Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies.

Anthropogenic climate change is expected to impact ecosystem structure, biodiversity and ecosystem services in Africa profoundly. We used the adaptive Dynamic Global Vegetation Model (aDGVM), which was originally developed and tested for Africa, to quantify sources of uncertainties in simulated African potential natural vegetation towards the end of the 21st century. We forced the aDGVM with regionally downscaled high-resolution climate scenarios based on an ensemble of six general circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). Our study assessed the direct effects of climate change and elevated CO2 on vegetation change and its plant-physiological drivers. Total increase in carbon in aboveground biomass in Africa until the end of the century was between 18% to 43% (RCP4.5) and 37% to 61% (RCP8.5) and was associated with woody encroachment into grasslands and increased woody cover in savannas. When direct effects of CO2 on plants were omitted, woody encroachment was muted and carbon in aboveground vegetation changed between -8 to 11% (RCP 4.5) and -22 to -6% (RCP8.5). Simulated biome changes lacked consistent large-scale geographical patterns of change across scenarios. In Ethiopia and the Sahara/Sahel transition zone, the biome changes forecast by the aDGVM were consistent across GCMs and RCPs. Direct effects from elevated CO2 were associated with substantial increases in water use efficiency, primarily driven by photosynthesis enhancement, which may relieve soil moisture limitations to plant productivity. At the ecosystem level, interactions between fire and woody plant demography further promoted woody encroachment. We conclude that substantial future biome changes due to climate and CO2 changes are likely across Africa. Because of the large uncertainties in future projections, adaptation strategies must be highly flexible. Focused research on CO2 effects, and improved model representations of these effects will be necessary to reduce these uncertainties.

A new research strategy for integrating studies of paleoclimate, paleoenvironment, and paleoanthropology.

Paleoanthropologists (scientists studying human origins) universally recognize the evolutionary significance of ancient climates and environments for understanding human origins. Even those scientists working in recent phases of human evolution, when modern humans evolved, agree that hunter-gatherer adaptations are tied to the way that climate and environment shape the food and technological resource base. The result is a long tradition of paleoanthropologists engaging with climate and environmental scientists in an effort to understand if and how hominin bio-behavioral evolution responded to climate and environmental change. Despite this unusual consonance, the anticipated rewards of this synergy are unrealized and, in our opinion, will not reach potential until there are some fundamental changes in the way the research model is constructed. Discovering the relation between climate and environmental change to human origins must be grounded in a theoretical framework and a causal understanding of the connection between climate, environment, resource patterning, behavior, and morphology, then move beyond the strict correlative research that continues to dominate the field.

Test for Covid-19 seasonality and the risk of second waves.

Ten months into the Covid-19 pandemic it remains unclear whether transmission of SARS-CoV-2 is affected by climate factors. Using a dynamic epidemiological model with Covid-19 climate sensitivity in the likely range, we demonstrate why attempts to detect a climate signal in Covid-19 have thus far been inconclusive. Then we formulate a novel methodology based on susceptible-infected time trajectories that can be used to test for seasonal climate sensitivity in observed Covid-19 infection data. We show that if the disease does have a substantial seasonal dependence, and herd immunity is not established during the first peak season of the outbreak (or a vaccine does not become available), there is likely to be a seasonality-sensitive second wave of infections about one year after the initial outbreak. In regions where non-pharmaceutical control has contained the disease in the first year of outbreak and thus kept a large portion of the population susceptible, the second wave may be substantially larger in amplitude than the first if control measures are relaxed. This is simply because it develops under the favorable conditions of a full autumn to winter period and from a larger pool of infected individuals.

Winter Is Coming: A Southern Hemisphere Perspective of the Environmental Drivers of SARS-CoV-2 and the Potential Seasonality of COVID-19.

SARS-CoV-2 virus infections in humans were first reported in December 2019, the boreal winter. The resulting COVID-19 pandemic was declared by the WHO in March 2020. By July 2020, COVID-19 was present in 213 countries and territories, with over 12 million confirmed cases and over half a million attributed deaths. Knowledge of other viral respiratory diseases suggests that the transmission of SARS-CoV-2 could be modulated by seasonally varying environmental factors such as temperature and humidity. Many studies on the environmental sensitivity of COVID-19 are appearing online, and some have been published in peer-reviewed journals. Initially, these studies raised the hypothesis that climatic conditions would subdue the viral transmission rate in places entering the boreal summer, and that southern hemisphere countries would experience enhanced disease spread. For the latter, the COVID-19 peak would coincide with the peak of the influenza season, increasing misdiagnosis and placing an additional burden on health systems. In this review, we assess the evidence that environmental drivers are a significant factor in the trajectory of the COVID-19 pandemic, globally and regionally. We critically assessed 42 peer-reviewed and 80 preprint publications that met qualifying criteria. Since the disease has been prevalent for only half a year in the northern, and one-quarter of a year in the southern hemisphere, datasets capturing a full seasonal cycle in one locality are not yet available. Analyses based on space-for-time substitutions, i.e., using data from climatically distinct locations as a surrogate for seasonal progression, have been inconclusive. The reported studies present a strong northern bias. Socio-economic conditions peculiar to the 'Global South' have been omitted as confounding variables, thereby weakening evidence of environmental signals. We explore why research to date has failed to show convincing evidence for environmental modulation of COVID-19, and discuss directions for future research. We conclude that the evidence thus far suggests a weak modulation effect, currently overwhelmed by the scale and rate of the spread of COVID-19. Seasonally modulated transmission, if it exists, will be more evident in 2021 and subsequent years.

Regional Projections of Extreme Apparent Temperature Days in Africa and the Related Potential Risk to Human Health.

Regional climate modelling was used to produce high resolution climate projections for Africa, under a "business as usual scenario", that were translated into potential health impacts utilizing a heat index that relates apparent temperature to health impacts. The continent is projected to see increases in the number of days when health may be adversely affected by increasing maximum apparent temperatures (AT) due to climate change. Additionally, climate projections indicate that the increases in AT results in a moving of days from the less severe to the more severe Symptom Bands. The analysis of the rate of increasing temperatures assisted in identifying areas, such as the East African highlands, where health may be at increasing risk due to both large increases in the absolute number of hot days, and due to the high rate of increase. The projections described here can be used by health stakeholders in Africa to assist in the development of appropriate public health interventions to mitigate the potential health impacts from climate change.

Natural hazards in a changing world: a case for ecosystem-based management.

Communities worldwide are increasingly affected by natural hazards such as floods, droughts, wildfires and storm-waves. However, the causes of these increases remain underexplored, often attributed to climate changes or changes in the patterns of human exposure. This paper aims to quantify the effect of climate change, as well as land cover change, on a suite of natural hazards. Changes to four natural hazards (floods, droughts, wildfires and storm-waves) were investigated through scenario-based models using land cover and climate change drivers as inputs. Findings showed that human-induced land cover changes are likely to increase natural hazards, in some cases quite substantially. Of the drivers explored, the uncontrolled spread of invasive alien trees was estimated to halve the monthly flows experienced during extremely dry periods, and also to double fire intensities. Changes to plantation forestry management shifted the 1:100 year flood event to a 1:80 year return period in the most extreme scenario. Severe 1:100 year storm-waves were estimated to occur on an annual basis with only modest human-induced coastal hardening, predominantly from removal of coastal foredunes and infrastructure development. This study suggests that through appropriate land use management (e.g. clearing invasive alien trees, re-vegetating clear-felled forests, and restoring coastal foredunes), it would be possible to reduce the impacts of natural hazards to a large degree. It also highlights the value of intact and well-managed landscapes and their role in reducing the probabilities and impacts of extreme climate events.