社会生態システムの空間的レジリアンス ― ザンビア南部州における世帯レベルのリスクと対処戦略 ―

Spatial relationships and spatial interactions affect the resilience in social-ecological systems in complex ways. This report reviews relevant literature to demonstrate the utility of a spatial perspective for the analysis of resilience in social-ecological systems, and provides selective examples from preliminary analysis of the extensive household survey in the Eastern Province (Zambia). We employ the term “spatial resilience” to characterize how spatial arrangement, spatial interactions and spatial context relate to the resilience of smallholders to climate variability. We also present a basic framework for transitioning this preliminary work to a more comprehensive analysis of the Eastern and Southern Province study areas.和文のものは、英文の報告の内容を要約したものとなってい

Global synthesis of vegetation control on evapotranspiration partitioning

Author's manuscript made available in accordance with the publisher's policy.Evapotranspiration (ET) is an important component of the global hydrological cycle. However, to what extent transpiration ratios (T/ET) are controlled by vegetation and the mechanisms of global-scale T/ET variations are not clear. We synthesized all the published papers that measured at least two of the three components (E, T, and ET) and leaf area index (LAI) simultaneously. Nonlinear relationships between T/ET and LAI were identified for both the overall data set and agricultural or natural data subsets. Large variations in T/ET occurred across all LAI ranges with wider variability at lower LAI. For a given LAI, higher T/ET was observed during later vegetation growing stage within a season. We developed a function relating T/ET to the growing stage relative to the timing of peak LAI. LAI and growing stage collectively explained 43% of the variations in the global T/ET data set, providing a new way to interpret and model global T/ET variability

Uncertainties in the assessment of the isotopic composition of surface fluxes: A direct comparison of techniques using laser-based water vapor isotope analyzers

Author's manuscript made available in accordance with the publisher's policy.The isotopic composition of surface fluxes is a key environmental tracer currently estimated with a variety of methods, including: Keeling mixing models, the flux-gradient technique, and eddy covariance. We present a direct inter-comparison of these three methods used to estimate the isotopic ratio of water vapor in surface fluxes (δET) over half-hour periods, with a focus on the statistical uncertainty of each method image We develop expressions for image a function of instrument precision, sample size, and atmospheric conditions. Uncertainty estimators are validated with high frequency (1 Hz) data from multiple configurations of commercial off-axis integrated cavity output spectroscopy (ICOS) systems. We find measurement techniques utilizing the high frequency capabilities of ICOS system outperform those methods where a single average of the isotopic composition is obtained at each height, with improvements attributed to large sample counts and increased variation in observed concentrations. Analytically, and with supporting data, we show that over 30 minute periods the Keeling plot and flux-gradient techniques produce nearly identicalδET and image values, while eddy covariance calculations always introduce more uncertainty given the same high frequency data. This additional uncertainty is proportional to the reciprocal of the correlation coefficient between vertical wind speed and water vapor mixing ratio. Finally, given the inverse relationship between δET uncertainties and the range of water vapor observed, we propose that experimental designs should attempt to maximize both sample count and the coefficient of variation in atmospheric water vapor

Stable Isotopes of Water Vapor in the Vadose Zone: A Review of Measurement and Modeling Techniques

Author's manuscript made available in accordance with the publisher's policy.The stable isotopes of soil water vapor can be useful in the study of ecosystem processes. Modeling has historically dominated the measurement of these parameters due to sampling difficulties. We discuss new developments in modeling and measurement, including the implications of including soil water potential in the Craig–Gordon modeling framework. The stable isotopes of soil water vapor are useful tracers of hydrologic processes occurring in the vadose zone. The measurement of soil water vapor isotopic composition (δ18O, δ2H) is challenging due to difficulties inherent in sampling the vadose zone airspace in situ. Historically, these parameters have therefore been modeled, as opposed to directly measured, and typically soil water vapor is treated as being in isotopic equilibrium with liquid soil water. We reviewed the measurement and modeling of soil water vapor isotopes, with implications for studies of the soil–plant–atmosphere continuum. We also investigated a case study with in situ measurements from a soil profile in a semiarid African savanna, which supports the assumption of liquid–vapor isotopic equilibrium. A contribution of this work is to introduce the effect of soil water potential (Ѱ) on kinetic fractionation during soil evaporation within the Craig–Gordon modeling framework. Including Ѱ in these calculations becomes important for relatively dry soils (Ѱ < −10 MPa). Additionally, we assert that the recent development of laser-based isotope analytical systems may allow regular in situ measurement of the vadose zone isotopic composition of water in the vapor phase. Wet soils pose particular sampling difficulties, and novel techniques are being developed to address these issues

Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa

Climate change is expected to modify intraseasonal rainfall variability, arising from shifts in rainfall frequency, intensity and seasonality. These intra-seasonal changes are likely to have important ecological impacts on terrestrial ecosystems. Yet, quantifying these impacts across biomes and large climate gradients is largely missing. This gap hinders our ability to better predict ecosystem services and their responses to climate change, especially for arid and semi-arid ecosystems. Here we use a synthetic weather generator and an independently validated vegetation dynamic model (SEIB-Dynamic Global Vegetation Model, DGVM) to virtually conduct a series of "rainfall manipulation experiments" to study how changes in the intra-seasonal rainfall variability affect continent-scale ecosystem responses across Africa. We generate different rainfall scenarios with fixed total annual rainfall but shifts in (i) frequency vs. intensity, (ii) rainy season length vs. frequency, (iii) intensity vs. rainy season length. These scenarios are fed into SEIB-DGVM to investigate changes in biome distributions and ecosystem productivity. We find a loss of ecosystem productivity with increased rainfall frequency and decreased intensity at very low rainfall regimes ( 1800mm year-11) where radiation limitation prevents further productivity gains. This result reconciles seemingly contradictory findings in previous field studies on the impact of rainfall frequency/intensity on ecosystem productivity. We also find that changes in rainy season length can yield more dramatic ecosystem responses compared with similar percentage changes in rainfall frequency or intensity, with the largest impacts in semi-arid woodlands. This study demonstrates that intra-seasonal rainfall characteristics play a significant role in influencing ecosystem function and structure through controls on ecohydrological processes. Our results suggest that shifts in rainfall seasonality have potentially large impacts on terrestrial ecosystems, and these understudied impacts should be explicitly examined in future studies of climate impacts

Ecosystem-scale spatial heterogeneity of stable isotopes of soil nitrogen in African savannas

Author's manuscript made available in accordance with the publisher's policy.Soil 15N is a natural tracer of nitrogen (N) cycling. Its spatial distribution is a good indicator of processes that are critical to N cycling and of their controlling factors integrated both in time and space. The spatial distribution of soil δ15N and its underlying drivers at sub-kilometer scales are rarely investigated. This study utilizes two sites (dry vs. wet) from a megatransect in southern Africa encompassing locations with similar soil substrate but different rainfall and vegetation, to explore the effects of soil moisture and vegetation distribution on ecosystem-scale patterns of soil δ15N. A 300-m long transect was set up at each site and surface soil samples were randomly collected for analyses of δ15N, %N and nitrate content. At each soil sampling location the presence of grasses, woody plants, Acacia species (potential N fixer) as well as soil moisture levels were recorded. A spatial pattern of soil δ15N existed at the dry site, but not at the wet site. Woody cover distribution determined the soil δ15N spatial pattern at ecosystem-scale; however, the two Acacia species did not contribute to the spatial pattern of soil δ15N. Grass cover was negatively correlated with soil δ15N at both sites owing to the lower foliar δ15N values of grasses. Soil moisture did not play a role in the spatial pattern of soil δ15N at either site. These results suggest that vegetation distribution, directly, and water availability, indirectly, affect the spatial patterns of soil δ15N through their effects on woody plant and grass distributions

Using atmospheric trajectories to model the isotopic composition of rainfall in central Kenya

Publisher’s version made available under a Creative Commons license.The isotopic composition of rainfall (δ2H and δ18O) is an important tracer in studies of the ecohydrology, plant physiology, climate and biogeochemistry of past and present ecosystems. The overall continental and global patterns in precipitation isotopic composition are fairly well described by condensation temperature and Rayleigh fractionation during rainout. However, these processes do not fully explain the isotopic variability in the tropics, where intra-storm and meso-scale dynamics may dominate. Here we explore the use of atmospheric back-trajectory modeling and associated meteorological variables to explain the large variability observed in the isotopic composition of individual rain events at the study site in central Kenya. Individual rain event samples collected at the study site (n = 41) range from −51‰ to 31‰ for δ2H and the corresponding monthly values (rain volume-weighted) range from −15‰ to 15‰. Using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, we map back-trajectories for all individual rain hours occurring at a research station in central Kenya from March 2010 through February 2012 (n = 544). A multiple linear regression analysis demonstrates that a large amount of variation in the isotopic composition of rainfall can be explained by two variables readily obtained from the HYSPLIT model: (1) solar radiation along the trajectory for 48 hours prior to the event, and (2) distance covered over land. We compare the measurements and regression model results to the isotopic composition expected from simple Rayleigh distillation along each trajectory. The empirical relationship described here has applications across temporal scales. For example, it could be used to help predict short-term changes in the isotopic composition of plant-available water in the absence of event-scale sampling. One can also reconstruct monthly, seasonal and annual weighted mean precipitation isotope signatures for a single location based only on hourly rainfall data and HYSPLIT model results. At the study site in East Africa, the annual weighted mean δ2H from measured and modeled values are −7.6‰ and −7.4‰, respectively, compared to −18‰ predicted for the study site by the Online Isotopes in Precipitation Calculator

Global Patterns of the Contributions of Storm Frequency, Intensity, and Seasonality to Interannual Variability of Precipitation

Interannual variation in precipitation totals is a critical factor governing the year-to-year availability of water resources, yet the connection between interannual precipitation variability and underlying event- and season-scale precipitation variability remains unclear. In this study, tropical and midlatitude precipitation characteristics derived from extensive station records and high-frequency satellite observations were analyzed to attribute the fraction of interannual variability arising as a result of individual variability in precipitation event intensity, frequency, and seasonality, as well as the cross-correlation between these factors at the global scale. This analysis demonstrates that variability in the length of the wet season is the most important factor globally, causing 52% of the total interannual variability, while variation in the intensity of individual rainfall events contributes 31% and variability in interstorm wait times contributes only 17%. Spatial patterns in the contribution of each of these intra-annual rainfall characteristics are informative, with regions such as Indonesia and southwestern North America primarily influenced by seasonality, while regions such as the eastern United States, central Africa, and the upper Amazon basin are strongly influenced by storm intensity and frequency. A robust cross-correlation between climate characteristics is identified in the equatorial Pacific, revealing an increased interannual variability over what is expected based on the variability of individual events. This decomposition of interannual variability identifies those regions where accurate representation of daily and seasonal rainfall statistics is necessary to understand and correctly model rainfall variability at longer time scales.Keywords: Interannual variability, Seasonal variability, Intraseasonal variability, Variabilit

Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia

Given the varying manifestations of climate change over time and the influence of climate perceptions on adaptation, it is important to understand whether farmer perceptions match patterns of environmental change from observational data. We use a combination of social and environmental data to understand farmer perceptions related to rainy season onset. Household surveys were conducted with 1171 farmers across Zambia at the end of the 2015/16 growing season eliciting their perceptions of historic changes in rainy season onset and their heuristics about when rain onset occurs. We compare farmers' perceptions with satellite-gauge-derived rainfall data from the Climate Hazards Group Infrared Precipitation with Station dataset and hyper-resolution soil moisture estimates from the HydroBlocks land surface model. We find evidence of a cognitive bias, where farmers perceive the rains to be arriving later, although the physical data do not wholly support this. We also find that farmers' heuristics about rainy season onset influence maize planting dates, a key determinant of maize yield and food security in sub-Saharan Africa. Our findings suggest that policy makers should focus more on current climate variability than future climate change.National Science Foundation [SES-1360463, BCS-1115009, BCS-1026776]6 month embargo; published online: 29 March 2019This 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]

Dynamic interactions of ecohydrological and biogeochemical processes in water-limited systems

Water is the essential reactant, catalyst, or medium for many biogeochemical reactions, thus playing an important role in the activation and deactivation of biogeochemical processes. The coupling b ..