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{"Abstract":["The varied topography and large elevation gradients that\n characterize the arid and semi-arid Southwest create a wide range of\n climatic conditions - and associated biomes - within relatively\n short distances. This creates an ideal experimental system in which\n to study the effects of climate on ecosystems. Such studies are\n critical given that the Southwestern U.S. has already experienced\n changes in climate that have altered precipitation patterns (Mote et\n al. 2005), and stands to experience dramatic climate change in the\n coming decades (Seager et al. 2007; Ting et al. 2007). Climate\n models currently predict an imminent transition to a warmer, more\n arid climate in the Southwest (Seager et al. 2007; Ting et al.\n 2007). Thus, high elevation ecosystems, which currently experience\n relatively cool and mesic climates, will likely resemble their lower\n elevation counterparts, which experience a hotter and drier climate.\n In order to predict regional changes in carbon storage, hydrologic\n partitioning and water resources in response to these potential\n shifts, it is critical to understand how both temperature and soil\n moisture affect processes such as evaportranspiration (ET), total\n carbon uptake through gross primary production (GPP), ecosystem\n respiration (Reco), and net ecosystem exchange of carbon, water and\n energy across elevational gradients. We are using a sequence of six\n widespread biomes along an elevational gradient in New Mexico --\n ranging from hot, arid ecosystems at low elevations to cool, mesic\n ecosystems at high elevation to test specific hypotheses related to\n how climatic controls over ecosystem processes change across this\n gradient. We have an eddy covariance tower and associated\n meteorological instruments in each biome which we are using to\n directly measure the exchange of carbon, water and energy between\n the ecosystem and the atmosphere. This gradient offers us a unique\n opportunity to test the interactive effects of temperature and soil\n moisture on ecosystem processes, as temperature decreases and soil\n moisture increases markedly along the gradient and varies through\n time within sites. This dataset examines how different stages of\n burn affects above-ground biomass production (ANPP) in a mixed\n desert-grassland. Net primary production is a fundamental ecological\n variable that quantifies rates of carbon consumption and fixation.\n Estimates of NPP are important in understanding energy flow at a\n community level as well as spatial and temporal responses to a range\n of ecological processes. Above-ground net primary production is the\n change in plant biomass, represented by stems, flowers, fruit and\n foliage, over time and incorporates growth as well as loss to death\n and decomposition. To measure this change the vegetation variables\n in this dataset, including species composition and the cover and\n height of individuals, are sampled twice yearly (spring and fall) at\n permanent 1m x 1m plots. The data from these plots is used to build\n regressions correlating biomass and volume via weights of select\n harvested species obtained in SEV157, "Net Primary Productivity\n (NPP) Weight Data." This biomass data is included in SEV292,\n "Flux Tower Seasonal Biomass and Seasonal and Annual NPP\n Data.""]}
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A Semi‐Mechanistic Model for Partitioning Evapotranspiration Reveals Transpiration Dominates the Water Flux in Drylands
Abstract Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well‐suited to dryland ecosystems, such as high sensitivity of plant water‐use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine‐scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi‐mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process‐based models, and loosely constrains time‐varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross‐wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub‐yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem‐scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.
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- PAR ID:
- 10525998
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 129
- Issue:
- 7
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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