Catalytic Social Entrepreneurship to Combat Desperate Poverty: A Systems Approach

Any credible agenda that seeks to eradicate global poverty must seek to correct the structural injustices and inequities that cause and perpetuate desperate endemic poverty. Such an agenda must aim not merely to aid the poor with grants, welfare and subsidies, but it must primarily seek to enhance the capabilities, skills, access and opportunities of the marginalized to participate on more equitable terms, in the dynamic process of overall economic growth. We apply a systems approach to poverty, the latter itself being a pernicious system. Eradication of global desperate poverty and its unjust structural causes can be done through two concurrent systems-thinking based strategies: (a) micro catalytic social entrepreneurship that leads to catalytic innovations that alleviate poverty, and (b) macro social catalytic political entrepreneurship that radically innovates legislation or designs macro-policy intervention systems that can effectively dismantle existing unjust structures of social injustice and inequities – the causes that perpetuate endemic global poverty. Using the theories of catalytic innovations and the bottom of the pyramid, we focus on solution (a) as being feasible, viable and doable and in the long run having the potential for eradicating global desperate poverty. We also provide two case studies where solution (b) was effectively implemented. The main proposition of the paper is that the use of both micro- and macro- catalyst can help alleviate poverty in the world.   Keywords: Micro catalyst, macro catalyst, global poverty, system approach, catalytic innovation, macro-policy intervention

Substantial carbon loss respired from a corn-soybean agroecosystem highlights the importance of careful management as we adapt to changing climate

Understanding agroecosystem carbon (C) cycle response to climate change and management is vital for maintaining their long-term C storage. We demonstrate this importance through an in-depth examination of a ten-year eddy covariance dataset from a corn-corn-soybean crop rotation grown in the Midwest United States. Ten-year average annual net ecosystem exchange (NEE) showed a net C sink of -0.39 Mg C ha-1 yr-1. However, NEE in 2014 and 2015 from the corn ecosystem was 3.58 and 2.56 Mg C ha-1 yr-1, respectively. Most C loss occurred during the growing season, when photosynthesis should dominate and C fluxes should reflect a net ecosystem gain. Partitioning NEE into gross primary productivity (GPP) and ecosystem respiration (ER) showed this C \u27burp\u27 was driven by higher ER, with a 51% (2014) and 57% (2015) increase from the ten-year average (15.84 Mg C ha-1 yr-1). GPP was also higher than average (16.24 Mg C ha-1 yr-1) by 25% (2014) and 37% (2015), but this was not enough to offset the C emitted from ER. This increased ER was likely driven by enhanced soil microbial respiration associated with ideal growing season climate, substrate availability, nutrient additions, and a potential legacy effect from drought

ECOSTRESS: NASA's next generation mission to measure evapotranspiration from the International Space Station

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station ECOSTRESS) was launched to the International Space Station on June 29, 2018. The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as level‐3 (L3) latent heat flux (LE) data products. These data are generated from the level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are over‐represented. The 70 m high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1 km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data