27 research outputs found
On The Vulnerability of Water Limited Ecosystems to Climate Change
No full textSociety is facing growing environmental problems that require new research efforts to understand the way ecosystems operate and survive, and their mutual relationships with the hydrologic cycle. In this respect, ecohydrology suggests a renewed interdisciplinary approach that aims to provide a better comprehension of the effects of climatic changes on terrestrial ecosystems. With this aim, a coupled hydrological/ecological model is adopted to describe simultaneously vegetation pattern evolution and hydrological water budget at the basin scale using as test site the Upper Rio Salado basin (Sevilleta, NM, USA). The hydrological analyses have been carried out using a recently formulated framework for the water balance at the daily level linked with a spatial model for the description of the spatial organization of vegetation. This enables quantitatively assessing the effects on soil water availability on future climatic scenarios. Results highlighted that the relationship between climatic forcing (water availability) and vegetation patterns is strongly non-linear. This implies, under some specific conditions which depend on the ecosystem characteristics,
small changes in climatic conditions may produce significant transformation of the vegetation patterns
Vegetation structure characteristics and relationships of Kalahari woodlands and savannas
No full textThe Kalahari Transect is one of several International Geosphere–Biosphere Programme (IGBP) transects designed to address global change questions at the regional scale, in particular by exploiting natural parameter gradients (Koch et al., 1995). In March 2000, we collected near-synoptic vegetation structural data at five sites spanning the Kalahari's large precipitation gradient (about 300–1000 mm yr?1) from southern Botswana (?24°S) to Zambia (?15°S). All sites were within the expansive Kalahari sandsheet. Common parameters, including plant area index (PAI), leaf area index (LAI) and canopy cover (CC), were measured or derived using several indirect instruments and at multiple spatial scales. Results show that CC and PAI increase with increasing mean annual precipitation. Canopy clumping, defined by the deviation of the gap size distribution from that of randomly distributed foliage, was fairly constant along the gradient. We provide empirical relationships relating these parameters to each other and to precipitation. These results, combined with those in companion Kalahari Transect studies, provide a unique and coherent test bed for ecological modeling. The data may be used to parameterize process models, as well as test internally predicted parameters and their variability in response to well-characterized climatological differences.<br/
On the importance of accurate depiction of infiltration processes on modelled soil moisture and vegetation water stress
No full textThe description of soil moisture dynamics is a challenging problem for the hydrological community, as it is governed by complex interactions between climate, soil and vegetation. Recent research has achieved significant advances in the description of temporal dynamics of soil water balance through the use of a stochastic differential equation proposed by Laio et al. (2001). The assumptions of the Laio et al. model simplify the mathematical form of the soil water loss functions and the infiltration process. In particular, runoff occurs only for saturation excess, the probability distribution function (PDF) of which is well-represented by a simple expression, but the model does not consider the limited infiltration capacity of soil. In the present work, we extend the soil moisture model to include limitations on soil infiltration capacity with the aim of understanding the impact of varying infiltration processes on the soil water balance and vegetation stress. A comparison between the two models (the original version and the modified one) is carried out via numerical simulations. The limited infiltration capacity influences the soil moisture PDF by reducing its mean and variance. Major changes in the PDFs are found for climates characterized by storms of short duration and high rainfall intensity, as well as in humid climates and in cases where soils have moderate permeability (e.g. loam and clay soils). In the case of limited infiltration capacity, modifications to the dynamics of soil moisture generally lead to higher amounts of vegetation water stress. An investigation of the role of soil texture on vegetation water stress demonstrates that loam soil provides the most favorable condition for plant-growth under arid and semi-arid conditions, while vegetation may benefit from the presence of more permeable soils (e.g. loamy sand) in humid climates
Dynamic Response of Grass Cover to Rainfall Variability: Implications the Function and Persistence of Savanna Ecosystems
No full textSavanna grass cover is dynamic and its annual extent resonates with wet season rainfall, as shown by satellite observations of normalized difference vegetation index (NDVI) time series for the Kalahari Transect (KT) in southern Africa. We explore the hydrological significance of the dynamic grass cover by applying a soil moisture model to the water-limited portion of the KT, which spans a north-south gradient in mean wet season rainfall, r̄, from approximately 700 to 300 mm. Satellite-derived tree fractional cover, xt, is shown to be highly correlated with ground meteorological measurements of r̄ (R2 = 0.94) in this region. By implementing a simple expression for grass growth and decay in the model that factored in only xt and near-surface soil moisture, we were able to effectively reproduce the satellite-derived fractional grass cover, xg, along the transect over a 16-year period (1983-1998). We compared the results from dynamic grass model with those yielded by a static grass cover model in which xg was set to its 16-year average for each simulation. The dynamic quality of the grass was found to be important for reducing tree stress during dry years and for reducing the amount of water that is lost from the overall root zone during the wet years, relative to the static grass case. We find that the dynamic grass cover acts as a buffer against variability in wet season precipitation, and in doing so helps to maximize ecosystem water use. The model results indicate that mixed tree/grass savanna ecosystems are ideally suited to reach a dynamic equilibrium with respect to the use of a fluctuating limiting resource (water) by having functional components that respond to variability in rainfall over long timescales (trees) and short timescales (grasses)
An Evaluation and Redesign of Philip Johnson¿s Tent of Tomorrow Through the Theory of Preservation Potential
No full textAt the heart of this thesis lies architect Philip Johnson¿s modern day ruin, the Tent
of Tomorrow, an iconic, abandoned pavilion from New York¿s 1964-1965 World¿s Fair.
Utilizing the Tent of Tomorrow as a case study, this thesis seeks to address both the
immediate need for a redesign of the structure and the long-term need for an integrated
method of analyzing preservation projects. A method for analyzing the structure
spanning multiple disciplines that acknowledges engineering, social, and artistic aspects
in the preservation and redesign process was developed. This multi-disciplinary
assessment, termed the theory of preservation potential, draws from engineering
Professor David Billington¿s theory of structural art. Utilizing the theory of preservation
potential, an analysis of the Tent of Tomorrow was carried out which produced findings
aimed at assisting in the structure¿s redesign. These findings were then used to redesign
the structure¿s roof. It is the hope of the author that future development of the theory of
preservation potential leads to a methodical and integrated system that informs how to
move forward with any preservation project
Time-varying ice crystal orientation in thunderstorms observed with multiparameter radar
No full textRepeated changes associated with lightning have been observed with multiparameter radar in the echoes from the tops of Florida thunderstorms. These lightning-related radar signatures are interpreted as changes in the orientation of ice crystals being preferentially aligned parallel to the in-cloud electric field. The changes occur at intervals on the order of 10 s and are easily observed in the signatures of the differential propagation phase shift and the linear depolarization ratio which are sensitive to propagation effects caused by the oriented ice crystals. Orientation of ice crystals aloft has been previously observed using circularly polarized radar while the simultaneous differential phase shift and linear depolarization measurements reported here were obtained with a dual-linear polarized radar. The observations indicate crystal orientation angles greater than 45° and occasionally near vertical. In one case, the crystals were found to be oriented in a layer near radar cloud top spanning a 20-km range and 3 km in depth
Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields
No full textSoil moisture is highly variable in space and time, and deficits (i.e., droughts) play an important role in modulating crop yields. Limited hydroclimate and yield data, however, hamper drought impact monitoring and assessment at the farm field scale. This study demonstrates the potential of using field-scale soil moisture simulations to support highresolution agricultural yield prediction and drought monitoring at the smallholder farm field scale. We present a multiscale modeling approach that combines HydroBlocks a physically based hyper-resolution land surface model (LSM) with machine learning. We used HydroBlocks to simulate root zone soil moisture and soil temperature in Zambia at 3 h 30 m resolution. These simulations, along with remotely sensed vegetation indices, meteorological data, and descriptors of the physical landscape (related to topography, land cover, and soils) were combined with district-level maize data to train a random forest (RF) model to predict maize yields at district and field scales (250 m). Our model predicted yields with an average testing coefficient of determination (R2) of 0.57 and mean absolute error (MAE) of 310 kgha-1 using year-based cross-validation. Our predicted maize losses due to the 2015 2016 El Niño drought agreed well with losses reported by the Food and Agriculture Organization (FAO). Our results reveal that soil moisture is the strongest and most reliable predictor of maize yield, driving its spatial and temporal variability. Soil moisture was also a more effective indicator of drought impacts on crops than precipitation, soil and air temperatures, and remotely sensed normalized difference vegetation index (NDVI)-based drought indices. This study demonstrates how field-scale modeling can help bridge the spatial-scale gap between drought monitoring and agricultural impacts. © 2021 Author(s).Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Dominant role of plant physiology in trend and variability of gross primary productivity in North America
No full textInternational audienceAnnual gross primary productivity (GPP) varies considerably due to climate-induced changes in plant phenology and physiology. However, the relative importance of plant phenology and physiology on annual GPP variation is not clear. In this study, a Statistical Model of Integrated Phenology and Physiology (SMIPP) was used to evaluate the relative contributions of maximum daily GPP (GPP max) and the start and end of growing season (GS start and GS end) to annual GPP variability, using a regional GPP product in North America during 2000-2014 and GPP data from 24 AmeriFlux sites. Climatic sensitivity of the three indicators was assessed to investigate the climate impacts on plant phenology and physiology. The SMIPP can explain 98% of inter-annual variability of GPP over mid-and high latitudes in North America. The long-term trend and inter-annual variability of GPP are dominated by GPP max both at the ecosystem and regional scales. During warmer spring and autumn, GS start is advanced and GS end delayed, respectively. GPP max responds positively to summer temperature over high latitudes (40-80°N), but negatively in mid-latitudes (25-40°N). This study demonstrates that plant physiology, rather than phenology, plays a dominant role in annual GPP variability, indicating more attention should be paid to physiological change under futher climate change. The importance of plant phenology shifts and physiology change on annual GPP variability is evident 1-4. Warming-induced earlier leaf emergence enhances terrestrial carbon uptake in spring, whereas later leaf senescence in autumn also leads to a smaller increase in carbon uptake in North American temperate forests 5. However, drought events associated with high temperature and low water availability can decrease plant photo-synthetic uptake 6-8. In regions exposed to summer drought, an increase of leaf area in earlier spring can accelerate soil drying, and lead to increased vulnerability of GPP in summer 9,10. In terms of net carbon balance, carbon loss during summer drought can negate increased uptake in warmer springs and autumns 11-13 , related to the negative covariance between increased spring productivity and decreased yearly productivity. The different responses of plant phenology and physiology to climate anomalies, and the contributions of phenological and physiological changes to annual GPP variability must thus be disentangled. The joint control of plant phenology and physiology on annual GPP can be expressed by constructing a statistical model 4,14 , which uses indicators to represent plant phenological and physiological changes. Phenology is about the time and duration of a process or event. The length of carbon uptake period (CUP), and the start (GS start) and the end (GS end) of the growing season, can be used as indicators of plant phenology. Plant pho-tosynthesis is an important process of plant physiology, and can reflect the responses of plant physiology t
