Social learning, selection, and HIV infection: Evidence from Malawi

"This paper examines social learning regarding HIV infection, using HIV test results and sibling death data from Malawi. In the analysis, we compare hypotheses on social learning, selection. and common factors. Empirical results show that young women are less likely to be HIV-infected if they observed prime-age deaths among their siblings, whereas HIV infection is found to be positively related to prime-age sibling deaths among older women. This supports the social-learning hypothesis. Notably, schooling reinforces the social-learning effect of sibling deaths on HIV infection in women regardless of age. The above findings are robust to age (cohort) effects and unobserved location factors." from authors' abstractSocial learning, HIV infection, AIDS (Disease) Africa, Sub-Saharan, siblings,

Marriage behavior response to prime-age adult mortality: Evidence from Malawi

"This paper examines the effect of AIDS-related mortality of the prime-age adult population on marriage behavior among women in Malawi. A rise in prime-age adult mortality increases risks associated with the search for a marriage partner in the marriage market. A possible behavioral change in the marriage market in response to an increase in prime-age adult mortality is for marriage to occur earlier to avoid women's exposure to HIV/AIDS risks under the condition that the risks are higher during singlehood. We test this hypothesis using micro data from Malawi, where prime-age adult mortality has drastically increased. In the analysis, we estimate prime-age adult mortality that sample women have observed during the adolescent period by utilizing retrospective information on the death of their siblings. Empirical analysis shows that excess prime-age adult mortality observed in the local marriage market (district) lowers the marriage age for females and reduces their premarital sexual activities. Since a lower age for first marriage implies less schooling completed, we expect that the average schooling achievement among women would decline. This behavioral change also implies a longer reproduction period during their marriage, which may lead to a higher fertility rate. However, the second implication should be discounted if the reduction of sexual activities also applies to the married population. Lower schooling attainment among women has further implications on human capital formation in the next generation." from Author's AbstractHIV/AIDS, Marriage, Sexual behavior,

Income growth and gender bias in childhood mortality in developing countries:

"With poverty studies having shifted their focus from household poverty to individual poverty, a number of studies have started to examine intrahousehold resource allocation, especially gender bias within the household as potential causes of poverty. The literature has highlighted the existence of gender inequalities in South Asia, attributed to strong preferences for male offspring stemming from cultural and traditional customs. Only a few studies focused on the regional difference in the extent of gender bias and its response to income growth. To fill a void in previous studies, this study analyzes regional differences in gender discrimination, taking into account time-series variations. Furthermore, we test whether economic factors are responsible for gender bias in child mortality. There are two main objectives in this study. First, through a comprehensive literature review and a careful treatment of data compilation, regional features and recent trends in gender bias in children's health outcomes are updated. We find strong evidence of severe disparity in child health against girls in South Asia; in contrast, no such anti-female gender bias exists in Sub-Saharan Africa. Second, this paper empirically tests the relationship between gender biases in child mortality and income growth using carefully-compiled new country-level panel data, paying attention to the possibility that such relationship differs between regions and changes over time. To investigate the relationship, two types of data sets are used: (1) new cross-country panel data of childhood mortality rates by sex, collected from various sources of macro statistics, such as DHS stat and WHO statistics; and (2) our own estimates for age-specific child mortality rates of children, constructed from the retrospective information on birth and death histories included in micro data of each round of the Demographic and Health Surveys (DHS). The empirical result suggests that income growth is correlated with the reduction of the anti-female bias in childhood mortality in most regions of the developing world—including South Asia. This result is reasonable, since income growth leads to an increase in nutrition intake (food consumption) and in health related inputs. In sharp contrast, the regression result does not show any significant correlation between gender biases in child health outcomes and income growth in Sub-Saharan Africa. While previous studies focused on the severe gender bias in South Asia, this study examined the correlation between income growth and gender bias and found a new dimension of regional contrast between Sub-Saharan Africa and other regions." from Authors' AbstractGender bias, Intrahousehold resource allocation, Childhood mortality, Sub-Saharan Africa, Developing countries, Poverty reduction,

Mortality, mobility, and schooling outcomes among orphans: Evidence from Malawi

"A tremendous increase in the number of orphans associated with a sharp rise in prime-age adult mortality due to AIDS has become a serious problem in Sub-Saharan Africa. In fact, more than 30 percent of school-aged children have lost at least one parent in Malawi. Lack of investments in human capital and adverse conditions during childhood are often associated with lower living standards in the future. Therefore, if orphans face an increased risk of poverty, exploitation, malnutrition, and poorer access to health care and schooling, early intervention is critical so as to avoid the potential poverty trap. The purpose of this study is to investigate the impacts of orphanhood/parental death on children's mortality risks, migration behaviors, and schooling outcomes, by using household panel data from Malawi, which has the eighth-highest HIV prevalence rates in the world. A number of studies have analyzed the relationship between parental death and children's school enrollment, but very few have considered mortality and mobility of orphans. This study uses the Malawi Complementary Panel Survey (CPS) conducted by the International Food Policy Research Institute (IFPRI) and another institution between January 2000 and July 2004. Since these panel data do not track individuals that move to other households, we take into account sample attritions of children. This study uses three estimation methodologies to explore different aspects of impacts. First, we analyze regression models with controls for various sets of household and child characteristics and for village fixed effects to examine heterogeneous impacts of orphanhood across different types of households. Second, we employ household fixed-effect models to test the differential effects of orphanhood on welfare outcomes among different types of orphans living in the same household. Third, we examine the impact of recent parental death—parental death between 2000 and 2004—on schooling outcomes. Empirical results show that maternal orphans, as well as double orphans, tend to face higher mortality risks and lower schooling outcomes than paternal and non-orphans do. This is especially so for boys. Similarly, maternal and double orphans tend to move to other households more frequently. Compared to adolescent orphans, the impact on younger orphans who enrolled in school after the introduction of universal free primary education in 1994 is more muted, suggesting that free primary education policies may have mitigated adverse shocks from parental death. More interestingly, the impacts of orphanhood on schooling outcomes are significantly gender-dependent: boys face severer negative impacts of being orphans than girls do. These empirical results are robust to sample attrition due to mortality and mobility." from Authors' AbstractOrphans, Mortality, HIV/AIDS, Mobility, Sample attrition, Education,

The biophysical climate mitigation potential of boreal peatlands during the growing season

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.Peer reviewe

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Wetland methane (CH4) emissions (FCH4) are important in global carbon budgets and climate change assessments. Currently, FCH4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that FCH4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH4 and temperature, suggesting larger FCH4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments. Wetland methane emissions contribute to global warming, and are oversimplified in climate models. Here the authors use eddy covariance measurements from 48 global sites to demonstrate seasonal hysteresis in methane-temperature relationships and suggest the importance of microbial processes.Peer reviewe

Upscaling Wetland Methane Emissions From the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0):Model Development, Network Assessment, and Budget Comparison

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4 y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).</p

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by similar to 17 +/- 11 days, and lagged air and soil temperature by median values of 8 +/- 16 and 5 +/- 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.Peer reviewe

Upscaling Wetland Methane Emissions From the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Wetlands are responsible for 20%-31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency similar to 0.52-0.63 and 0.53). UpCH(4) estimated annual global wetland CH4 emissions of 146 +/- 43 TgCH4 y(-1) for 2001-2018 which agrees closely with current bottom-up land surface models (102-181 TgCH4 y(-1)) and overlaps with top-down atmospheric inversion models (155-200 TgCH4 y -1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25 degrees from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ ORNLDAAC/2253).Plain Language Summary Wetlands account for a large share of global methane emissions to the atmosphere, but current estimates vary widely in magnitude (similar to 30% uncertainty on annual global emissions) and spatial distribution, with diverging predictions for tropical rice growing (e.g., Bengal basin), rainforest (e.g., Amazon basin), and floodplain savannah (e.g., Sudd) regions. Wetland methane model estimates could be improved by increased use of land surface methane flux data. Upscaling approaches use flux data collected across globally distributed measurement networks in a machine learning framework to extrapolate fluxes in space and time. Here, we train and evaluate a methane upscaling model (UpCH4) and use it to generate monthly, globally gridded wetland methane emissions estimates for 2001-2018. The UpCH4 model uses only six predictor variables among which temperature is dominant. Global annual methane emissions estimates and associated uncertainty ranges from upscaling fall within state-of-the-art model ensemble estimates from the Global Carbon Project (GCP) methane budget. In some tropical regions, the spatial pattern of UpCH4 emissions diverged from GCP predictions, however, inclusion of flux measurements from additional ground-based sites, together with refined maps of tropical wetlands extent, could reduce these prediction uncertainties

The ABCflux database : Arctic-boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic-boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic-boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June-August; 32 %), and fewer observations were available for autumn (September-October; 25 %), winter (December-February; 18 %), and spring (March-May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).Peer reviewe