MICROFINANCE AND CLIMATE CHANGE IMPACTS: THE CASE OF AGROAMIGO IN BRAZIL

ABSTRACTThis paper reports an empirical case study on the interface between microfinance and climate change actions. Climate change, which until recently seemed a luxury for the microfinance sector, now appears to be crucial for its future. For their low adaptive capacity, the millions of microfinance clients worldwide happen to be the most vulnerable to a changing climate. However, such an arena is still blurred from an academic viewpoint, and inexistent among Brazilian academia. Therefore, by investigating Brazil’s largest rural MFI, Agroamigo, we aim at providing an empirical contribution to green microfinance. The main conclusion is that, albeit Agroamigo offers important links to climate change initiatives, it will need to take better account of specific vulnerabilities and risks to protect its portfolio and clients better from climate change impacts.

Impact of increasing mean air temperature on the development of rice and red rice

The objective of this study was to assess the development response of cultivated rice and red rice to different increases in minimum and maximum daily air temperatures, in Santa Maria, Rio Grande do Sul State, Brazil. One hundred years climate scenarios of temperatures 0, +1, +2, +3, +4, and +5ºC, with symmetric and asymmetric increases in minimum and maximum daily air temperatures were created, using the LARS-WG Weather Generator, and a 1969-2003 database. Nine cultivated rice genotypes (IRGA 421, IRGA 416, IRGA 417, IRGA 420, BRS 7 TAIM, BR-IRGA 409, EPAGRI 109, EEA 406 and a hybrid), and two red rice biotypes (awned black hull-ABHRR, and awned yellow hull-AYHRR) were used. The dates of panicle differentiation (R1), anthesis (R4), and all grains with brown hulls (R9) were estimated with a nonlinear simulation model. Overall, the duration of the emergence-R1 phase decreased, whereas the duration of the R1-R4 and R4-R9 phases most often increased, as temperature increased in the climate change scenarios. The simulated rice development response to elevated temperature was not the same, when the increase in minimum and maximum temperature was symmetric or asymmetric.

CO2-response function of radiation use efficiency in rice for climate change scenarios

The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.

Climate change and future scenarios for palisade grass production in the state of São Paulo, Brazil

The objective of this work was to analyze future scenarios for palisade grass yield subjected to climate change for the state of São Paulo, Brazil. An empirical crop model was used to estimate yields, according to growing degree-days adjusted by one drought attenuation factor. Climate data from 1963 to 2009 of 23 meteorological stations were used for current climate conditions. Downscaled outputs of two general circulation models were used to project future climate for the 2013-2040 and 2043-2070 periods, considering two contrasting scenarios of temperature and atmospheric CO2 concentration increase (high and low). Annual dry matter yield should be from 14 to 42% higher than the current one, depending on the evaluated scenario. Yield variation between seasons (seasonality) and years is expected to increase. The increase of dry matter accumulation will be higher in the rainy season than in the dry season, and this result is more evident for soils with low-water storage capacity. The results varied significantly between regions (<10% to >60%). Despite their higher climate potential, warmer regions will probably have a lower increase in future forage production.

Impact of elevated temperature scenarios on potato leaf development

The objective of this study was to simulate the impact of elevated temperature scenarios on leaf development of potato in Santa Maria, RS, Brazil. Leaf appearance was estimated using a multiplicative model that has a non-linear temperature response function which calculates the daily leaf appearance rate (LAR, leaves day-1) and the accumulated number of leaves (LN) from crop emergence to the appearance of the upper last leaf. Leaf appearance was estimated during 100 years in the following scenarios: current climate, +1 °C, +2 °C, +3 °C, +4 °C e +5 °C. The LAR model was estimated with coefficients of the Asterix cultivar in five emergence dates and in two growing seasons (Fall and Spring). Variable of interest was the duration (days) of the crop emergence to the appearance of the final leaf number (EM-FLN) phase. Statistical analysis was performed assuming a three-factorial experiment, with main effects being climate scenarios, growing seasons, and emergence dates in a completely randomized design using years (one hundred) as replications. The results showed that warmer scenarios lead to an increase, in the fall, and a decrease, in the spring growing season, in the duration of the leaf appearance phase, indicating high vulnerability and complexity of the response of potato crop grown in a Subtropical environment to climate change.

Spatialization of climate, physical and socioeconomic factors that affect the dairy goat production in Brazil and their impact on animal breeding decisions

Brazil has high climate, soil and environmental diversity, as well as distinct socioeconomic and political realities, what results in differences among the political administrative regions of the country. The objective of this study was to determine spatial distribution of the physical, climatic and socioeconomic aspects that best characterize the production of dairy goats in Brazil. Production indices of milk per goat, goat production, milk production, as well as temperature range, mean temperature, precipitation, normalized difference vegetation index, relative humidity, altitude, agricultural farms; farms with native pasture, farms with good quality pasture, farms with water resources, farms that receive technical guidance, family farming properties, non-familiar farms and the human development index were evaluated. The multivariate analyses were carried out to spatialize climatic, physical and socioeconomic variables and so differenciate the Brazilian States and Regions. The highest yields of milk and goat production were observed in the Northeast. The Southeast Region had the second highest production of milk, followed by the South, Midwest and North. Multivariate analysis revealed distinctions between clusters of political-administrative regions of Brazil. The climatic variables were most important to discriminate between regions of Brazil. Therefore, it is necessary to implement animal breeding programs to meet the needs of each region.