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.

Widespread seasonal compensation effects of spring warming on northern plant productivity.

Climate change is shifting the phenological cycles of plants1, thereby altering the functioning of ecosystems, which in turn induces feedbacks to the climate system2. In northern (north of 30° N) ecosystems, warmer springs lead generally to an earlier onset of the growing season3,4 and increased ecosystem productivity early in the season5. In situ6 and regional7-9 studies also provide evidence for lagged effects of spring warmth on plant productivity during the subsequent summer and autumn. However, our current understanding of these lagged effects, including their direction (beneficial or adverse) and geographic distribution, is still very limited. Here we analyse satellite, field-based and modelled data for the period 1982-2011 and show that there are widespread and contrasting lagged productivity responses to spring warmth across northern ecosystems. On the basis of the observational data, we find that roughly 15 per cent of the total study area of about 41 million square kilometres exhibits adverse lagged effects and that roughly 5 per cent of the total study area exhibits beneficial lagged effects. By contrast, current-generation terrestrial carbon-cycle models predict much lower areal fractions of adverse lagged effects (ranging from 1 to 14 per cent) and much higher areal fractions of beneficial lagged effects (ranging from 9 to 54 per cent). We find that elevation and seasonal precipitation patterns largely dictate the geographic pattern and direction of the lagged effects. Inadequate consideration in current models of the effects of the seasonal build-up of water stress on seasonal vegetation growth may therefore be able to explain the differences that we found between our observation-constrained estimates and the model-constrained estimates of lagged effects associated with spring warming. Overall, our results suggest that for many northern ecosystems the benefits of warmer springs on growing-season ecosystem productivity are effectively compensated for by the accumulation of seasonal water deficits, despite the fact that northern ecosystems are thought to be largely temperature- and radiation-limited10.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Testing alternative hypotheses for evolutionary diversification in an African songbird: rainforest refugia versus ecological gradients.

Geographic isolation in rainforest refugia and local adaptation to ecological gradients may both be important drivers of evolutionary diversification. However, their relative importance and the underlying mechanisms of these processes remain poorly understood because few empirical studies address both putative processes in a single system. A key question is to what extent is divergence in signals that are important in mate and species recognition driven by isolation in rainforest refugia or by divergent selection across ecological gradients? We studied the little greenbul, Andropadus virens, an African songbird, in Cameroon and Uganda, to determine whether refugial isolation or ecological gradients better explain existing song variation. We then tested whether song variation attributable to refugial or ecological divergence was biologically meaningful using reciprocal playback experiments to territorial males. We found that much of the existing song variation can be explained by both geographic isolation and ecological gradients, but that divergence across the gradient, and not geographic isolation, affects male response levels. These data suggest that ecologically divergent traits, independent of historical isolation during glacial cycles, can promote reproductive isolation. Our study provides further support for the importance of ecology in explaining patterns of evolutionary diversification in ecologically diverse regions of the planet.

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

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