The genome-wide signature of short-term temporal selection.

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multigenerational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a 10-y population-genomic survey of the microcrustacean Daphnia pulex. The genome sequences of [Formula: see text]800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the following: the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals); the preponderance of weak positive selection operating on minor alleles; and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that interannual fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the further development of theoretical expressions for the interpretation of population-genomic data.

The extent of introgression between incipient Clarkia species is determined by temporal environmental variation and mating system.

Introgression is pervasive across the tree of life but varies across taxa, geography, and genomic regions. However, the factors modulating this variation and how they may be affected by global change are not well understood. Here, we used 200 genomes and a 15-y site-specific environmental dataset to investigate the effects of environmental variation and mating system divergence on the magnitude of introgression between a recently diverged outcrosser-selfer pair of annual plants in the genus Clarkia. These sister taxa diverged very recently and subsequently came into secondary sympatry where they form replicated contact zones. Consistent with observations of other outcrosser-selfer pairs, we found that introgression was asymmetric between taxa, with substantially more introgression from the selfer to the outcrosser. This asymmetry was caused by a bias in the direction of initial F1 hybrid formation and subsequent backcrossing. We also found extensive variation in the outcrosser's admixture proportion among contact zones, which was predicted nearly entirely by interannual variance in spring precipitation. Greater fluctuations in spring precipitation resulted in higher admixture proportions, likely mediated by the effects of spring precipitation on the expression of traits that determine premating reproductive isolation. Climate-driven hybridization dynamics may be particularly affected by global change, potentially reshaping species boundaries and adaptation to novel environments.

Carbon reduction and water saving potentials for growing corrugated boxes for express delivery services in China.

Corrugated packaging for express grew by 90 times to 16.5 Mt y-1 in China, where 81% of recent global express delivery growth occurred. However, the environmental impacts of production, usage, disposal, and recycling of corrugated boxes under the entire supply chain remain unclear. Here, we estimate the magnitudes, drivers, and mitigation potentials of cradle-to-grave life-cycle carbon footprint (CF) and three colors of water footprints (WFs) for corrugated cardboard packaging in China. Over 2007 to 2021, CF, blue and gray WFs per unit package decreased by 45%, 60%, and 84%, respectively, while green WF increased by 23% with growing imports of virgin pulp and China's waste ban. National total CF and WFs were 21 to 102 folded with the scale effects. Only a combination of the supply chain reconstruction, lighter single-piece packaging, and increased recycling rate can possibly reduce the environmental footprints by 24 to 44% by 2035.

Spatial versus spatio-temporal approaches for studying metacommunities: a multi-taxon analysis in Mediterranean and tropical temporary ponds.

Prior research on metacommunities has largely focused on snapshot surveys, often overlooking temporal dynamics. In this study, our aim was to compare the insights obtained from metacommunity analyses based on a spatial approach repeated over time, with a spatio-temporal approach that consolidates all data into a single model. We empirically assessed the influence of temporal variation in the environment and spatial connectivity on the structure of metacommunities in tropical and Mediterranean temporary ponds. Employing a standardized methodology across both regions, we surveyed multiple freshwater taxa in three time periods within the same hydrological year from multiple temporary ponds in each region. To evaluate how environmental, spatial and temporal influences vary between the two approaches, we used nonlinear variation partitioning analyses based on generalized additive models. Overall, this study underscores the importance of adopting spatio-temporal analytics to better understand the processes shaping metacommunities. While the spatial approach suggested that environmental factors had a greater influence, our spatio-temporal analysis revealed that spatial connectivity was the primary driver influencing metacommunity structure in both regions. Temporal effects were equally important as environmental effects, suggesting a significant role of ecological succession in metacommunity structure.

Rapid quantification of biological nitrogen fixation using optical spectroscopy.

Biological nitrogen fixation (BNF) provides a globally important input of nitrogen (N); its quantification is critical but technically challenging. Leaf reflectance spectroscopy offers a more rapid approach than traditional techniques to measure plant N concentration ([N]) and isotopes (δ15N). Here we present a novel method for rapidly and inexpensively quantifying BNF using optical spectroscopy. We measured plant [N], δ15N, and the amount of N derived from atmospheric fixation (Ndfa) following the standard traditional methodology using isotope ratio mass spectrometry (IRMS) from tissues grown under controlled conditions and taken from field experiments. Using the same tissues, we predicted the same three parameters using optical spectroscopy. By comparing the optical spectroscopy-derived results with traditional measurements (i.e. IRMS), the amount of Ndfa predicted by optical spectroscopy was highly comparable to IRMS-based quantification, with R2 being 0.90 (slope=0.90) and 0.94 (slope=1.02) (root mean square error for predicting legume δ15N was 0.38 and 0.43) for legumes grown in glasshouse and field, respectively. This novel application of optical spectroscopy facilitates BNF studies because it is rapid, scalable, low cost, and complementary to existing technologies. Moreover, the proposed method successfully captures the dynamic response of BNF to climate changes such as warming and drought.

Temporal variability can promote migration between habitats.

Understanding the conditions that promote the evolution of migration is important in ecology and evolution. When environments are fixed and there is one most favorable site, migration to other sites lowers overall growth rate and is not favored. Here we ask, can environmental variability favor migration when there is one best site on average? Previous work suggests that the answer is yes, but a general and precise answer remained elusive. Here we establish new, rigorous inequalities to show (and use simulations to illustrate) how stochastic growth rate can increase with migration when fitness (dis)advantages fluctuate over time across sites. The effect of migration between sites on the overall stochastic growth rate depends on the difference in expected growth rates and the variance of the fluctuating difference in growth rates. When fluctuations (variance) are large, a population can benefit from bursts of higher growth in sites that are worse on average. Such bursts become more probable as the between-site variance increases. Our results apply to many (≥ 2) sites, and reveal an interplay between the length of paths between sites, the average differences in site-specific growth rates, and the size of fluctuations. Our findings have implications for evolutionary biology as they provide conditions for departure from the reduction principle, and for ecological dynamics: even when there are superior sites in a sea of poor habitats, variability and habitat quality across space determine the importance of migration.

Spatial and temporal variation in lake macroinvertebrate communities is decreased by eutrophication.

Eutrophication impacts freshwater ecosystems and biodiversity across the world. While temporal monitoring has shown changes in the nutrient inputs in many areas, how spatial and temporal beta diversity change along the eutrophication gradient under a changing context remains unclear. In this regard, analyses based on time series spanning multiple years are particularly scarce. We sampled benthic macroinvertebrates in 32 sites across three lake habitat types (MACROPHYTE, OPEN WATER, PHYTOPLANKTON) along the eutrophication gradient of Lake Taihu in four seasons from 2007 to 2019. Our purpose was to identify the relative contributions of spatial and temporal dissimilarity (i.e., inter-annual dissimilarity and seasonal dissimilarity) to overall benthic biodiversity. We also examined spatio-temporal patterns in community assembly mechanisms and how associated variation in benthic macroinvertebrate communities responded to nutrient indicators. Results showed that eutrophication caused macroinvertebrate community homogenization both along spatial and temporal gradients. Though spatial variability dominated the variation of species richness, abundance and community dissimilarity, seasons within years dissimilarity, inter-annual dissimilarity and seasonal dissimilarity were much more sensitive to eutrophication. Moreover, eutrophication inhibited a strong environmental control in benthic macroinvertebrate community assembly, including a dominant role of deterministic process in the spatial variation of macroinvertebrate communities and transition from stochastic to deterministic process in the temporal assembly of macroinvertebrate communities along the eutrophication gradient. In addition, some sites in PHYTOPLANKTON habitats showed similar spatial dissimilarity and spatial SES as sites in MACROPHYTE habitats, and the decreased spatial dissimilarity of three habitats implying that lake ecosystem recovery projects have achieved their goal at least to a certain degree.

Hourly land-use regression modeling for NO2 and PM2.5 in the Netherlands.

Annual average land-use regression (LUR) models have been widely used to assess spatial patterns of air pollution exposures. However, they fail to capture diurnal variability in air pollution and consequently might result in biased dynamic exposure assessments. In this study we aimed to model average hourly concentrations for two major pollutants, NO2 and PM2.5, for the Netherlands using the LUR algorithm. We modelled the spatial variation of average hourly concentrations for the years 2016-2019 combined, for two seasons, and for two weekday types. Two modelling approaches were used, supervised linear regression (SLR) and random forest (RF). The potential predictors included population, road, land use, satellite retrievals, and chemical transport model pollution estimates variables with different buffer sizes. We also temporally adjusted hourly concentrations from a 2019 annual model using the hourly monitoring data, to compare its performance with the hourly modelling approach. The results showed that hourly NO2 models performed overall well (5-fold cross validation R2 = 0.50-0.78), while the PM2.5 performed moderately (5-fold cross validation R2 = 0.24-0.62). Both for NO2 and PM2.5 the warm season models performed worse than the cold season ones, and the weekends' worse than weekdays'. The performance of the RF and SLR models was similar for both pollutants. For both SLR and RF, variables with larger buffer sizes representing variation in background concentrations, were selected more often in the weekend models compared to the weekdays, and in the warm season compared to the cold one. Temporal adjustment of annual average models performed overall worse than both modelling approaches (NO2 hourly R2 = 0.35-0.70; PM2.5 hourly R2 = 0.01-0.15). The difference in model performance and selection of variables across hours, seasons, and weekday types documents the benefit to develop independent hourly models when matching it to hourly time activity data.

Exploring the environmental influences and community assembly processes of bacterioplankton in a subtropical coastal system: Insights from the Beibu Gulf in China.

Due to rapid urbanization, the Beibu Gulf, a semi-closed gulf in the northwestern South China Sea, faces escalating ecological and environmental threats. Understanding the assembly mechanisms and driving factors of bacterioplankton in the Beibu Gulf is crucial for preserving its ecological functions and services. In the present study, we investigated the spatiotemporal dynamics of bacterioplankton communities and their assembly mechanisms in the Beibu Gulf based on the high-throughput sequencing of the bacterial 16 S rRNA gene. Results showed significantly higher bacterioplankton diversity during the wet season compared to the dry season. Additionally, distinct seasonal variations in bacterioplankton composition were observed, characterized by an increase in Cyanobacteria and Thermoplasmatota and a decrease in Proteobacteria and Bacteroidota during the wet season. Null model analysis revealed that stochastic processes governed bacterioplankton community assembly in the Beibu Gulf, with drift and homogenizing dispersal dominating during the dry and wet seasons, respectively. Enhanced deterministic assembly of bacterioplankton was also observed during the wet season. Redundancy and random forest model analyses identified the physical properties (e.g., temperature) and nutrient content (e.g., nitrate) of water as primary environmental drivers influencing bacterioplankton dynamics. Moreover, variation partitioning and distance-decay of similarity revealed that environmental filtering played a significant role in shaping bacterioplankton variations in this rapidly developed coastal ecosystem. These findings advance our understanding of bacterioplankton assembly in coastal ecosystems and establish a theoretical basis for effective ecological health management amidst ongoing global changes.

High diversity within and low but significant genetic differentiation among geographic and temporal populations of the global Streptococcus pneumoniae.

Streptococcus pneumoniae is the major cause of invasive pneumococcal disease. However, the global population structure remains largely unexplored. In this study, we investigated the spatial and temporal patterns of genetic variation of S. pneumoniae based on archived multilocus sequence typing data from PubMLST.org. Our analyses demonstrated both shared and unique distributions of sequence types (STs) and allele types among regional populations. Among the 17 915 global STs, 36 representing 15 263 isolates were broadly shared among all six continents, consistent with recent clonal dispersal and expansion of this pathogen. The analysis of molecular variance revealed that >96% genetic variations were found within individual regional populations. However, though low (<4%), statistically significant genetic differentiation among regional populations was observed. Comparisons between non-clone-corrected and clone-corrected datasets showed that localized clonal expansion contributed significantly to the observed genetic differentiations among regions. Temporal analyses of the isolates showed that implementation of pneumococcal conjugate vaccine impacted the distributions of STs, but the effect on population structure was relatively limited. Linkage disequilibrium analyses identified evidence for recombination in all continental populations; however, the inferred recombination was not random. We discussed the limitations and implications of our analyses to the global epidemiology and future vaccine developments for S. pneumoniae.

A comprehensive drought index based on spatial principal component analysis and its application in northern China.

In the background of the greenhouse effect, drought events occurred more frequently. How to monitor drought events scientifically and efficiently is very urgent at present. In this study, we employed the Vegetation Water Supply Index (VSWI), Temperature Vegetation Drought Index (TVDI), and Crop Water Stress Index (CWSI) as individual variables to construct a composite drought index (CDI) using spatial principal component analysis (SPCA). The validity of CDI was assessed using gross primary productivity (GPP), soil moisture (SM), Standardized Precipitation Evapotranspiration Index (SPEI), and Vegetation Condition Index (VCI). CDI was subsequently used for drought monitoring in northern China from 2011 to 2020. The results showed that (1) at a 99% confidence level, the Pearson correlation coefficients between CDI and GPP was 0.72, while the value between CDI and SM was 0.69, which indicated the relationship between SM, GPP, and CDI was significant. (2) We compared CDI with other variables such as Standardized Precipitation Evapotranspiration Index (SPEI) and Crop Drought Index (CDI) and found that the monitoring result of CDI was more sensitive, which indicated that the proposed CDI had a better effect in local drought monitoring. (3) The results of CDI showed that the drought status in the northern region during 2011-2020 lasted from March to October, and the high severe drought period generally occurs in March-May and September-October, with low severe drought in June-August.

Time series analysis of PM2.5 pollution risk based on the supply and demand of PM2.5 removal service: a case study of the urban areas of Beijing.

Demonstrating the temporal changes in PM2.5 pollution risk in regions facing serious PM2.5 pollution problems can provide scientific evidence for the air pollution control of the region. However, research on the variation of PM2.5 pollution risk on a fine temporal scale is very limited. Therefore, we developed a method for quantitative characterizing PM2.5 pollution risk based on the supply and demand of PM2.5 removal services, analyzed the time series characteristics of PM2.5 pollution risk, and explored the reasons for the temporal changes using the urban areas of Beijing as the case study area. The results show that the PM2.5 pollution risk in the urban areas of Beijing was close between 2008 and 2012, decreased by approximately 16.3% in 2016 compared to 2012, and further decreased by approximately 13.2% in 2021 compared to 2016. The temporal variation pattern of the PM2.5 pollution risk in 2016 and 2021 showed significant differences, including an increase in the number of risk-free days, a decrease in the number of heavily polluted days, and an increase in the stability of the risk day sequence. The significant reduction in risk level was mainly attributed to Beijing's air pollution control measures, supplemented by the impact of COVID-19 control measures in 2021. The results of PM2.5 pollution risk decomposition indicate that compared to the previous 2 years, the stability and predictability of the risk variation in 2016 increased, but the overall characteristics of high risk from November to February and low risk from April to September did not change. The high risk from November to February was mainly due to the demand for coal heating during this period, a decrease in PM2.5 removal service supply caused by plant leaf fall, and the common occurrence of temperature inversions in winter, which hinders the diffusion of air pollutants. This study provides a method for the analysis of PM2.5 pollution risk on fine temporal scales and may provide a reference for the PM2.5 pollution control in the urban areas of Beijing.

Temporal dynamics of urban air pollutants and their correlation with associated meteorological parameters: an investigation in northern Indian cities.

This study delves into the intricate dynamics of air pollution in the rapidly expanding northern regions of India, examining the intertwined influences of agricultural burning, industrialization, and meteorological conditions. Through comprehensive analysis of key pollutants (PM2.5, PM10, NO2, SO2, CO, O3) across ten monitoring stations in Uttar Pradesh, Haryana, Delhi, and Punjab, a consistent pattern of high pollution levels emerges, particularly notable in Delhi. Varanasi leads in SO2 and O3 concentrations, while Moradabad stands out for CO levels, and Jalandhar for SO2 concentrations. The study further elucidates the regional distribution of pollutants, with Punjab receiving significant contributions from SW, SE, and NE directions, while Haryana and Delhi predominantly face air masses from SE and NE directions. Uttar Pradesh's pollution sources are primarily local, with additional inputs from various directions. Moreover, significant negative correlations (p < 0.05) between PM10, NO2, SO2, O3, and relative humidity (RH) underscore the pivotal role of meteorological factors in shaping pollutant levels. Strong positive correlations between PM2.5 and NO2 (0.71 to 0.93) suggest shared emission sources or similar atmospheric conditions in several cities. This comprehensive understanding highlights the urgent need for targeted mitigation strategies to address the multifaceted drivers of air pollution, ensuring the protection of public health and environmental sustainability across the region.

Spatial and temporal-trend assessment of desertification-sensitive land using the desertification sensitivity index in the provincial Ninh Thuan, Vietnam.

Desertification is a specific land-degrading process, reducing soil productivity and potentially threatening global food security. Therefore, spatially and temporally identifying and mapping desertification-sensitive areas is essential for better management. The current study aimed to (1) assess spatial areas sensitive to desertification and (2) examine the changing tendency of the desertification-sensitive areas over the past 25 years in the provincial Ninh Thuan. The desertification sensitivity index (DSI) was computed based on the Medalus model using 10 quantitative parameters, grouped into the soil, climate, and vegetation quality indexes, computed for the years 1996, 2005, 2010, and 2016. GIS was used to map desertification-sensitive areas associated with five DSI classes. Results showed that classes II and III had the highest area percentage, followed by classes IV and V, and class I. The classes most sensitive to desertification (classes IV and V) covered around 13 to 17%, and classes II and III were 25 to 32% of the total study area, respectively. The coastal areas located in the southeastern parts were more sensitive to desertification than the other parts. Over the four examined periods, the areas of classes IV and V increased while those of classes II and I decreased. These indicated that the study province tended to increase in its desertification sensitivity with a severe increase in the coastal areas over the past 25 years. The key factors involved in these changes could be related the human activities and climate variation, which could be more serious in southeastern areas than in the other areas.

Temporal variation of the PM2.5/PM10 ratio and its association with meteorological factors in a South American megacity: Metropolitan Area of Lima-Callao, Peru.

The Metropolitan Area of Lima-Callao (MALC) is a South American megacity that has suffered a serious deterioration in air quality due to high levels of particulate matter (PM2.5 and PM10). Studies on the behavior of the PM2.5/PM10 ratio and its temporal variability in relation to meteorological parameters are still very limited. The objective of this study was to analyze the temporal trends of the PM2.5/PM10 ratio, its temporal variability, and its association with meteorological variables over a period of 5 years (2015-2019). For this, the Theil-Sen estimator, bivariate polar plots, and correlation analysis were used. The regions of highest mean concentrations of PM2.5 and PM10 were identified at eastern Lima (ATE station-41.2 µg/m3) and southern Lima (VMT station-126.7 µg/m3), respectively. The lowest concentrations were recorded in downtown Lima (CDM station-16.8 µg/m3 and 34.0 µg/m3, respectively). The highest average PM2.5/PM10 ratio was found at the CDM station (0.55) and the lowest at the VMT station (0.27), indicating a predominance of emissions from the vehicular fleet within central Lima and a greater emission of coarse particles by resuspension in southern Lima. The temporal progression of the ratio of PM2.5/PM10 showed positive and highly significant trends in northern and central Lima with values of 0.03 and 0.1 units of PM2.5/PM10 per year, respectively. In the southern region of Lima, the trend was also significant, showcasing a value of 0.02 units of PM2.5/PM10 per year. At the hourly and monthly level, the PM2.5/PM10 ratio presented a negative and significant correlation with wind speed and air temperature, and a positive and significant correlation with relative humidity. These findings offer insights into identifying the sources of PM pollution and are useful for implementing regulations to reduce air emissions considering both anthropogenic sources and meteorological dispersion patterns.

Bioaccumulation of Cadmium in Muscle and Liver Tissues of Juvenile Yellowfin Tuna (Thunnus albacares) from the Indian Ocean.

The present study evaluated the cadmium (Cd) levels and temporal variation of Cd in dark muscle, white muscle, and liver of juvenile Thunnus albacares. 72 individuals (Standard length: 50-67 cm; weight: 0.8-2.5 kg) were collected from Indian Oceanic water around Sri Lanka during the period between April 2021 to May 2022. Total Cd levels were analyzed using an Inductively Coupled Plasma Mass Spectrophotometer. The mean Cd levels (mean ± SD mg kg-1 dry weight) in different tissues varied with significantly higher levels in the liver (13.62 ± 0.98, p < 0.05), compared to dark muscle (0.52 ± 0.05), and white muscle (0.42 ± 0.04). Cd levels in liver tissues were positively correlated (p < 0.05) with the fish weight. The Cd levels reported in dark muscles, white muscles, and liver tissues were significantly higher (p < 0.05) during 2nd inter-monsoon than in the other monsoonal regimes and exceeded the maximum permissible level (0.1 mg kg-1 wet weight) set by the European Union (EU). However, the measured Cd levels in white and dark muscles were below the maximum permissible level (0.2 mg kg-1 wet weight) set by FAO/WHO. The Cd levels in all the liver tissues were above the levels set by the EU and FAO/WHO. Accordingly, people should avoid the consumption of liver tissues of T. albacares from the Indian Ocean. A human with a body weight of 60 kg can consume white muscles up to 4.667 kg per week without exceeding the Provisional Tolerable Weekly Intake.

The Slowing Rate of CpG Depletion in SARS-CoV-2 Genomes Is Consistent with Adaptations to the Human Host.

Depletion of CpG dinucleotides in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genomes has been linked to virus evolution, host-switching, virus replication, and innate immune responses. Temporal variations, if any, in the rate of CpG depletion during virus evolution in the host remain poorly understood. Here, we analyzed the CpG content of over 1.4 million full-length SARS-CoV-2 genomes representing over 170 million documented infections during the first 17 months of the pandemic. Our findings suggest that the extent of CpG depletion in SARS-CoV-2 genomes is modest. Interestingly, the rate of CpG depletion is highest during early evolution in humans and it gradually tapers off, almost reaching an equilibrium; this is consistent with adaptations to the human host. Furthermore, within the coding regions, CpG depletion occurs predominantly at codon positions 2-3 and 3-1. Loss of ZAP (Zinc-finger antiviral protein)-binding motifs in SARS-CoV-2 genomes is primarily driven by the loss of the terminal CpG within the motifs. Nonetheless, majority of the CpG depletion in SARS-CoV-2 genomes occurs outside ZAP-binding motifs. SARS-CoV-2 genomes selectively lose CpGs-motifs from a U-rich context; this may help avoid immune recognition by TLR7. SARS-CoV-2 alpha-, beta-, and delta-variants of concern have reduced CpG content compared to sequences from the beginning of the pandemic. In sum, we provide evidence that the rate of CpG depletion in virus genomes is not uniform and it greatly varies over time and during adaptations to the host. This work highlights how temporal variations in selection pressures during virus adaption may impact the rate and the extent of CpG depletion in virus genomes.

Spatially and temporally varying selection influence species boundaries in two sympatric Mimulus.

Spatially and temporally varying selection can maintain genetic variation within and between populations, but it is less well known how these forces influence divergence between closely related species. We identify the interaction of temporal and spatial variation in selection and their role in either reinforcing or eroding divergence between two closely related Mimulus species. Using repeated reciprocal transplant experiments with advanced generation hybrids, we compare the strength of selection on quantitative traits involved in adaptation and reproductive isolation in Mimulus guttatus and Mimulus laciniatus between two years with dramatically different water availability. We found strong divergent habitat-mediated selection on traits in the direction of species differences during a drought in 2013, suggesting that spatially varying selection maintains species divergence. However, a relaxation in divergent selection on most traits in an unusually wet year (2019), including flowering time, which is involved in pre-zygotic isolation, suggests that temporal variation in selection may weaken species differences. Therefore, we find evidence that temporally and spatially varying selection may have opposing roles in mediating species boundaries. Given our changing climate, future growing seasons are expected to be more similar to the dry year, suggesting that in this system climate change may actually increase species divergence.

Intestinal microbiota of Nearctic-Neotropical migratory birds vary more over seasons and years than between host species.

Seasonal migration of Nearctic-Neotropical passerine birds may have profound effects on the diversity and abundance of their host-associated microbiota. Migratory birds experience seasonal change in environments and diets throughout the course of the annual cycle that, along with recurrent biological events such as reproduction, may significantly impact their microbiota. In this study, we characterize the intestinal microbiota of four closely related species of migratory Catharus thrushes at three time points of their migratory cycle: during spring migration, on the summer breeding territories and during fall migration. Using observations replicated over 3 years, we determined that microbial community diversity of Catharus thrushes was significantly different across distinct time periods of the annual cycle, whereas community composition was more similar within than across years. Elevated alpha diversity in the summer birds compared to either migratory period indicated that birds may harbour a reduced microbiota during active migration. We also found that community composition of the microbiota did not substantially differ between host species. Finally, we recovered two phyla, Cyanobacteria and Planctomycetota, which are not commonly described from birds, that were in relatively high abundance in specific years. This study contributes to our growing understanding of how microbiota in wild birds vary throughout disparate ecological conditions and reveals potential axes across which an animal's microbial flexibility adapts to variable environments and recurrent biological conditions throughout the annual cycle.

Inter-annual Persistence of Canopy Fungi Driven by Abundance Despite High Spatial Turnover.

While it is now well established that fungal community composition varies spatially at a variety of scales, temporal turnover of fungi is less well understood. Here we studied inter-annual community compositional changes of fungi in a rainforest tree canopy environment. We tracked fungal community shifts over 3 years in three substrate types (live bryophytes, dead bryophytes, and host tree bark) and compared these changes to amounts of community turnover seen at small spatial scales in the same system. The effect of substrate type on fungal community composition was stronger than that of sampling year, which was very small but significant. Although levels of temporal turnover varied among substrates, with greater turnover in live bryophytes than other substrates, the amount of turnover from year to year was comparable to what is seen at spatial distances between 5 and 9 cm for the same substrate. Stability of communities was largely driven by a few fungi with high relative abundances. A majority of fungal occurrences were at low relative abundances (≤ 0.1%). These fungi tended to be short lived and persisted to following years ≤ 50% of the time, depending on substrate. Their presence and persistence are likely impacted by stochastic processes like dispersal limitation and disturbance. Most samples contained only one or a few fungi at high relative abundance (≥ 10%) that persisted half or more of the time. These more abundant and persistent fungi are expected to have sustained functional interactions within the canopy ecosystem.