximize photosynthesis and minimize transpiration at the expense of large opening costs, the observed combinations of opening and closure times appeared to be consistent with a nearoptimal balance of carbon gain, water loss and movement costs.

SummarySoil and plant hydraulics constrain ecosystem productivity by setting physical limits to water transport and hence carbon uptake by leaves. While more negative xylem water potentials provide a larger driving force for water transport, they also cause cavitation that limits hydraulic conductivity. An optimum balance between driving force and cavitation occurs at intermediate water potentials, thus defining the maximum transpiration rate the xylem can sustain (denoted as E max ). The presence of this maximum raises the question as to whether plants regulate transpiration through stomata to function near E max .To address this question, we calculated E max across plant functional types and climates using a hydraulic model and a global database of plant hydraulic traits.The predicted E max compared well with measured peak transpiration across plant sizes and growth conditions (R = 0.86, P < 0.001) and was relatively conserved among plant types (for a given plant size), while increasing across climates following the atmospheric evaporative demand. The fact that E max was roughly conserved across plant types and scales with the product of xylem saturated conductivity and water potential at 50% cavitation was used here to explain the safety-efficiency trade-off in plant xylem.Stomatal conductance allows maximum transpiration rates despite partial cavitation in the xylem thereby suggesting coordination between stomatal regulation and xylem hydraulic characteristics.

No abstract

[1] The partitioning of rainfall into evapotranspiration, runoff, and deep infiltration in seasonally dry climates is influenced by strong temporal variability in rainfall and potential evapotranspiration at the intra-annual scale, which cannot be captured by conventional steady state water balance models. Guided by dimensional analysis and using simplified stochastic soil moisture models, we develop analytical expressions describing the annual partitioning of rainfall into evapotranspiration and deep percolation/runoff in seasonally dry, surface water dependent landscapes. We discuss the related changes to Budyko's curve under different seasonality scenarios, showing that an increase in seasonal rainfall and potential evapotranspiration variability as well as dry season length can lead to a decrease in the annual evapotranspiration ratio. In addition, our model shows that although increased soil water storage can compensate for the decrease in evapotranspiration due to climate seasonality, this effect is more marked in drier climates (higher annual dryness index) compared to wetter climates. Finally, the coupling of the soil moisture model to a minimalist plant growth model shows that in seasonally dry climates, a maximum in biomass is to be expected for a wet season of optimal length, for which the limitations imposed by both water availability and growth duration are at a minimum.Citation: Feng, X., G. Vico, and A. Porporato (2012), On the effects of seasonality on soil water balance and plant growth, Water Resour. Res., 48, W05543,

No abstract

No abstract