Katia Fernandes

High-yield oil palm expansion spares land at the expense of forests in the Peruvian Amazon.

High-yield agriculture potentially reduces pressure on forests by requiring less land to increase production. Using satellite and field data, we assessed the area deforested by industrial-scale high-yield oil palm expansion in the Peruvian Amazon from 2000 to 2010, finding that 72% of new plantations expanded into forested areas. In a focus area in the Ucayali region, we assessed deforestation for high- and smallholder low-yield oil palm plantations. Low-yield plantations accounted for most expansion overall (80%), but only 30% of their expansion involved forest conversion, contrasting with 75% for high-yield expansion. High-yield expansion minimized the total area required to achieve production but counter-intuitively at higher expense to forests than low-yield plantations. The results show that high-yield agriculture is an important but insufficient strategy to reduce pressure on forests. We suggest that high-yield agriculture can be effective in sparing forests only if coupled with incentives for agricultural expansion into already cleared lands.

What controls the interannual variation of the wet season onsets over the Amazon

Previous studies have established that sea surface temperature anomalies (SSTAs) in the tropical Pacific and Atlantic are the main forcing of the interannual variation of the wet season onsets in the Amazon. However, this variation appears to be complex and not uniquely determined by SSTAs. What causes such a complexity and to what extent the interannual variation of the wet season onsets is predictable remain unclear. This study suggests that such a complex relationship is the result of several competing processes, which are nonlinearly related to the SSTAs. In particular, three dry season conditions are crucial for determining interannual variation of the wet season onset. (i) A poleward shift of the Southern Hemisphere subtropical jet (SHSJ) over the South American sector, initiated from a wave train-like structure possibly forced by south central Pacific SST patterns, can prevent cold frontal systems from moving northward into the Amazon. This delays cold air incursion and results in late wet season onset over the southern Amazon. (ii) An anomalous anticyclonic center, which enhances westerly wind at 850 hPa over the southern Amazon and also the South American low-level jets, leads to moisture export from the southern Amazon to La Plata basin and reduces convective systems that provide elevated diabatic heating. (iii) Smaller convective available potential energy (CAPE) limits local thermodynamically driven convection. Based on the stepwise and partial least squares regressions, these three selected preseasonal conditions (Nino 4, SHSJ, and CAPE) can explain 57% of the total variance of the wet season onset.

Depopulation of rural landscapes exacerbates fire activity in the western Amazon

Destructive fires in Amazonia have occurred in the past decade, leading to forest degradation, carbon emissions, impaired air quality, and property damage. Here, we couple climate, geospatial, and province-level census data, with farmer surveys to examine the climatic, demographic, and land use factors associated with fire frequency in the Peruvian Amazon from 2000 to 2010. Although our results corroborate previous findings elsewhere that drought and proximity to roads increase fire frequency, the province-scale analysis further identifies decreases in rural populations as an additional factor. Farmer survey data suggest that increased burn scar frequency and size reflect increased flammability of emptying rural landscapes and reduced capacity to control fire. With rural populations projected to decline, more frequent drought, and expansion of road infrastructure, fire risk is likely to increase in western Amazonia. Damage from fire can be reduced through warning systems that target high-risk locations, coordinated fire fighting efforts, and initiatives that provide options for people to remain in rural landscapes.

Decadal covariability of Atlantic SSTs and western Amazon dry-season hydroclimate in observations and CMIP5 simulations

The unusual severity and return time of the 2005 and 2010 dry-season droughts in western Amazon is attributed partly to decadal climate fluctuations and a modest drying trend. Decadal variability of western Amazon hydroclimate is highly correlated to the Atlantic sea surface temperature (SST) north-south gradient (NSG). Shifts of dry and wet events frequencies are also related to the NSG phase, with a 66% chance of 3+ years of dry events per decade when NSG > 0 and 19% when NSG < 0. The western Amazon and NSG decadal covariability is well reproduced in general circulation models (GCMs) historical (HIST) and preindustrial control (PIC) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). The HIST and PIC also reproduce the shifts in dry and wet events probabilities, indicating potential for decadal predictability based on GCMs. Persistence of the current NSG positive phase favors above normal frequency of western Amazon dry events in coming decades.

Two summers of São Paulo drought: Origins in the western tropical Pacific

Two years of drought in Southeast Brazil have led to water shortages in Sao Paulo, the countrys most populous city. We examine the observed drought during austral summers of 2013/2014 and 2014/2015 and the related large-scale dynamics. The 2013–2014 precipitation deficits were more concentrated in the state of Sao Paulo, while in 2014–2015 moderate deficits were seen throughout the region. We find that a persistent warm sea surface temperature (SST) anomaly in the western tropical Pacific Ocean was an important driver of drought via atmospheric teleconnection in the two December–February seasons. The warm SST and associated convective heating initiated a wave train across the South Pacific. The resulting anticyclonic geopotential height anomaly over the southwest Atlantic expanded the westward margin of the South Atlantic high and prevented low-pressure systems from entering southeast Brazil from midlatitudes. This mechanism suggests a hemispheric symmetry to that proposed for the recent California drought.

Land cover change interacts with drought severity to change fire regimes in Western Amazonia.

Fire is becoming a pervasive driver of environmental change in Amazonia and is expected to intensify, given projected reductions in precipitation and forest cover. Understanding of the influence of post-deforestation land cover change on fires in Amazonia is limited, even though fires in cleared lands constitute a threat for ecosystems, agriculture, and human health. We used MODIS satellite data to map burned areas annually between 2001 and 2010. We then combined these maps with land cover and climate information to understand the influence of land cover change in cleared lands and dry-season severity on fire occurrence and spread in a focus area in the Peruvian Amazon. Fire occurrence, quantified as the probability of burning of individual 232-m spatial resolution MODIS pixels, was modeled as a function of the area of land cover types within each pixel, drought severity, and distance to roads. Fire spread, quantified as the number of pixels burned in 3 × 3 pixel windows around each focal burned pixel, was modeled as a function of land cover configuration and area, dry-season severity, and distance to roads. We found that vegetation regrowth and oil palm expansion are significantly correlated with fire occurrence, but that the magnitude and sign of the correlation depend on drought severity, successional stage of regrowing vegetation, and oil palm age. Burning probability increased with the area of nondegraded pastures, fallow, and young oil palm and decreased with larger extents of degraded pastures, secondary forests, and adult oil palm plantations. Drought severity had the strongest influence on fire occurrence, overriding the effectiveness of secondary forests, but not of adult plantations, to reduce fire occurrence in severely dry years. Overall, irregular and scattered land cover patches reduced fire spread but irregular and dispersed fallows and secondary forests increased fire spread during dry years. Results underscore the importance of land cover management for reducing fire proliferation in this landscape. Incentives for promoting natural regeneration and perennial crops in cleared lands might help to reduce fire risk if those areas are protected against burning in early stages of development and during severely dry years.

Climate and environmental monitoring for decision making

As human populations grow, so do the resource demands imposed on ecosystems and the impacts of our global footprint. Natural resources are not invulnerable, nor infinitely available. The environmental impacts of anthropogenic actions are becoming more apparent – air and water quality are increasingly compromised, pests and diseases are extending beyond their historical boundaries, and deforestation is exacerbating flooding downstream and loss of biodiversity. Society is increasingly becoming aware that ecosystem services are not only limited, but also that they are threatened by human activities. The need to better consider long-term ecosystem health and its role in enabling human habitation and economic activity is urgent. In this context IRI conducts research to understand the impact of climate and environmental changes on different sectors including agriculture, water management, human health, and natural disasters. Through exhaustive, rigorous evaluation, analysis and interpretation of remotely-sensed products and in-situ measurements, IRI ensures its partners have access to the most reliable and relevant information about the climate and environment in a format that best informs their decision making and planning. We focus on monitoring satellite-derived and in-situ estimates of precipitation, temperature, vegetation, water bodies, evapotranspiration, and land cover. Ultimately, the new products developed at IRI in partnership with other institutions at national (e.g. NOAA, NASA, USGS) and international (e.g. National Meteorology Agencies, UN FAO) levels are integrated into operational early-warning systems for health, natural disasters, agriculture, and food security. The new products which monitor in almost real-time climate and environmental conditions are made available through two online data bases at IRI called IRI Data Library and Map Room. In this paper we present the products developed at IRI and how they are integrated into Early Warning Systems (EWS). We also discuss IRI’s experience in linking EWS into decisions and policies using the fire early warning system as a concrete example.

Climate change and sugarcane expansion increase Hantavirus infection risk

Hantavirus Cardiopulmonary Syndrome (HCPS) is a disease caused by Hantavirus, which is highly virulent for humans. High temperatures and conversion of native vegetation to agriculture, particularly sugarcane cultivation can alter abundance of rodent generalist species that serve as the principal reservoir host for HCPS, but our understanding of the compound effects of land use and climate on HCPS incidence remains limited, particularly in tropical regions. Here we rely on a Bayesian model to fill this research gap and to predict the effects of sugarcane expansion and expected changes in temperature on Hantavirus infection risk in the state of São Paulo, Brazil. The sugarcane expansion scenario was based on historical data between 2000 and 2010 combined with an agro-environment zoning guideline for the sugar and ethanol industry. Future evolution of temperature anomalies was derived using 32 general circulation models from scenarios RCP4.5 and RCP8.5 (Representative greenhouse gases Concentration Pathways adopted by IPCC). Currently, the state of São Paulo has an average Hantavirus risk of 1.3%, with 6% of the 645 municipalities of the state being classified as high risk (HCPS risk ≥ 5%). Our results indicate that sugarcane expansion alone will increase average HCPS risk to 1.5%, placing 20% more people at HCPS risk. Temperature anomalies alone increase HCPS risk even more (1.6% for RCP4.5 and 1.7%, for RCP8.5), and place 31% and 34% more people at risk. Combined sugarcane and temperature increases led to the same predictions as scenarios that only included temperature. Our results demonstrate that climate change effects are likely to be more severe than those from sugarcane expansion. Forecasting disease is critical for the timely and efficient planning of operational control programs that can address the expected effects of sugarcane expansion and climate change on HCPS infection risk. The predicted spatial location of HCPS infection risks obtained here can be used to prioritize management actions and develop educational campaigns.