Predicting the deforestation-trend under different carbon-prices

BACKGROUND: Global carbon stocks in forest biomass are decreasing by 1.1 Gt of carbon annually, owing to continued deforestation and forest degradation. Deforestation emissions are partly offset by forest expansion and increases in growing stock primarily in the extra-tropical north. Innovative financial mechanisms would be required to help reducing deforestation. Using a spatially explicit integrated biophysical and socio-economic land use model we estimated the impact of carbon price incentive schemes and payment modalities on deforestation. One payment modality is adding costs for carbon emission, the other is to pay incentives for keeping the forest carbon stock intact. RESULTS: Baseline scenario calculations show that close to 200 mil ha or around 5% of todays forest area will be lost between 2006 and 2025, resulting in a release of additional 17.5 GtC. Today's forest cover will shrink by around 500 million hectares, which is 1/8 of the current forest cover, within the next 100 years. The accumulated carbon release during the next 100 years amounts to 45 GtC, which is 15% of the total carbon stored in forests today. Incentives of 6 US$/tC for vulnerable standing biomass payed every 5 year will bring deforestation down by 50$/year. On the other hand a carbon tax of 12 $/tC harvested forest biomass will also cut deforestation by half. The tax income will, if enforced, decrease from 6 billion US$ in 2005 to 4.3 billion US$in 2025 and 0.7 billion US$ in 2100 due to decreasing deforestation speed. CONCLUSION: Avoiding deforestation requires financial mechanisms that make retention of forests economically competitive with the currently often preferred option to seek profits from other land uses. Incentive payments need to be at a very high level to be effective against deforestation. Taxes on the other hand will extract budgetary revenues from the regions which are already poor. A combination of incentives and taxes could turn out to be a viable solution for this problem. Increasing the value of forest land and thereby make it less easily prone to deforestation would act as a strong incentive to increase productivity of agricultural and fuelwood production, which could be supported by revenues generated by the deforestation tax

Global Health and Economic Impacts of Future Ozone Pollution

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).We assess the human health and economic impacts of projected 2000-2050 changes in ozone pollution using the MIT Emissions Prediction and Policy Analysis-Health Effects (EPPA-HE) model, in combination with results from the GEOS-Chem global tropospheric chemistry model that simulated climate and chemistry effects of IPCC SRES emissions. We use EPPA to assess the human health damages (including acute mortality and morbidity outcomes) caused by ozone pollution and quantify their economic impacts in sixteen world regions. We compare the costs of ozone pollution under scenarios with 2000 and 2050 ozone precursor and greenhouse gas emissions (SRES A1B scenario). We estimate that health costs due to global ozone pollution above pre-industrial levels by 2050 will be $580 billion (year 2000$) and that acute mortalities will exceed 2 million. We find that previous methodologies underestimate costs of air pollution by more than a third because they do not take into account the long-term, compounding effects of health costs. The economic effects of emissions changes far exceed the influence of climate alone.United States Department of Energy, Office of Science (BER) grants DE-FG02-94ER61937 and DE-FG02-93ER61677, the United States Environmental Protection Agency grant EPA-XA-83344601-0, and the industrial and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change

Invasion of freshwater ecosystems is promoted by network connectivity to hotspots of human activity

Aim: Hotspots of human activity are focal points for ecosystem disturbance and non‐native introduction, from which invading populations disperse and spread. As such, connectivity to locations used by humans may influence the likelihood of invasion. Moreover, connectivity in freshwater ecosystems may follow the hydrological network. Here we tested whether multiple forms of connectivity to human recreational activities promotes biological invasion of freshwater ecosystems. Location: England, UK. Time period: 1990–2018. Major taxa studied: One hundred and twenty‐six non‐native freshwater birds, crustaceans, fish, molluscs and plants. Methods: Machine learning was used to predict spatial gradients in human recreation and two high risk activities for invasion (fishing and water sports). Connectivity indices were developed for each activity, in which human influence decayed from activity hotspots according to Euclidean distance (spatial connectivity) or hydrological network distance (downstream, upstream and along‐channel connectivity). Generalized linear mixed models identified the connectivity type most associated to invasive species richness of each group, while controlling for other anthropogenic and environmental drivers. Results: Connectivity to humans generally had stronger positive effects on invasion than all other drivers except recording effort. Recreation had stronger influence than urban land cover, and for most groups high risk activities had stronger effects than general recreation. Downstream human connectivity was most important for invasion by most of the groups, potentially reflecting predominantly hydrological dispersal. An exception was birds, for which spatial connectivity was most important, possibly because of overland dispersal capacity. Main conclusions: These findings support the hypothesis that freshwater invasion is partly determined by an interaction between human activity and species dispersal in the hydrological network. By comparing alternative connectivity types for different human activities, our approach could enable robust inference of specific pathways and spread mechanisms associated with particular taxa. This would provide evidence to support better prioritization of surveillance and management for invasive non‐native species

Active Amplification of the Terrestrial Albedo to Mitigate Climate Change: An Exploratory Study

This study explores the potential to enhance the reflectance of solar insolation by the human settlement and grassland components of the Earth's terrestrial surface as a climate change mitigation measure. Preliminary estimates derived using a static radiative transfer model indicate that such efforts could amplify the planetary albedo enough to offset the current global annual average level of radiative forcing caused by anthropogenic greenhouse gases by as much as 30 percent or 0.76 W/m2. Terrestrial albedo amplification may thus extend, by about 25 years, the time available to advance the development and use of low-emission energy conversion technologies which ultimately remain essential to mitigate long-term climate change. However, additional study is needed to confirm the estimates reported here and to assess the economic and environmental impacts of active land-surface albedo amplification as a climate change mitigation measure.Comment: 21 pages, 3 figures. In press with Mitigation and Adaptation Strategies for Global Change, Springer, N

Global and regional trends in particulate air pollution and attributable health burden over the past 50 years

Long-term exposure to ambient particulate matter (PM2.5, mass of particles with an aerodynamic dry diameter of < 2.5 μm) is a major risk factor to the global burden of disease. Previous studies have focussed on present day or future health burdens attributed to ambient PM2.5. Few studies have estimated changes in PM2.5 and attributable health burdens over the last few decades, a period where air quality has changed rapidly. Here we used the HadGEM3-UKCA coupled chemistry-climate model, integrated exposure-response relationships, demographic and background disease data to provide the first estimate of the changes in global and regional ambient PM2.5 concentrations and attributable health burdens over the period 1960 to 2009. Over this period, global mean population-weighted PM2.5 concentrations increased by 38%, dominated by increases in China and India. Global attributable deaths increased by 89% to 124% over the period 1960 to 2009, dominated by large increases in China and India. Population growth and ageing contributed mostly to the increases in attributable deaths in China and India, highlighting the importance of demographic trends. In contrast, decreasing PM2.5 concentrations and background disease dominated the reduction in attributable health burden in Europe and the United States. Our results shed light on how future projected trends in demographics and uncertainty in the exposure–response relationship may provide challenges for future air quality policy in Asia

A gap analysis modelling framework to prioritize collecting for ex situ conservation of crop landraces

Aim: The conservation and effective use of crop genetic diversity are crucial to over-come challenges related to human nutrition and agricultural sustainability. Farmers’ traditional varieties (“landraces”) are major sources of genetic variation. The degree of representation of crop landrace diversity in ex situ conservation is poorly under-stood, partly due to a lack of methods that can negotiate both the anthropogenic and environmental determinants of their geographic distributions. Here, we describe a novel spatial modelling and ex situ conservation gap analysis modelling framework for crop landraces, using common bean (Phaseolus vulgaris L.) as a case study.Location: The Americas.Methods: The modelling framework includes five main steps: (a) determining relevant landrace groups using literature to develop and test classification models; (b) model-ling the potential geographic distributions of these groups using occurrence (landrace presences) combined with environmental and socioeconomic predictor data; (c) cal-culating geographic and environmental gap scores for current genebank collections; (d) mapping ex situ conservation gaps; and (e) compiling expert inputs.Results: Modelled distributions and conservation gaps for the two genepools of com-mon bean (Andean and Mesoamerican) were robustly predicted and align well with expert opinions. Both genepools are relatively well conserved, with Andean ex situ collections representing 78.5% and Mesoamerican 98.2% of their predicted geo-graphic distributions. Modelling revealed additional collection priorities for Andean landraces occur primarily in Chile, Peru, Colombia and, to a lesser extent, Venezuela. Mesoamerican landrace collecting priorities are concentrated in Mexico, Belize and Guatemala.Conclusions: The modelling framework represents an advance in tools that can be deployed to model the geographic distributions of cultivated crop diversity, to as-sess the comprehensiveness of conservation of this diversity ex situ and to highlight geographic areas where further collecting may be conducted to fill gaps in ex situ conservation

Seasonal cycles enhance disparities between low- and high-income countries in exposure to monthly temperature emergence with future warming

A common proxy for the adaptive capacity of a community to the impacts of future climate change is the range of climate variability which they have experienced in the recent past. This study presents an interpretation of such a framework for monthly temperatures. Our results demonstrate that emergence into genuinely 'unfamiliar' climates will occur across nearly all months of the year for low-income nations by the second half of the 21st century under an RCP8.5 warming scenario. However, high income countries commonly experience a large seasonal cycle, owing to their position in the middle latitudes: as a consequence, temperature emergence for transitional months translates only to more-frequent occurrences of heat historically associated with the summertime. Projections beyond 2050 also show low-income countries will experience 2–10 months per year warmer than the hottest month experienced in recent memory, while high-income countries will witness between 1–4 months per year hotter than any month previously experienced. While both results represent significant departures that may bring substantive societal impacts if greenhouse gas emissions continue unabated, they also demonstrate that spatial patterns of emergence will compound existing differences between high and low income populations, in terms of their capacity to adapt to unprecedented future temperatures

Assessing Africa-wide pangolin exploitation by scaling local data

Overexploitation is one of the main pressures driving wildlife closer to extinction, yet broad-scale data to evaluate species’ declines are limited. Using African pangolins (Family: Pholidota) as a case study, we demonstrate that collating local-scale data can provide crucial information on regional trends in exploitation of threatened species to inform conservation actions and policy. We estimate that 0.4-2.7 million pangolins are hunted annually in Central African forests. The number of pangolins hunted has increased by ∼150% and the proportion of pangolins of all vertebrates hunted increased from 0.04% to 1.83% over the past four decades. However, there were no trends in pangolins observed at markets, suggesting use of alternative supply chains. The price of giant (Smutsia gigantea) and arboreal (Phataginus sp.) pangolins in urban markets has increased 5.8 and 2.3 times respectively, mirroring trends in Asian pangolins. Efforts and resources are needed to increase law enforcement and population monitoring, and investigate linkages between subsistence hunting and illegal wildlife trade

Thresholds of fire response to moisture and fuel load differ between tropical savannas and grasslands across continents

Aim An emerging framework for tropical ecosystems states that fire activity is either “fuel build‐up limited” or “fuel moisture limited”, that is, as you move up along rainfall gradients, the major control on fire occurrence switches from being the amount of fuel, to the moisture content of the fuel. Here we used remotely sensed datasets to assess whether interannual variability of burned area is better explained by annual rainfall totals driving fuel build‐up, or by dry season rainfall driving fuel moisture. Location Pantropical savannas and grasslands. Time period 2002–2016. Methods We explored the response of annual burned area to interannual variability in rainfall. We compared several linear models to understand how fuel moisture and fuel build‐up effect (accumulated rainfall during 6 and 24 months prior to the end of the burning season, respectively) determine the interannual variability of burned area and explore if tree cover, dry season duration and human activity modified these relationships. Results Fuel and moisture controls on fire occurrence in tropical savannas varied across continents. Only 24% of South American savannas were fuel build‐up limited against 61% of Australian savannas and 47% of African savannas. On average, South America switched from fuel limited to moisture limited at 500 mm/year, Africa at 800 mm/year and Australia at 1,000 mm/year of mean annual rainfall. Main conclusions In 42% of tropical savannas (accounting for 41% of current area burned) increased drought and higher temperatures will not increase fire, but there are savannas, particularly in South America, that are likely to become more flammable with increasing temperatures. These findings highlight that we cannot transfer knowledge of fire responses to global change across ecosystems/regions—local solutions to local fire management issues are required, and different tropical savanna regions may show contrasting responses to the same drivers of global change

Environmental-mechanistic modelling of the impact of global change on human zoonotic disease emergence: A case study of Lassa fever

1. Human infectious diseases are a significant threat to global human health and economies (e.g., Ebola, SARs), with the majority of infectious diseases having an animal source (zoonotic). Despite their importance, the lack of a quantitative predictive framework hampers our understanding of how spill-overs of zoonotic infectious diseases into the human population will be impacted by global environmental stressors. 2. Here, we create an environmental-mechanistic model for understanding the impact of global change on the probability of zoonotic disease reservoir host-human spill-over events. As a case study, we focus on Lassa fever virus (LAS). We firstly quantify the spatial determinants of LAS outbreaks, including the phylogeographic distribution of its reservoir host Natal multimammate rat (Mastomys natalensis) (LAS host). Secondly, we use these determinants to inform our environmental-mechanistic model to estimate present day LAS spill-over events and the predicted impact of climate change, human population growth, and land use by 2070. 3. We find phylogeographic evidence to suggest that LAS is confined to only one clade of LAS host (Western clade Mastomys natalensis), and that the probability of its occurrence was a major determinant of the spatial variation in LAS historical outbreaks (69.8%), along with human population density (20.4%). Our estimates for present day LAS spill-over events from our environmental-mechanistic model were consistent with observed patterns, and we predict an increase in events per year by 2070 from 195,125 to 406,725 within the LAS endemic western African region. Of the component drivers, climate change and human population growth are predicted to have the largest effects by increasing landscape suitability for the host and human-host contact rates, while land use change has only a weak impact on the number of future events. 4. LAS spill-over events did not respond uniformly to global environmental stressors, and we suggest that understanding the impact of global change on zoonotic infectious disease emergence requires an understanding of how reservoir host species respond to environmental change. Our environmental-mechanistic modelling methodology provides a novel generalizable framework to understand the impact of global change on the spill-over of zoonotic diseases