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The invasive tree, Tamarix sp., was introduced to the United States in the 1800s to stabilize stream banks. The riparian ecosystem adjacent to the middle Rio Grande River in central New Mexico consists of mature cottonwood ( Populus fremontii) gallery forests with a dense Tamarix understory. We hypothesized that Populus would compensate for reduced competition by increasing its water consumption in restored riparian plots following selective Tamarix removal, resulting in similar transpiration ( T) among stands. The northern study site included a Populus stand invaded by Tamarix (INVN) and a restored Populus-only stand (RESN), as did a southern site (INVS and RESS) approximately 80 miles south. At each site, 20 × 20-m plots were established where up to 16 stems were monitored throughout the 2004 growing season using thermal dissipation sapflow sensors. Populus sapflux rates were greater in restored stands, suggesting those trees compensated for understory removal by using more water. Sapflow was scaled to estimate stand-level T based on a quantitative assessment of sapwood basal area ( Asw) by species. Although exotic species represented 85 and 91% of the total stems in the invaded stands, it amounted to only 3% (INVS) and 4% (INVN) of the total Asw, contributing proportionately less to T compared to Populus. Our results indicate that removing Tamarix from the Populus understory in this riparian forest had a minimal impact on stand water balance. Riparian restoration of the type discussed herein should focus primarily on enhancing riparian health rather than generating water. [ABSTRACT FROM AUTHOR]

Abstract: Rates of groundwater recharge are especially unpredictable in semiarid regions, partly because of the role that vegetation plays in soil–plant–water dynamics. Understanding how abiotic and biotic variables affect water movement and associated soil-chloride distribution is essential to estimating groundwater recharge. Converting shrubland to grassland reduces rooting depth and plant cover, at least temporarily. In turn, reduced rooting depth increases leaching of soil chloride from the root zone when evaporative water losses are less in the grassland than in the original shrubland. This study contrasts soil and vegetation effects on soil chloride in semiarid rangelands. We established experimental plots that represent a successional chronosequence. Three native, undisturbed stands of rangeland brush (control) dominated by mature honey mesquite (Prosopis glandulosa) were compared with adjacent land plowed of vegetation at different times (in 1991, 2001, and 2005) and were subsequently allowed to regrow (3 locations×4 plot types). Soil samples were collected at incremental depths up to 4.2m and analyzed for physical properties (bulk density, texture, and others), chloride concentration, and root biomass. Aboveground vegetation surveys were also conducted. We expected shallower rooting depth for at least 5years after conversion of shrubland to grassland and attributed deeper peak soil-chloride concentration to increased deep drainage potentially leading to groundwater recharge. Differences among soil abiotic properties were too minor to change chloride distribution. Rather, differences in chloride distribution were related to changes in vegetation. Shrub cover increased over time after clearing. Grass cover peaked in the 5-year treatment plots and decreased as shrub species regained dominance. Contrary to expectations, root biomass increased for approximately 5years following the clearing of shrubs, but then it decreased with time. Roots were shallowly distributed in earlier successional plots. Vegetation removal greatly reduced root-zone total chloride in 5- and 15-year treatment plots compared with control plots, suggesting chloride had been flushed from the profile following brush removal, after as short a time as 5years. In addition, deepest peak soil-chloride concentration occurred in 5-year plots. We created a stepwise multiple regression model based on related soil and vegetation attributes. According to the model, time since treatment accounted for 24% of the variation in the depth to maximum chloride concentration, and root depth accounted for an additional 20% of the variation. Hydrologic changes following brush removal were evident in our study area within the first 5years, and they are likely to positively influence groundwater recharge. [Copyright &y& Elsevier]

Tamarix chinensis Lour., which is common throughout the southwestern USA, is a phreatophytic riparian tree capable of high water use. We investigated temporal congruence between daily total evapotranspiration (E) estimated from stem sap flux (Js) measurements (Esf) and eddy covariance (Ecv), both seasonally and immediately following rain events, and used measurements of leaf-level gas exchange, stem water content and diurnal changes in leaf water potential to track drivers of transpiration. In one study, conducted near the end of the growing season in a pure T. chinensis stand adjacent to the Rio Grande River in central New Mexico, nighttime Esf as a proportion of daily Esf increased with water availability to a peak of 36.6%. High nighttime Esf was associated with underestimates of nighttime Ecv. A second study, conducted in west Texas, beside the Pecos River, investigated the relationships between nighttime Js and stem tissue rehydration, on the one hand, and nighttime E, on the other hand. Leaf gas exchange measurements and stomatal impressions suggested that nighttime Js was primarily attributed to concurrent transpiration, although there were small overnight changes in stem water content. Both vapor pressure deficit and soil water availability were positively related to nighttime Js, especially following rainfall events. Thus, both studies indicate that T. chinensis can transpire large amounts at night, a fact that must be considered when attempting to quantify E either by eddy covariance or sap flux methods. [ABSTRACT FROM AUTHOR]

We compared the accuracy and precision of three devices for measuring soil water content in both natural and repacked soils and evaluated their temperature sensitivity. Calibrations were developed for a capacitance instrument (ECH2O), a time domain reflectometry cable tester (CT), and a water content reflectometer (WCR) in soils collected from the Wind River and H.J. Andrews Experimental Forests. We compared these calibrations with equations suggested by manufacturers or commonly used in the literature and found the standard equations predicted soil moisture content 0%–11.5% lower (p < 0.0001) than new calibrations. Each new calibration equation adequately predicted soil moisture from the output for each instrument regardless of location or soil type. Prediction intervals varied, with errors of 4.5%, 3.5%, and 7.1% for the ECH2O, CT, and WCR, respectively. Only the ECH2O system was significantly influenced by temperature for the range sampled: as temperature increased by 1 °C, the soil moisture estimate decreased by 0.1%. Overall, the ECH2O performed nearly as well as the CT, and thanks to its lower cost, small differences in performance might be offset by deployment of a greater number of probes in field sampling. Despite its higher cost, the WCR did not perform as well as the other two systems. [ABSTRACT FROM AUTHOR]

To advance current environmental flow standards in Texas, we developed field, laboratory, and analytical methods to model recruitment dynamics of indicator species selected to cover a range of population responses to flow variation. Preliminary investigations were conducted in three central Texas river basins to evaluate the feasibility of these methods for formulating and evaluating the state's environmental flow standards. Age analysis allowed back‐calculation of dates of fish hatching, mussel recruitment, and tree germination for estimation of temporal variation in recruitment. Recruitment data were then analyzed in relation to flow regime components. Statistical models were derived for flow–recruitment relationships of Shoal Chub Macrhybopsis hyostoma, Smallmouth Buffalo Ictiobus bubalus, threeridge mussel Amblema plicata, and boxelder Acer negundo. The Shoal Chub model was used to hindcast recruitment dynamics in the Brazos River, revealing a decline in recruitment after dam construction. The Smallmouth Buffalo model revealed that strong year‐classes were positively associated with springtime pulses of long duration but negatively associated with frequent short‐duration pulses. Results for the threeridge mussel were not as easily interpreted, but for all three river basins generally showed weaker recruitment during periods with extreme low and high flows. The boxelder model revealed positive associations between recruitment and high flow components and was used to forecast the probability of germination under five simulated flow regime scenarios, thereby providing an additional means for evaluating the suitability of environmental flow standards. Assessment of how hydrology influences recruitment provides an evidence‐based method to hindcast responses to past flow regimes and forecast responses to future flow scenarios, thereby providing a basis for evaluating environmental flow standards and water management options. [ABSTRACT FROM AUTHOR]

To optimize irrigation, agronomists need to modulate crop water productivity (CWP) throughout phenology. We compared regulated deficit irrigation (RDI) and sustained deficit irrigation (SDI) in chickpea (Cicer arietinum L. var. Blanoro), expecting RDI during vegetative growth (VG) to enhance CWP, as opposed to flowering (F) and pod-filling (PF) stages. The effects of RDI and SDI on grain yield, plant height, weight, grain caliber, pods and grains per plant, harvest index, and CWP, were tested through a complete randomized block experiment during the years 2020 and 2021, comparing full irrigation (FI, ETc = 100%), SDI (SDI75, ETc = 75% during all stages), and six RDI treatments varying in ETc% across phenology: VG50, VG75, F50, F75, PF50, and PF75. VG75 had higher CWP while minimizing impacts on productivity. During 2020, the plants were taller (0.44 ± 4.4 m), and increased in harvest index (0.47 ± 0.06), and CWP (0.90 ± 0.2 kg m−3) (p < 0.05), while in 2021, plants were heavier (11.4 ± 2.8 g) and increased in caliber (46.1 ± 3.0 grains); grain yield did not differ between the years (p ˃ 0.05), reaching 861.8 (2020) and 944.7 kg ha−1 (2021). Our results highlight the relevance of maintaining 100% ETc during flowering, and the maintenance of RDI at 75% ETc during vegetative growth. [ABSTRACT FROM AUTHOR]

This study updates the multi‐layered Community Land Model (CLM‐ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. Test results indicate that the modified multi‐layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO2, temperature, and wind speed) under the canopy. In the single‐layer models (CLM4.5 and CLM5), excessive day‐to‐night differences in leaf temperature and leaf wetness were originally noted, but CLM‐ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Sub‐canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. More importantly, unlike single layer models, the results that CLM‐ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest. Plain Language Summary: This study is to improve and examine a multi‐layered land‐surface model for a better understanding of the surface process and advanced future climate prediction. This study was made through comparison with a single‐layer model and with site observations about a tropical montane rainforest in Costa Rica. To apply the multi‐layer model at this site, we updated a vertical leaf distribution and turbulence scheme and added the CO2 profile and soil respiration scheme. The study showed the multi‐layer model could more correctly reflect the site uniqueness (e.g., extremely wet) and the complexity by hillslope, compared to the single‐layer model. Key Points: Multi‐layered Community Land Model (CLM‐ml) v0 was updated and compared to observations across a vertical profile in the tropical montane rainforestCLM‐ml reasonably estimates key micrometeorological variablesVertical leaf‐distributions and turbulence play a significant role in land‐atmosphere interactions [ABSTRACT FROM AUTHOR]

This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions. [ABSTRACT FROM AUTHOR]

This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4,000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulation for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micro-meteorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5 but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLM models still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions. [ABSTRACT FROM AUTHOR]

The structural loss rates of standing dead trees (SDTs) affect a variety of processes of interest to ecologists and foresters, yet the decomposition of SDTs has been traditionally characterized by qualitative decay classes, reductions in wood density as decay progresses, and sampling schemes focused on estimating snag longevity. By establishing a methodology to accurately and efficiently quantify SDT structural loss over time, these estimated structural loss rates would improve the performance of a variety of models and potentially provide new insight as to the manner in which SDTs undergo degradation in various conditions. The specific objective of this study were: 1) utilize the TreeVolX algorithm to estimate the volume of 29 SDTs scanned with terrestrial lidar; 2) develop a novel, voxel-based change detection algorithm capable of providing automated structural loss estimates with multitemporal terrestrial lidar observations; and 3) estimate and characterize the structural loss rates of Pinus taeda and Quercus stellata in southeastern Texas. A voxel-based change detection methodology was developed to accurately detect and quantify structural losses and incorporated several methods to mitigate the challenges presented by shifting tree and branch positions as SDT decay progresses. The volume and structural loss of 29 SDTs, composed of Pinus taeda and Quercus stellata , were successfully estimated using multitemporal terrestrial lidar observations over elapsed times ranging from 71 to 753 days. Pine and oak structural loss rates were characterized by estimating the amount of volumetric loss occurring in 20 equal-interval height bins of each SDT. Results showed that large pine snags exhibited more rapid structural loss in comparison to medium-sized oak snags in southeastern Texas. [ABSTRACT FROM AUTHOR]

While it is reasonable to predict that photosynthetic rates are inhibited while leaves are wet, leaf gas exchange measurements during wet conditions are challenging to obtain due to equipment limitations and the complexity of canopy-atmosphere interactions in forested environments. Thus, the objective of this study was to evaluate responses of seven tropical and three semiarid savanna plant species to simulated leaf wetness and test the hypotheses that (i) leaf wetness reduces photosynthetic rates (Anet), (ii) leaf traits explain different responses among species and (iii) leaves from wet environments are better adapted for wet leaf conditions than those from drier environments. The two sites were a tropical rainforest in northern Costa Rica with ~4200 mm annual rainfall and a savanna in central Texas with ~1100 mm. Gas exchange measurements were collected under dry and wet conditions on five sun-exposed leaf replicates from each species. Additional measurements included leaf wetness duration and stomatal density. We found that Anet responses varied greatly among species, but all plants maintained a baseline of activity under wet leaf conditions, suggesting that abaxial leaf Anet was a significant percentage of total leaf Anet for amphistomatous species. Among tropical species, Anet responses immediately after wetting ranged from -31% (Senna alata (L.) Roxb.) to +21% (Zamia skinneri Warsz. Ex. A. Dietr.), while all savanna species declined (up to -48%). After 10 min of drying, most species recovered Anet towards the observed status prior to wetting or surpassed it, with the exception of Quercus stellata Wangenh., a savanna species, which remained 13% below Anet dry. The combination of leaf wetness duration and leaf traits, such as stomatal density, trichomes or wax, most likely influenced Anet responses positively or negatively. There was also overlap between leaf traits and Anet responses of savanna and tropical plants. It is possible that these species converge on a relatively conservative response to wetness, each for divergent purposes (cooling, avoiding stomatal occlusion, or by several unique means of rapid drying). A better understanding of leaf wetness inhibiting photosynthesis is vital for accurate modeling of growth in forested environments; however, species adapted for wet environments may possess compensatory traits that mitigate these effects. [ABSTRACT FROM AUTHOR]

Tree mortality from major disturbances can greatly increase dead wood in forested areas, affecting fire intensity and behavior, wildlife habitat, and carbon dynamics. Accurately quantifying regional standing dead tree (SDT) pools, as conducted by the U.S. Forest Service Forest Inventory and Analysis (FIA) program, remains a prominent challenge. Little empirical work has been done accounting for structural changes in SDT volume across decay classes due to measurement and sampling challenges associated with SDT. Light-detection-and-ranging (LiDAR) represents a remote sensing technology with the potential to improve sampling efficacy and provide volume estimates of SDT via non-destructive sampling. Following this, the goal of this study was to explore the feasibility of empirically quantifying and assessing structural volume in southern pine SDT by decay class using terrestrial LiDAR. To meet this goal, we addressed three objectives, 1) construct empirical volume estimates of SDT by decay class using terrestrial LiDAR and a voxel-based, volume calculation algorithm capable of accounting for occlusion and point cloud quality, 2) develop allometric relationships of aboveground SDT component volumes by decay class and assess error in models and predictions, and 3) quantify proportion-remaining volume of SDT components from terrestrial LiDAR-derived volumes relative to predicted intact tree volumes. This study represents the first to develop empirically-based, terrestrial LiDAR-derived allometric volume relationships and proportion-remaining volume of SDT by decay class. Results indicate that terrestrial LiDAR-derived volumes of SDT produced robust allometric equations by decay class for total above-stump and stem-plus-bark components (adjusted R2 = 0.94–0.98). Allometric relationships for tops-and-branches comprised more variability, likely impacted by scan quality, having adjusted R2 values of ~0.52–0.59. Notably, the inclusion of height in allometric relationships for total above-stump volume precluded the need for decay class as a covariate, accounting for the variability inherent in each decay class. Importantly, this means that total above-stump allometric equations could be effective under different decay class systems or, more broadly, where no decay classes were measured, thus providing broad utility. Empirically-derived proportion-remaining volume of SDT components followed expected decreasing trends by decay class. Interestingly, proportion-remaining volume for tops-and-branches closely matched theoretically-derived values from a previous FIA-related study. Ultimately, terrestrial LiDAR was critical for efficiently measuring volume of southern pine SDT by decay class and for developing SDT-specific allometric relationships of volume and estimates of structural change by decay class. This study showcases the feasibility of LiDAR-derived, SDT-specific tools for improved accounting of SDT resources in FIA and other inventories. • Estimated volume of 49 standing dead trees by decay class via terrestrial LiDAR. • Developed robust standing dead tree-specific volume allometry by decay class. • Height accounted for variability from decay classes for some allometric models. • Calculated empirical values of proportion-remaining volume of standing dead trees. • Lower scan quality impacted variability of tops-and-branches volume and allometry. [ABSTRACT FROM AUTHOR]