The phenomenon of thunderstorm asthma in Bavaria, Southern Germany: a statistical approach

Higher incidences of asthma during thunderstorms can pose a serious health risk. In this study, we estimate the thunderstorm asthma risk using statistical methods, with special focus on Bavaria, Southern Germany. In this approach, a dataset of asthma-related emergency cases for the study region is combined with meteorological variables and aeroallergen data to identify statistical relationships between the occurrence of asthma (predictand) and different environmental parameters (set of predictors). On the one hand, the results provide evidence for a weak but significant relationship between atmospheric stability indices and asthma emergencies in the region, but also show that currently thunderstorm asthma is not a major concern in Bavaria due to overall low incidences. As thunderstorm asthma can have severe consequences for allergic patients, the presented approach can be important for the development of emergency strategies in regions affected by thunderstorm asthma and under present and future climate change conditions.

Genomic vulnerability and socio-economic threats under climate change in an African rainforest bird

Preserving biodiversity under rapidly changing climate conditions is challenging. One approach for estimating impacts and their magnitude is to model current relationships between genomic and environmental data and then to forecast those relationships under future climate scenarios. In this way, understanding future genomic and environmental relationships can help guide management decisions, such as where to establish new protected areas where populations might be buffered from high temperatures or major changes in rainfall. However, climate warming is only one of many anthropogenic threats one must consider in rapidly developing parts of the world. In Central Africa, deforestation, mining, and infrastructure development are accelerating population declines of rainforest species. Here we investigate multiple anthropogenic threats in a Central African rainforest songbird, the little greenbul (Andropadus virens). We examine current climate and genomic variation in order to explore the association between genome and environment under future climate conditions. Specifically, we estimate Genomic Vulnerability, defined as the mismatch between current and predicted future genomic variation based on genotype-environment relationships modeled across contemporary populations. We do so while considering other anthropogenic impacts. We find that coastal and central Cameroon populations will require the greatest shifts in adaptive genomic variation, because both climate and land use in these areas are predicted to change dramatically. In contrast, in the more northern forest-savanna ecotones, genomic shifts required to keep pace with climate will be more moderate, and other anthropogenic impacts are expected to be comparatively low in magnitude. While an analysis of diverse taxa will be necessary for making comprehensive conservation decisions, the species-specific results presented illustrate how evolutionary genomics and other anthropogenic threats may be mapped and used to inform mitigation efforts. To this end, we present an integrated conceptual model demonstrating how the approach for a single species can be expanded to many taxonomically diverse species.

Seasonal biological carryover dominates northern vegetation growth

The state of ecosystems is influenced strongly by their past, and describing this carryover effect is important to accurately forecast their future behaviors. However, the strength and persistence of this carryover effect on ecosystem dynamics in comparison to that of simultaneous environmental drivers are still poorly understood. Here, we show that vegetation growth carryover (VGC), defined as the effect of present states of vegetation on subsequent growth, exerts strong positive impacts on seasonal vegetation growth over the Northern Hemisphere. In particular, this VGC of early growing-season vegetation growth is even stronger than past and co-occurring climate on determining peak-to-late season vegetation growth, and is the primary contributor to the recently observed annual greening trend. The effect of seasonal VGC persists into the subsequent year but not further. Current process-based ecosystem models greatly underestimate the VGC effect, and may therefore underestimate the CO2 sequestration potential of northern vegetation under future warming.

Climate-Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation-based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS-LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture-atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long-term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP.

Causes of slowing-down seasonal CO2 amplitude at Mauna Loa

Changing amplitude of the seasonal cycle of atmospheric CO₂ (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO₂ record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing-down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing-down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing-down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO₂ fertilization. This challenges the view that CO₂ fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land-atmosphere CO₂ flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.

Summer soil drying exacerbated by earlier spring greening of northern vegetation

Earlier vegetation greening under climate change raises evapotranspiration and thus lowers spring soil moisture, yet the extent and magnitude of this water deficit persistence into the following summer remain elusive. We provide observational evidence that increased foliage cover over the Northern Hemisphere, during 1982-2011, triggers an additional soil moisture deficit that is further carried over into summer. Climate model simulations independently support this and attribute the driving process to be larger increases in evapotranspiration than in precipitation. This extra soil drying is projected to amplify the frequency and intensity of summer heatwaves. Most feedbacks operate locally, except for a notable teleconnection where extra moisture transpired over Europe is transported to central Siberia. Model results illustrate that this teleconnection offsets Siberian soil moisture losses from local spring greening. Our results highlight that climate change adaptation planning must account for the extra summer water and heatwave stress inherited from warming-induced earlier greening.

Have Synergies Between Nitrogen Deposition and Atmospheric CO2 Driven the Recent Enhancement of the Terrestrial Carbon Sink?

The terrestrial carbon sink has increased since the turn of this century at a time of increased fossil fuel burning, yet the mechanisms enhancing this sink are not fully understood. Here we assess the hypothesis that regional increases in nitrogen deposition since the early 2000s has alleviated nitrogen limitation and worked in tandem with enhanced CO2 fertilization to increase ecosystem productivity and carbon sequestration, providing a causal link between the parallel increases in emissions and the global land carbon sink. We use the Community Land Model (CLM4.5-BGC) to estimate the influence of changes in atmospheric CO2, nitrogen deposition, climate, and their interactions to changes in net primary production and net biome production. We focus on two periods, 1901-2016 and 1990-2016, to estimate changes in land carbon fluxes relative to historical and contemporary baselines, respectively. We find that over the historical period, nitrogen deposition (14%) and carbon-nitrogen synergy (14%) were significant contributors to the current terrestrial carbon sink, suggesting that long-term increases in nitrogen deposition led to a substantial increase in CO2 fertilization. However, relative to the contemporary baseline, changes in nitrogen deposition and carbon-nitrogen synergy had no substantial contribution to the 21st century increase in global carbon uptake. Nonetheless, we find that increased nitrogen deposition in East Asia since the early 1990s contributed 50% to the overall increase in net biome production over this region, highlighting the importance of carbon-nitrogen interactions. Therefore, potential large-scale changes in nitrogen deposition could have a significant impact on terrestrial carbon cycling and future climate.

Tropical land carbon cycle responses to 2015/16 El Niño as recorded by atmospheric greenhouse gas and remote sensing data

The outstanding tropical land climate characteristic over the past decades is rapid warming, with no significant large-scale precipitation trends. This warming is expected to continue but the effects on tropical vegetation are unknown. El Niño-related heat peaks may provide a test bed for a future hotter world. Here we analyse tropical land carbon cycle responses to the 2015/16 El Niño heat and drought anomalies using an atmospheric transport inversion. Based on the global atmospheric CO₂ and fossil fuel emission records, we find no obvious signs of anomalously large carbon release compared with earlier El Niño events, suggesting resilience of tropical vegetation. We find roughly equal net carbon release anomalies from Amazonia and tropical Africa, approximately 0.5 PgC each, and smaller carbon release anomalies from tropical East Asia and southern Africa. Atmospheric CO anomalies reveal substantial fire carbon release from tropical East Asia peaking in October 2015 while fires contribute only a minor amount to the Amazonian carbon flux anomaly. Anomalously large Amazonian carbon flux release is consistent with downregulation of primary productivity during peak negative near-surface water anomaly (October 2015 to March 2016) as diagnosed by solar-induced fluorescence. Finally, we find an unexpected anomalous positive flux to the atmosphere from tropical Africa early in 2016, coincident with substantial CO release.

This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Response to Comment on "Genomic signals of selection predict climate-driven population declines in a migratory bird"

Fitzpatrick et al discuss issues that they had with analyses and interpretation in our recent manuscript on genomic correlates of climate in yellow warblers. We provide evidence that our findings would not change with different analysis and maintain that our study represents a promising direction for integrating the potential for climate adaptation as one of many tools in conservation management.

Small global effect on terrestrial net primary production due to increased fossil fuel aerosol emissions from East Asia since the turn of the century

The global terrestrial carbon sink has increased since the start of this century at a time of growing carbon emissions from fossil fuel burning. Here we test the hypothesis that increases in atmospheric aerosols from fossil fuel burning enhanced the diffuse light fraction and the efficiency of plant carbon uptake. Using a combination of models, we estimate that at global scale changes in light regimes from fossil fuel aerosol emissions had only a small negative effect on the increase in terrestrial net primary production over the period 1998-2010. Hereby, the substantial increases in fossil fuel aerosol emissions and plant carbon uptake over East Asia were effectively canceled by opposing trends across Europe and North America. This suggests that if the recent increase in the land carbon sink would be causally linked to fossil fuel emissions, it is unlikely via the effect of aerosols but due to other factors such as nitrogen deposition or nitrogen-carbon interactions.

Mapping evolutionary process: a multi-taxa approach to conservation prioritization

Human-induced land use changes are causing extensive habitat fragmentation. As a result, many species are not able to shift their ranges in response to climate change and will likely need to adapt in situ to changing climate conditions. Consequently, a prudent strategy to maintain the ability of populations to adapt is to focus conservation efforts on areas where levels of intraspecific variation are high. By doing so, the potential for an evolutionary response to environmental change is maximized. Here, we use modeling approaches in conjunction with environmental variables to model species distributions and patterns of genetic and morphological variation in seven Ecuadorian amphibian, bird, and mammal species. We then used reserve selection software to prioritize areas for conservation based on intraspecific variation or species-level diversity. Reserves selected using species richness and complementarity showed little overlap with those based on genetic and morphological variation. Priority areas for intraspecific variation were mainly located along the slopes of the Andes and were largely concordant among species, but were not well represented in existing reserves. Our results imply that in order to maximize representation of intraspecific variation in reserves, genetic and morphological variation should be included in conservation prioritization.

Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment

Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg ) series, and its recent successor version 3g (GIMMS3g ), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg ), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg , particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas.

Spatial conservation planning framework for assessing conservation opportunities in the Atlantic Forest of Brazil

Historic rates of habitat change and growing exploitation of natural resources threaten avian biodiversity in the Brazilian Atlantic Forest, a global biodiversity hotspot. We implemented a twostage framework for conservation planning in the Atlantic Forest. First, we used ecological niche modeling to predict the distributions of 23 endemic bird species using 19 climatic metrics and 12 spectral and radar remote sensing metrics. Second, we utilized the principle of complementarity to prioritize new sites to augment the Atlantic Forest's existing reserves. The best predictors of bird distributions were precipitation metrics (the seasonality of rainfall) and radar remote sensing metrics (QSCAT). The existing protected areas do not include 10% of the habitat of each of the 23 endemic species. We propose a more economical set of protected areas by reducing the extent to which new sites duplicate the biodiversity content of existing protected areas. There is a high concordance between the proposed conservation areas that we designed using computerized algorithms and Important Bird Areas prioritized by BirdLife International. Insofar as deforestation in the Atlantic Forest is similar to land conversion in other biodiversity hotspots, our methodology is applicable to conservation efforts elsewhere in the world.

A continental risk assessment of West Nile virus under climate change

Since first introduced to North America in 1999, West Nile virus (WNV) has spread rapidly across the continent, threatening wildlife populations and posing serious health risks to humans. While WNV incidence has been linked to environmental factors, particularly temperature and rainfall, little is known about how future climate change may affect the spread of the disease. Using available data on WNV infections in vectors and hosts collected from 2003-2011 and using a suite of 10 species distribution models, weighted according to their predictive performance, we modeled the incidence of WNV under current climate conditions at a continental scale. Models were found to accurately predict spatial patterns of WNV that were then used to examine how future climate may affect the spread of the disease. Predictions were accurate for cases of human WNV infection in the following year (2012), with areas reporting infections having significantly higher probability of presence as predicted by our models. Projected geographic distributions of WNV in North America under future climate for 2050 and 2080 show an expansion of suitable climate for the disease, driven by warmer temperatures and lower annual precipitation that will result in the exposure of new and naïve host populations to the virus with potentially serious consequences. Our risk assessment identifies current and future hotspots of West Nile virus where mitigation efforts should be focused and presents an important new approach for monitoring vector-borne disease under climate change.

Regional differences in seasonal timing of rainfall discriminate between genetically distinct East African giraffe taxa

Masai (Giraffa tippelskirchi), Reticulated (G. reticulata) and Rothschild's (G. camelopardalis) giraffe lineages in East Africa are morphologically and genetically distinct, yet in Kenya their ranges abut. This raises the question of how divergence is maintained among populations of a large mammal capable of long-distance travel, and which readily hybridize in zoos. Here we test four hypotheses concerning the maintenance of the phylogeographic boundaries among the three taxa: 1) isolation-by-distance; 2) physical barriers to dispersal; 3) general habitat differences resulting in habitat segregation; or 4) regional differences in the seasonal timing of rainfall, and resultant timing of browse availability. We used satellite remotely sensed and climate data to characterize the environment at the locations of genotyped giraffes. Canonical variate analysis, random forest algorithms, and generalized dissimilarity modelling were employed in a landscape genetics framework to identify the predictor variables that best explained giraffes' genetic divergence. We found that regional differences in the timing of precipitation, and resulting green-up associated with the abundance of browse, effectively discriminate between taxa. Local habitat conditions, topographic and human-induced barriers, and geographic distance did not aid in discriminating among lineages. Our results suggest that selection associated with regional timing of events in the annual climatic cycle may help maintain genetic and phenotypic divergence in giraffes. We discuss potential mechanisms of maintaining divergence, and suggest that synchronization of reproduction with seasonal rainfall cycles that are geographically distinct may contribute to reproductive isolation. Coordination of weaning with green-up cycles could minimize the costs of lactation and predation on the young. Our findings are consistent with theory and empirical results demonstrating the efficacy of seasonal or phenologically dictated selection pressures in contributing to the reproductive isolation of parapatric populations.

Pathogen-host associations and predicted range shifts of human monkeypox in response to climate change in central Africa

Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4(th) Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts.

Intraspecific morphological and genetic variation of common species predicts ranges of threatened ones

Predicting where threatened species occur is useful for making informed conservation decisions. However, because they are usually rare, surveying threatened species is often expensive and time intensive. Here, we show how regions where common species exhibit high genetic and morphological divergence among populations can be used to predict the occurrence of species of conservation concern. Intraspecific variation of common species of birds, bats and frogs from Ecuador were found to be a significantly better predictor for the occurrence of threatened species than suites of environmental variables or the occurrence of amphibians and birds. Fully 93 per cent of the threatened species analysed had their range adequately represented by the geographical distribution of the morphological and genetic variation found in seven common species. Both higher numbers of threatened species and greater genetic and morphological variation of common species occurred along elevation gradients. Higher levels of intraspecific divergence may be the result of disruptive selection and/or introgression along gradients. We suggest that collecting data on genetic and morphological variation in common species can be a cost effective tool for conservation planning, and that future biodiversity inventories include surveying genetic and morphological data of common species whenever feasible.

Predicting bird song from space

Environmentally imposed selection pressures are well known to shape animal signals. Changes in these signals can result in recognition mismatches between individuals living in different habitats, leading to reproductive divergence and speciation. For example, numerous studies have shown that differences in avian song may be a potent prezygotic isolating mechanism. Typically, however, detailed studies of environmental pressures on variation in animal behavior have been conducted only at small spatial scales. Here, we use remote-sensing data to predict animal behavior, in this case, bird song, across vast spatial scales. We use remotely sensed data to predict the song characteristics of the little greenbul (Andropadus virens), a widely distributed African passerine, found across secondary and mature rainforest habitats and the rainforest-savanna ecotone. Satellite data that captured ecosystem structure and function explained up to 66% of the variation in song characteristics. Song differences observed across habitats, including those between human-altered and mature rainforest, have the potential to lead to reproductive divergence, and highlight the impacts that both natural and anthropogenic change may have on natural populations. Our approach offers a novel means to examine the ecological correlates of animal behavior across large geographic areas with potential applications to both evolutionary and conservation biology.

A preliminary assessment of the effectiveness of the Mesoamerican Biological Corridor for protecting potential Baird's tapir (Tapirus bairdii) habitat in Southern Mexico

Baird's tapir (Tapirus bairdii) is one of the most emblematic mammals of Mesoamerica, but like other large-bodied animals, it is facing an increasing risk of extinction due primarily to habitat loss. Mexico's 'ortion of the Mesoamerican Biological Corridor (MBC-M) is located in one of the main strongholds for Bairds tapir. To assess the MBC-M's effectiveness for tapir conservation, we estimated the distribution of the species' potential habitat by applying 2 modelling approaches (random forest and Maxent) to a set of uncorrelated environmental variables and a 157-point presence dataset. We calculated the extent of tapir habitat in within the MBC-M and modelled new corridors and conservation areas, which we compared to the MBC-M. Moreover, we assessed deforestation patterns in the region. Twenty-seven percent of highly suitable tapir habitat occurred in protected areas, 15% in corridors and 58.3% was outside the MBC-M and associated reserves. The spatial configuration of the MBC-M was partially concordant with the modelled set of conservation areas and corridors. The main dissimilarity was that the modelled corridors traversed forests in Belize and Guatemala to connect conservation areas. Analyses of deforestation since 1993 and human population density in the vicinity of the MBC-M indicated that future conservation efforts should give particular attention to the Montes Azules-El Triunfo Corridor due to greater habitat threat. The MBC-M has a great potential to play a prominent role in the conservation of tapir habitat but there is an urgent need to implement management plans that reinforce and complement this conservation initiative.

Using remote sensing to map the risk of human monkeypox virus in the Congo Basin

Although the incidence of human monkeypox has greatly increased in Central Africa over the last decade, resources for surveillance remain extremely limited. We conducted a geospatial analysis using existing data to better inform future surveillance efforts. Using active surveillance data collected between 2005 and 2007, we identified locations in Sankuru district, Democratic Republic of Congo (DRC) where there have been one or more cases of human monkeypox. To assess what taxa constitute the main reservoirs of monkeypox, we tested whether human cases were associated with (i) rope squirrels (Funisciurus sp.), which were implicated in monkeypox outbreaks elsewhere in the DRC in the 1980s, or (ii) terrestrial rodents in the genera Cricetomys and Graphiurus, which are believed to be monkeypox reservoirs in West Africa. Results suggest that the best predictors of human monkeypox cases are proximity to dense forests and associated habitat preferred by rope squirrels. The risk of contracting monkeypox is significantly greater near sites predicted to be habitable for squirrels (OR = 1.32; 95% CI 1.08-1.63). We recommend that semi-deciduous rainforests with oil-palm, the rope squirrel's main food source, be prioritized for monitoring.

Economic conditions predict prevalence of West Nile virus

Understanding the conditions underlying the proliferation of infectious diseases is crucial for mitigating future outbreaks. Since its arrival in North America in 1999, West Nile virus (WNV) has led to population-wide declines of bird species, morbidity and mortality of humans, and expenditures of millions of dollars on treatment and control. To understand the environmental conditions that best explain and predict WNV prevalence, we employed recently developed spatial modeling techniques in a recognized WNV hotspot, Orange County, California. Our models explained 85–95% of the variation of WNV prevalence in mosquito vectors, and WNV presence in secondary human hosts. Prevalence in both vectors and humans was best explained by economic variables, specifically per capita income, and by anthropogenic characteristics of the environment, particularly human population and neglected swimming pool density. While previous studies have shown associations between anthropogenic change and pathogen presence, results show that poorer economic conditions may act as a direct surrogate for environmental characteristics related to WNV prevalence. Low-income areas may be associated with higher prevalence for a number of reasons, including variations in property upkeep, microhabitat conditions conducive to viral amplification in both vectors and hosts, host community composition, and human behavioral responses related to differences in education or political participation. Results emphasize the importance and utility of including economic variables in mapping spatial risk assessments of disease.

Human impacts flatten rainforest-savanna gradient and reduce adaptive diversity in a rainforest bird

Ecological gradients have long been recognized as important regions for diversification and speciation. However, little attention has been paid to the evolutionary consequences or conservation implications of human activities that fundamentally change the environmental features of such gradients. Here we show that recent deforestation in West Africa has homogenized the rainforest-savanna gradient, causing a loss of adaptive phenotypic diversity in a common rainforest bird, the little greenbul (Andropadus virens). Previously, this species was shown to exhibit morphological and song divergence along this gradient in Central Africa. Using satellite-based estimates of forest cover, recent morphological data, and historical data from museum specimens collected prior to widespread deforestation, we show that the gradient has become shallower in West Africa and that A. virens populations there have lost morphological variation in traits important to fitness. In contrast, we find no loss of morphological variation in Central Africa where there has been less deforestation and gradients have remained more intact. While rainforest deforestation is a leading cause of species extinction, the potential of deforestation to flatten gradients and inhibit rainforest diversification has not been previously recognized. More deforestation will likely lead to further flattening of the gradient and loss of diversity, and may limit the ability of species to persist under future environmental conditions.

Spatially explicit predictions of blood parasites in a widely distributed African rainforest bird

Critical to the mitigation of parasitic vector-borne diseases is the development of accurate spatial predictions that integrate environmental conditions conducive to pathogen proliferation. Species of Plasmodium and Trypanosoma readily infect humans, and are also common in birds. Here, we develop predictive spatial models for the prevalence of these blood parasites in the olive sunbird (Cyanomitra olivacea). Since this species exhibits high natural parasite prevalence and occupies diverse habitats in tropical Africa, it represents a distinctive ecological model system for studying vector-borne pathogens. We used PCR and microscopy to screen for haematozoa from 28 sites in Central and West Africa. Species distribution models were constructed to associate ground-based and remotely sensed environmental variables with parasite presence. We then used machine-learning algorithm models to identify relationships between parasite prevalence and environmental predictors. Finally, predictive maps were generated by projecting model outputs to geographically unsampled areas. Results indicate that for Plasmodium spp., the maximum temperature of the warmest month was most important in predicting prevalence. For Trypanosoma spp., seasonal canopy moisture variability was the most important predictor. The models presented here visualize gradients of disease prevalence, identify pathogen hotspots and will be instrumental in studying the effects of ecological change on these and other pathogens.

Mapping the risk of avian influenza in wild birds in the US

BACKGROUND

Avian influenza virus (AIV) is an important public health issue because pandemic influenza viruses in people have contained genes from viruses that infect birds. The H5 and H7 AIV subtypes have periodically mutated from low pathogenicity to high pathogenicity form. Analysis of the geographic distribution of AIV can identify areas where reassortment events might occur and how high pathogenicity influenza might travel if it enters wild bird populations in the US. Modelling the number of AIV cases is important because the rate of co-infection with multiple AIV subtypes increases with the number of cases and co-infection is the source of reassortment events that give rise to new strains of influenza, which occurred before the 1968 pandemic. Aquatic birds in the orders Anseriformes and Charadriiformes have been recognized as reservoirs of AIV since the 1970s. However, little is known about influenza prevalence in terrestrial birds in the order Passeriformes. Since passerines share the same habitat as poultry, they may be more effective transmitters of the disease to humans than aquatic birds. We analyze 152 passerine species including the American Robin (Turdus migratorius) and Swainson's Thrush (Catharus ustulatus).

METHODS

We formulate a regression model to predict AIV cases throughout the US at the county scale as a function of 12 environmental variables, sampling effort, and proximity to other counties with influenza outbreaks. Our analysis did not distinguish between types of influenza, including low or highly pathogenic forms.

RESULTS

Analysis of 13,046 cloacal samples collected from 225 bird species in 41 US states between 2005 and 2008 indicates that the average prevalence of influenza in passerines is greater than the prevalence in eight other avian orders. Our regression model identifies the Great Plains and the Pacific Northwest as high-risk areas for AIV. Highly significant predictors of AIV include the amount of harvested cropland and the first day of the year when a county is snow free.

CONCLUSIONS

Although the prevalence of influenza in waterfowl has long been appreciated, we show that 22 species of song birds and perching birds (order Passeriformes) are influenza reservoirs in the contiguous US.

Spatial variation of haemosporidian parasite infection in African rainforest bird species

Spatial heterogeneity influences the distribution, prevalence, and diversity of haemosporidian parasites. Previous studies have found complex patterns of prevalence with respect to habitat characteristics and parasite genotype, and their interactions, but there is little information regarding how parasitemia intensity and the prevalence of co-infections may vary in space. Here, using both molecular methods and microscopy, we report an analysis of the variation of parasitemia intensity and co-infections of avian haemosporidian parasites ( Plasmodium and Haemoproteus species) in 2 common African birds species, the yellow-whiskered greenbul ( Andropadus latirostris ) and the olive sunbird ( Cyanomitra olivacea ), at 3 sites with distinct habitat characteristics in Ghana. First, we found an interaction between the site and host species for the prevalence of Plasmodium spp. and Haemoproteus spp. For the olive sunbird, the prevalence of Plasmodium spp., as well as the number of individuals with co-infections, varied significantly among the sites, but these measures remained constant for the yellow-whiskered greenbul. In addition, yellow-whiskered greenbuls infected with Haemoproteus spp. were found only at 1 site. Furthermore, for both bird species, the parasitemia intensity of Plasmodium spp. varied significantly among the 3 sites, but with opposing trends. These results suggest that spatial heterogeneity differently affects haemosporidian infection parameters in these vertebrate-hosts. Environmental conditions here can either favor or reduce parasite infection. We discuss the implications of these discrepancies for conservation and ecological studies of infectious diseases in natural populations.

Modeling environmentally associated morphological and genetic variation in a rainforest bird, and its application to conservation prioritization

To better understand how environment shapes phenotypic and genetic variation, we explore the relationship between environmental variables across Ecuador and genetic and morphological variation in the wedge-billed woodcreeper (Glyphorynchus spirurus), a common Neotropical rainforest bird species. Generalized dissimilarity models show that variation in amplified fragment length polymorphism markers was strongly associated with environmental variables on both sides of the Andes, but could also partially be explained by geographic distance on the western side of the Andes. Tarsus, wing, tail, and bill lengths and bill depth were well explained by environmental variables on the western side of the Andes, whereas only tarsus length was well explained on the eastern side. Regions that comprise the highest rates of genetic and phenotypic change occur along steep elevation gradients in the Andes. Such environmental gradients are likely to be particularly important for maximizing adaptive diversity to minimize the impacts of climate change. Using a framework for conservation prioritization based on preserving ecological and evolutionary processes, we found little overlap between currently protected areas in Ecuador and regions we predicted to be important in maximizing adaptive variation.

Modeling the effects of anthropogenic habitat change on savanna snake invasions into African rainforest

We used a species-distribution modeling approach, ground-based climate data sets, and newly available remote-sensing data on vegetation from the MODIS and Quick Scatterometer sensors to investigate the combined effects of human-caused habitat alterations and climate on potential invasions of rainforest by 3 savanna snake species in Cameroon, Central Africa: the night adder (Causus maculatus), olympic lined snake (Dromophis lineatus), and African house snake (Lamprophis fuliginosus). Models with contemporary climate variables and localities from native savanna habitats showed that the current climate in undisturbed rainforest was unsuitable for any of the snake species due to high precipitation. Limited availability of thermally suitable nest sites and mismatches between important life-history events and prey availability are a likely explanation for the predicted exclusion from undisturbed rainforest. Models with only MODIS-derived vegetation variables and savanna localities predicted invasion in disturbed areas within the rainforest zone, which suggests that human removal of forest cover creates suitable microhabitats that facilitate invasions into rainforest. Models with a combination of contemporary climate, MODIS- and Quick Scatterometer-derived vegetation variables, and forest and savanna localities predicted extensive invasion into rainforest caused by rainforest loss. In contrast, a projection of the present-day species-climate envelope on future climate suggested a reduction in invasion potential within the rainforest zone as a consequence of predicted increases in precipitation. These results emphasize that the combined responses of deforestation and climate change will likely be complex in tropical rainforest systems.

Parallel shifts in ecology and natural selection in an island lizard

BACKGROUND

Natural selection is a potent evolutionary force that shapes phenotypic variation to match ecological conditions. However, we know little about the year-to-year consistency of selection, or how inter-annual variation in ecology shapes adaptive landscapes and ultimately adaptive radiations. Here we combine remote sensing data, field experiments, and a four-year study of natural selection to show that changes in vegetation structure associated with a severe drought altered both habitat use and natural selection in the brown anole, Anolis sagrei.

RESULTS

In natural populations, lizards increased their use of vegetation in wet years and this was correlated with selection on limb length but not body size. By contrast, a die-back of vegetation caused by drought was followed by reduced arboreality, selection on body size, and relaxed selection on limb length. With the return of the rains and recovery of vegetation, selection reverted back to pre-drought pattern of selection acting on limb length but not body size. To test for the impact of vegetation loss on natural selection during the drought, we experimentally removed vegetation on a separate study island in a naturally wet year. The experiment revealed similar inter-annual changes in selection on body size but not limb length.

CONCLUSION

Our results illustrate the dynamic nature of ecology driving natural selection on Anolis morphology and emphasize the importance of inter-annual environmental variation in shaping adaptive variation. In addition, results illustrate the utility of using remote sensing data to examine ecology's role in driving natural selection.

Evolutionary consequences of human disturbance in a rainforest bird species from Central Africa

Relatively little attention has been directed towards understanding the impacts of human disturbance on evolutionary processes that produce and maintain biodiversity. Here, we examine the influence of anthropogenic habitat changes on traits typically associated with natural and sexual selection in the little greenbul (Andropadus virens), an African rainforest bird species. Using satellite remote-sensing and field survey data, we classified habitats into nonhuman-altered mature and human-altered secondary forest. Mature rainforest consisted of pristine rainforest, with little or no human influence, and secondary forest was characterized by plantations of coffee and cacao and high human impacts. Andropadus virens abundance was higher in secondary forest, and populations inhabiting mature rainforest were significantly larger in wing and tarsus length and bill size; characters often correlated with fitness. To assess the extent to which characters important in sexual section and mate choice might be influenced by habitat change, we also examined differences in plumage colour and song. Plumage colour and the variance in plumage luminance were found to differ between forest types, and song duration was found to be significantly longer in mature forest. The possible adaptive significance of these differences in traits is discussed. Despite relatively high levels of gene flow across habitats, amplified fragment length polymorphism analysis revealed that a small proportion of high-F(ST) loci differentiated mature from secondary forest populations. These loci were significant outliers against neutral expectations in a simulation analysis, suggesting a role for divergent selection in differentiation across habitats. A distance-based redundancy analysis further showed that forest type as defined by remote-sensing variables was significantly associated with genetic dissimilarities between habitats, even when controlling for distance. The observed shifts in morphology, plumage and song were consistent with divergent selection on heritable variation, but a role for plasticity cannot be ruled out. Results suggest that anthropogenic habitat changes may have evolutionary consequences, with implications for conservation and restoration.

The changing carbon cycle at Mauna Loa Observatory

The amplitude of the CO(2) seasonal cycle at the Mauna Loa Observatory (MLO) increased from the early 1970s to the early 1990s but decreased thereafter despite continued warming over northern continents. Because of its location relative to the large-scale atmospheric circulation, the MLO receives mainly Eurasian air masses in the northern hemisphere (NH) winter but relatively more North American air masses in NH summer. Consistent with this seasonal footprint, our findings indicate that the MLO amplitude registers North American net carbon uptake during the warm season and Eurasian net carbon release as well as anomalies in atmospheric circulation during the cold season. From the early 1970s to the early 1990s, our analysis was consistent with that of Keeling et al. [Keeling CD, Chin JFS, Whorf TP (1996) Nature 382:146-149], suggesting that the increase in the MLO CO(2) amplitude is dominated by enhanced photosynthetic drawdown in North America and enhanced respiration in Eurasia. In contrast, the recent decline in the CO(2) amplitude is attributed to reductions in carbon sequestration over North America associated with severe droughts from 1998 to 2003 and changes in atmospheric circulation leading to decreased influence of Eurasian air masses. With the return of rains to the U.S. in 2004, both the normalized difference vegetation index and the MLO amplitude sharply increased, suggesting a return of the North American carbon sink to more normal levels. These findings indicate that atmospheric CO(2) measurements at remote sites can continue to play an important role in documenting changes in land carbon flux, including those related to widespread drought, which may continue to worsen as a result of global warming.

Drier summers cancel out the CO2 uptake enhancement induced by warmer springs

An increase in photosynthetic activity of the northern hemisphere terrestrial vegetation, as derived from satellite observations, has been reported in previous studies. The amplitude of the seasonal cycle of the annually detrended atmospheric CO(2) in the northern hemisphere (an indicator of biospheric activity) also increased during that period. We found, by analyzing the annually detrended CO(2) record by season, that early summer (June) CO(2) concentrations indeed decreased from 1985 to 1991, and they have continued to decrease from 1994 up to 2002. This decrease indicates accelerating springtime net CO(2) uptake. However, the CO(2) minimum concentration in late summer (an indicator of net growing-season uptake) showed no positive trend since 1994, indicating that lower net CO(2) uptake during summer cancelled out the enhanced uptake during spring. Using a recent satellite normalized difference vegetation index data set and climate data, we show that this lower summer uptake is probably the result of hotter and drier summers in both mid and high latitudes, demonstrating that a warming climate does not necessarily lead to higher CO(2) growing-season uptake, even in high-latitude ecosystems that are considered to be temperature limited.

Climatic control of the high-latitude vegetation greening trend and Pinatubo effect

A biogeochemical model of vegetation using observed climate data predicts the high northern latitude greening trend over the past two decades observed by satellites and a marked setback in this trend after the Mount Pinatubo volcano eruption in 1991. The observed trend toward earlier spring budburst and increased maximum leaf area is produced by the model as a consequence of biogeochemical vegetation responses mainly to changes in temperature. The post-Pinatubo decline in vegetation in 1992-1993 is apparent as the effect of temporary cooling caused by the eruption. High-latitude CO(2) uptake during these years is predicted as a consequence of the differential response of heterotrophic respiration and net primary production.