Benchmark map of forest carbon stocks in tropical regions across three continents.

Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ± 6% to ± 53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ± 5% and ca. ± 1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

Environmental and climatic impact on the infection and mortality of SARS-CoV-2 in Peru.

OBJECTIVES: The role of the environment and climate in the transmission and case fatality rates of SARS-CoV-2 is still being investigated a year into the pandemic. Elevation and air quality are believed to be significant factors in the development of the pandemic, but the influence of additional environmental factors remains unclear. METHODS: We explored the relationship between the cumulative number of infections and mortality cases with climate (temperature, precipitation, solar radiation, water vapor pressure, wind), environmental data (elevation, normalized difference vegetation index or NDVI, particulate matter at 2.5 µm or PM2.5 and NO2 concentration), and population density in Peru. We use confirmed cases of infection from 1,287 districts and mortality in 479 districts, we used Spearman's correlations to assess the bivariate correlation between environmental and climatic factors with cumulative infection cases, cumulative mortality and case-fatality rate. We explored district cases within the ecozones of coast, sierra, high montane forest and lowland rainforest. RESULTS: Multiple linear regression models indicate elevation, mean solar radiation, air quality, population density and green vegetation cover, as a socioeconomic proxy, are influential factors in the distribution of infection and mortality of SARS-CoV-2 in Peru. Case-fatality rate was weakly associated with elevation. CONCLUSIONS: Our results also strongly suggest that exposure to poor air quality is a significant factor in the mortality of individuals below the age of 30. We conclude that environmental and climatic factors do play a significant role in the transmission and case fatality rates in Peru, however further study is required to see if these relationships are maintained over time.

Prediciendo la distribución de Polylepis: bosques Andinos vulnerables y cada vez más importantes

Los bosques de Polylepis son recursos vitales para la conservación de la biodiversidad y funciones hidrológicas, la cual se verá alterada por el cambio climático a nivel mundial desafiando la sostenibilidad de las comunidades locales. Sin embargo, estos ecosistemas andinos de gran altitud son cada vez más vulnerables debido a la presión antropogénica como la fragmentación, deforestación y el incremento en el ganado. La importancia para predecir la distribución de bosques nativos ha aumentado para contrarrestar los efectos negativos del cambio climático a través de la conservación y la reforestación. El objetivo de este estudio fue desarrollar y analizar los modelos de distribución de dos especies, Polylepis sericea y P. besseri, que forman bosques extensos a lo largo de los Andes. Este estudio utilizó el programa Maxent, el clima y capas ambientales de una resolución de 1 Km. El modelo de distribución previsto para P. sericea indica que la especie podría estar situada en una variedad de hábitats a lo largo de la Cordillera de los Andes, mientras que P. besseri se limitaba a las grandes alturas del sur de Perú y Bolivia. Para ambas especies, los metros de elevación y la temperatura son los factores más importantes para la distribución prevista. El perfeccionamiento del modelo de Polylepis y otras especies andinas utilizando datos de satélites cada vez más disponibles al público demuestran el potencial para ayudar a definir las áreas de diversidad y mejorar las estrategias de conservación en los Andes.

Polylepis woodlands are a vital resource for preserving biodiversity and hydrological functions, which will be altered by climate change and challenge the sustainability of local human communities. However, these high-altitude Andean ecosystems are becoming increasingly vulnerable due to anthropogenic pressure including fragmentation, deforestation and the increase in livestock. Predicting the distribution of native woodlands has become increasingly important to counteract the negative effects of climate change through reforestation and conservation. The objective of this study was to develop and analyze the distribution models of two species that form extensive woodlands along the Andes, namely Polylepis sericea and P. weberbaueri. This study utilized the program Maxent, climate and remotely sensed environmental layers at 1 Km resolution. The predicted distribution model for P. sericea indicated that the species could be located in a variety of habitats along the Andean Cordillera, while P. weberbaueri was restricted to the high elevations of southern Peru and Bolivia. For both species, elevation and temperature metrics were the most significant factors for predicted distribution. Further model refinement of Polylepis and other Andean species using increasingly available satellite data demonstrate the potential to help define areas of diversity and improve conservation strategies for the Andes.