Accurate estimates of how soil water stress affects plant transpiration are crucial for reliable land surface model (LSM) predictions. Current LSMs generally use a water stress factor, β, dependent on soil moisture content, θ, that ranges linearly between β=1 for unstressed vegetation and β=0 when wilting point is reached. This paper explores the feasibility of replacing the current approach with equations that use soil water potential as their independent variable, or with a set of equations that involve hydraulic and chemical signaling, thereby ensuring feedbacks between the entire soil–root–xylem–leaf system. A comparison with the original linear θ-based water stress parameterization, and with its improved curvi-linear version, was conducted. Assessment of model suitability was focused on their ability to simulate the correct (as derived from experimental data) curve shape of relative transpiration versus fraction of transpirable soil water. We used model sensitivity analyses under progressive soil drying conditions, employing two commonly used approaches to calculate water retention and hydraulic conductivity curves. Furthermore, for each of these hydraulic parameterizations we used two different parameter sets, for 3 soil texture types; a total of 12 soil hydraulic permutations. Results showed that the resulting transpiration reduction functions (TRFs) varied considerably among the models. The fact that soil hydraulic conductivity played a major role in the model that involved hydraulic and chemical signaling led to unrealistic values of β, and hence TRF, for many soil hydraulic parameter sets. However, this model is much better equipped to simulate the behavior of different plant species. Based on these findings, we only recommend implementation of this approach into LSMs if great care with choice of soil hydraulic parameters is taken

Reduced stomatal conductance (g_s) during soil drought in angiosperms may result from effects of leaf turgor on stomata and/or factors that do not directly depend on leaf turgor, including root‐derived abscisic acid (ABA) signals. To quantify the roles of leaf turgor‐mediated and leaf turgor‐independent mechanisms in g_s decline during drought, we measured drought responses of g_s and water relations in three woody species (almond, grapevine and olive) under a range of conditions designed to generate independent variation in leaf and root turgor, including diurnal variation in evaporative demand and changes in plant hydraulic conductance and leaf osmotic pressure. We then applied these data to a process‐based g_s model and used a novel method to partition observed declines in g_s during drought into contributions from each parameter in the model. Soil drought reduced g_s by 63–84% across species, and the model reproduced these changes well (r² = 0.91, P < 0.0001, n = 44) despite having only a single fitted parameter. Our analysis concluded that responses mediated by leaf turgor could explain over 87% of the observed decline in g_s across species, adding to a growing body of evidence that challenges the root ABA‐centric model of stomatal responses to drought.

12 páginas.-- 10 figuras.-- 3 tablas.-- 43 referenciasCharacterization of the spatio-temporal variability of tree water status is a prerequisite to conducting precise irrigation management in fruit tree orchards. This study assessed the suitability of a crop water stress index (CWSI) derived from high-resolution aerial thermal imagery for estimating tree water status variability in super high density (SHD) olive orchards. The experiment was conducted at a commercial SHD olive orchard near Seville (southwestern Spain), with drip irrigated trees under three irrigation treatments (four plots per treatment in a randomized block design): a full irrigation treatment to replace the crop water needs (ETc) and two regulated deficit irrigation treatments to replace ca. 45% of ETc. Meteorological variables, soil moisture content, leaf water potential, stem water potential and leaf gas exchange measurements were performed along the irrigation season. Infrared temperature sensors (IRTs) installed approximately 1 m above the canopies were used to derive the required Non-Water-Stressed Baselines (NWSBs) for CWSI calculation. NWSBs were not common during the growing season, although the seasonal effect could be partly explained with solar angle variations. A thermal camera installed on a mini Remotely Piloted Aircraft System (RPAS) allowed for the recording of high-resolution thermal images on 5 representative dates during the irrigation season. The CWSI values derived from aerial thermal imagery were sensitive to the imposed variations in tree water status within the SHD olive orchard. Among the recorded variables, maximum stomatal conductance showed the tightest correlation with CWSI. We concluded that high-resolution thermal imagery captured from a mini RPAS is a suitable tool for defining tree water status variability within SHD olive orchardsThis work was funded by the Spanish Ministry of Economy and Competitiveness (research project AGL2012-34544, predoctoral contract grant BES-2013-065380) and by the Junta de Andalucía (research project P12-AGR-1227).Peer reviewe

Urban development is causing environmental and social concerns that are compromising human welfare and the sustainability of cities. New urban greening concepts are being developed to mitigate these problems in a sustainable and natural way. Vertical greening systems can be defined as structures that allow vegetation to spread over a building facade or interior wall. These systems are becoming popular though they are still evolving and more knowledge on some of their particular impacts is required. In the last five years, the number of studies published in the scientific literature on this topic, especially involving living walls, has significantly increased. This scientific interest has corresponded with an increased and parallel attention by the general public. This work offers a broad description of the different systems and a comprehensive review of the particular benefits of these green infrastructures. Knowledge gaps and shortcomings have also been identified and discussed.