Photosynthetic capacity, canopy size and rooting depth mediate response to heat and water stress of annual and perennial grain crops

Perennial grain crops are promoted as an alternative to annual staple crops to reduce negative environmental effects of agriculture and support a variety of ecosystem services. While perennial grains have undergone extensive testing, their vulnerability to projected future warmer and drier growing conditions remains unclear. To fill this gap, we compared leaf temperature and gas exchange rates of annual wheat and different perennial wheat ideotypes using a multi-layer process-based eco-hydrological model. The model combines leaf-level gas exchange, optimality principles regulating stomatal conductance, energy balance, radiative and momentum transfer inside the canopy, as well as soil water balance. Wheat ideotypes are parameterized based on an extensive review of field data. When compared with annual wheat, perennial wheat ideotypes with high leaf area index had between 12% and 39% higher canopy transpiration and net CO2 assimilation, depending on their photosynthetic capacity and water status. Differences in leaf temperature and instantaneous water use efficiency between annual wheat and the perennial ideotypes were moderate (-0.5 to +0.4 & DEG;C and -6 to +2%, respectively). Low soil water availability did not alter the ranking of ideotypes in terms of canopy temperature and gas exchanges. During a prolonged dry down, cumulated water use was higher and canopy temperature lower in perennial than annual ideotypes, thanks to the deeper roots, whereas cumulated net CO2 fixation depended on the specific traits and air temperature. Leaf-specific and whole plant characteristics interacted with hydro-meteorological conditions in defining the perennial's vulnerability envelopes to potential heat and water stress. These findings underline the importance of plant characteristics, and particularly leaf area and rooting depth, in defining the suitability of perennial grain crops under future climates

Contrasting Physiological and Environmental Controls of Evapotranspiration over Kernza Perennial Crop, Annual Crops, and C4 and Mixed C3/C4 Grasslands

This work is licensed under a Creative Commons Attribution 4.0 International License.Perennial grain crops have been suggested as a more sustainable alternative to annual crops. Yet their water use and how they are impacted by environmental conditions have been seldom compared to those of annual crops and grasslands. Here, we identify the dominant mechanisms driving evapotranspiration (ET), and how they change with environmental conditions in a perennial Kernza crop (US-KLS), an annual crop field (US-ARM), a C4 grassland (US-KON), and a mixed C3/C4 grassland (US-KFS) in the Central US. More specifically, we have utilized the omega (Ω) decoupling factor, which reflects the dominant mechanisms responsible for the evapotranspiration (ET) of the canopy. Our results showed that the US-ARM site was the most coupled with the lowest decoupling values. We also observed differences in coupling mechanism variables, showing more sensitivity to the water fluctuation variables as opposed to the radiative flux variables. All of the sites showed their lowest Ω value in 2012, the year of the severe drought in the Central US. The 2012 results further indicate the dependence on the water fluctuation variables. This was especially true with the perennial Kernza crop, which displayed much higher soil moisture values. In this regard, we believe that the ability of perennial Kernza to resist water stress and retain higher soil moisture values is both a result of its deeper roots, in addition to its higher Ω value. Through the analysis of both the site comparison and the comparison of the differences in years, we conclude that the perennial Kernza crop (US-KLS) is more similar in its microclimate effects to the C4 (US-KON) and mixed C3/C4 (US-KFS) grassland sites as opposed to its annual counterpart (US-ARM). This has implications for the role of perennial agriculture for addressing agricultural resilience under changing climate conditions

The sensitivity of carbon exchanges in Great Plains grasslands to precipitation variability

In the Great Plains, grassland carbon dynamics differ across broad gradients of precipitation and temperature, yet finer-scale variation in these variables may also affect grassland processes. Despite the importance of grasslands, there is little information on how fine-scale relationships compare between them regionally. We compared grassland C exchanges, energy partitioning and precipitation variability in eight sites in the eastern and western Great Plains using eddy covariance and meteorological data. During our study, both eastern and western grasslands varied between an average net carbon sink and a net source. Eastern grasslands had a moderate vapor pressure deficit (VPD = 0.95 kPa) and high growing season gross primary productivity (GPP = 1010 ± 218 g C m−2 yr−1). Western grasslands had a growing season with higher VPD (1.43 kPa) and lower GPP (360 ± 127 g C m−2 yr−1). Western grasslands were sensitive to precipitation at daily timescales, whereas eastern grasslands were sensitive at monthly and seasonal timescales. Our results support the expectation that C exchanges in these grasslands differ as a result of varying precipitation regimes. Because eastern grasslands are less influenced by short-term variability in rainfall than western grasslands, the effects of precipitation change are likely to be more predictable in eastern grasslands because the timescales of variability that must be resolved are relatively longer. We postulate increasing regional heterogeneity in grassland C exchanges in the Great Plains in coming decades.Konza Prairie Biological Station. Grant Number: DEB-0823341U.S. Department of Energy. Grant Number: DE-AC02-05CH11231U.S. Department of Agriculture. Grant Number: 2014-67003-22070DOE-NIGEC. Grant Number: 26-6223-7230-002Natural Sciences and Engineering Research Council of Canada Discovery. Grant Number: RGPIN-2014-05882Sevilleta LTERNAS

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia

In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001–December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance

Effects of land‐cover changes on the partitioning of surface energy and water fluxes in Amazonia using high‐resolution satellite imagery

Spatial variability of surface energy and water fluxes at local scales is strongly controlled by soil and micrometeorological conditions. Thus, the accurate estimation of these fluxes from space at high spatial resolution has the potential to improve prediction of the impact of land‐use changes on the local environment. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) data were used to examine the partitioning of surface energy and water fluxes over different land‐cover types in one wet year (2004) and one drought year (2005) in eastern Rondonia state, Brazil. The spatial variation of albedo, net radiation (Rn), soil (G) and sensible (H) heat fluxes, evapotranspiration (ET), and evaporative fraction (EF) were primarily related to the lower presence of forest (primary [PF] or secondary [SF]) in the western side of the Ji‐Parana River in comparison with the eastern side, located within the Jaru Biological Reserve protected area. Water limitation in this part of Amazonia tends to affect anthropic (pasture [PA] and agriculture [AG]) ecosystems more than the natural land covers (PF and SF). We found statistically significant differences on the surface fluxes prior to and ~1 year after the deforestation. Rn over forested areas is ~10% greater in comparison with PA and AG. Deforestation and consequent transition to PA or AG increased the total energy (~200–400%) used to heat the soil subsurface and raise air temperatures. These differences in energy partitioning contributed to approximately three times higher ET over forested areas in comparison with nonforested areas. The conversion of PF to AG is likely to have a higher impact in the local climate in this part of Amazonia when compared with the change to PA and SF, respectively. These results illustrate the importance of conserving secondary forest areas in Amazonia.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/1/eco2126_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/2/eco2126.pd

Analysis of Precipitation and Evapotranspiration in Atlantic Rainforest Remnants in Southeastern Brazil from Remote Sensing Data

The Atlantic Rainforest has been intensely devastated since the beginning of the colonization of Brazil, mainly due to wood extraction and urban and rural settlement. Although the Atlantic Rainforest has been reduced and fragmented, its remnants are important sources of heat and water vapor to the atmosphere. The present study aimed to characterize and to analyze the temporal dynamics of precipitation and evapotranspiration in the Atlantic Rainforest remnants in São Paulo state, southeastern Brazil, for the period from January 2000 to December 2010. To achieve this, global precipitation and evapotranspiration data from TRMM satellite and MOD16 algorithm as well as forest remnant maps produced by SOS Mata Atlântica Foundation and Brazilian National Institute for Space Research (INPE) were used. Results found in this study demonstrated that the use of remote sensing was an important tool for analyzing hydrological variables in Atlantic Rainforest remnants, which can contribute to better understand the interaction between tropical forests and the atmosphere, and for generating input data necessary for surface models coupled to atmospheric general circulation models

Methods to Evaluate Land-Atmosphere Exchanges in Amazonia Based on Satellite Imagery and Ground Measurements

During the last three decades, intensive campaigns and experiments have been conducted for acquiring micrometeorological data in the Amazonian ecosystems, which has increased our understanding of the variation, especially seasonally, of the total energy available for the atmospheric heating process by the surface, evapotranspiration and carbon exchanges. However, the measurements obtained by such experiments generally cover small areas and are not representative of the spatial variability of these processes. This chapter aims to discuss several algorithms developed to estimate surface energy and carbon fluxes combining satellite data and micrometeorological observations, highlighting the potentialities and limitations of such models for applications in the Amazon region. We show that the use of these models presents an important role in understanding the spatial and temporal patterns of biophysical surface parameters in a region where most of the information is local. Data generated may be used as inputs in earth system surface models allowing the evaluation of the impact, both in regional as well as global scales, caused by land-use and land-cover changes

Differential effects of extreme drought on production and respiration: synthesis and modeling analysis

This is the published version, also available here: http://dx.doi.org/10.5194/bg-11-621-2014, 2014.Extremes in climate may severely impact ecosystem structure and function, with both the magnitude and rate of response differing among ecosystem types and processes. We conducted a modeling analysis of the effects of extreme drought on two key ecosystem processes, production and respiration, and, to provide a broader context, we complemented this with a synthesis of published results that cover a wide variety of ecosystems. The synthesis indicated that across a broad range of biomes, gross primary production (GPP) was generally more sensitive to extreme drought (defined as proportional reduction relative to average rainfall periods) than was ecosystem respiration (ER). Furthermore, this differential sensitivity between production and respiration increased as drought severity increased; it occurred only in grassland ecosystems, and not in evergreen needle-leaf and broad-leaf forests or woody savannahs. The modeling analysis was designed to enable a better understanding of the mechanisms underlying this pattern, and focused on four grassland sites arrayed across the Great Plains, USA. Model results consistently showed that net primary productivity (NPP) was reduced more than heterotrophic respiration (Rh) by extreme drought (i.e., 67% reduction in annual ambient rainfall) at all four study sites. The sensitivity of NPP to drought was directly attributable to rainfall amount, whereas the sensitivity of Rh to drought was driven by soil drying, reduced carbon (C) input and a drought-induced reduction in soil C content – a much slower process. However, differences in reductions in NPP and Rh diminished as extreme drought continued, due to a gradual decline in the soil C pool leading to further reductions in Rh. We also varied the way in which drought was imposed in the modeling analysis; it was either imposed by simulating reductions in rainfall event size (ESR) or by reducing rainfall event number (REN). Modeled NPP and Rh decreased more by ESR than REN at the two relatively mesic sites but less so at the two xeric sites. Our findings suggest that responses of production and respiration differ in magnitude, occur on different timescales, and are affected by different mechanisms under extreme, prolonged drought