Assessing scale‐dependent effects on Forest biomass productivity based on machine learning

Estimating forest above‐ground biomass (AGB) productivity constitutes one of the most fundamental topics in forest ecological research. Based on a 30‐ha permanent field plot in Northeastern China, we modeled AGB productivity as output, and topography, species diversity, stand structure, and a stand density variable as input across a series of area scales using the Random Forest (RF) algorithm. As the grain size increased from 10 to 200 m, we found that the relative importance of explanatory variables that drove the variation of biomass productivity varied a lot, and the model accuracy was gradually improved. The minimum sampling area for biomass productivity modeling in this region was 140 × 140 m. Our study shows that the relationship of topography, species diversity, stand structure, and stand density variables with biomass productivity modeled using the RF algorithm changes when moving from scales typical of forest surveys (10 m) to larger scales (200 m) within a controlled methodology. These results should be of considerable interest to scientists concerned with forest assessment.     

Species turnover in ant assemblages is greater horizontally than vertically in the world's tallest tropical forest

Abiotic and biotic factors structure species assembly in ecosystems both horizontally and vertically. However, the way community composition changes along comparable horizontal and vertical distances in complex three‐dimensional habitats, and the factors driving these patterns, remains poorly understood. By sampling ant assemblages at comparable vertical and horizontal spatial scales in a tropical rainforest, we tested hypotheses that predicted differences in vertical and horizontal turnover explained by different drivers in vertical and horizontal space. These drivers included environmental filtering, such as microclimate (temperature, humidity, and photosynthetic photon flux density) and microhabitat connectivity (leaf area), which are structured differently across vertical and horizontal space. We found that both ant abundance and richness decreased significantly with increasing vertical height. Although the dissimilarity between ant assemblages increased with vertical distance, indicating a clear distance‐decay pattern, the dissimilarity was higher horizontally where it appeared independent of distance. The pronounced horizontal and vertical structuring of ant assemblages across short distances is likely explained by a combination of microclimate and microhabitat connectivity. Our results demonstrate the importance of considering three‐dimensional spatial variation in local assemblages and reveal how highly diverse communities can be supported by complex habitats.     

Population dynamics of the glacial relict amphipods in a subarctic lake: role of density‐dependent and density‐independent factors

Relative role of intrinsic density‐dependent factors (such as inter‐ and intraspecific competition, predation) and extrinsic density‐independent factors (environmental changes) in population dynamics is a key issue in ecology. Density‐dependent mechanisms are considered as important drivers of population dynamics in many vertebrate and insect species; however, their influence on the population dynamics of freshwater invertebrates is not clearly understood. In this study, I examined interannual variations in the abundance of the glacial relict amphipod Monoporeia affinis in a small subarctic lake based on long‐term (2002–2019) monitoring data. The results suggest that the population dynamics of amphipods in the lake is influenced by the combined effects of both intrinsic and extrinsic factors. The reproductive success of amphipod cohorts was inversely related to its initial abundance, indicating it is influenced by density‐dependent factors. M. affinis recruitment was negatively correlated with population density and near‐bottom temperature but positively correlated with food availability, which is defined as the concentration of chlorophyll a. Multiple regression with chlorophyll, temperature, and abundance of parent cohort as independent factors explained about 80% of the variation in the reproductive success of amphipods. The negative correlation between amphipod recruitment and water temperature indicates that the current climate conditions adversely affect the populations of glacial relict amphipods even in cold‐water lakes of the subarctic zone. Results of this study can be useful in environmental assessments to separate population oscillations connected with density‐dependent mechanisms from human‐mediated changes.     

Remotely sensed between‐individual functional trait variation in a temperate forest

1. Trait‐based ecology holds the promise to explain how plant communities work, for example, how functional diversity may support community productivity. However, so far it has been difficult to combine field‐based approaches assessing traits at the level of plant individuals with limited spatial coverage and approaches using remote sensing (RS) with complete spatial coverage but assessing traits at the level of vegetation pixels rather than individuals. By delineating all individual‐tree crowns within a temperate forest site and then assigning RS‐derived trait measures to these trees, we combine the two approaches, allowing us to use general linear models to estimate the influence of taxonomic or environmental variation on between‐ and within‐species variation across contiguous space.
2. We used airborne imaging spectroscopy and laser scanning to collect individual‐tree RS data from a mixed conifer‐angiosperm forest on a mountain slope extending over 5.5 ha and covering large environmental gradients in elevation as well as light and soil conditions. We derived three biochemical (leaf chlorophyll, carotenoids, and water content) and three architectural traits (plant area index, foliage‐height diversity, and canopy height), which had previously been used to characterize plant function, from the RS data. We then quantified the contributions of taxonomic and environmental variation and their interaction to trait variation and partitioned the remaining within‐species trait variation into smaller‐scale spatial and residual variation. We also investigated the correlation between functional trait and phylogenetic distances at the between‐species level. The forest consisted of 13 tree species of which eight occurred in sufficient abundance for quantitative analysis.
3. On average, taxonomic variation between species accounted for more than 15% of trait variation in biochemical traits but only around 5% (still highly significant) in architectural traits. Biochemical trait distances among species also showed a stronger correlation with phylogenetic distances than did architectural trait distances. Light and soil conditions together with elevation explained slightly more variation than taxonomy across all traits, but in particular increased plant area index (light) and reduced canopy height (elevation). Except for foliage‐height diversity, all traits were affected by significant interactions between taxonomic and environmental variation, the different responses of the eight species to the within‐site environmental gradients potentially contributing to the coexistence of the eight abundant species.
4. We conclude that with high‐resolution RS data it is possible to delineate individual‐tree crowns within a forest and thus assess functional traits derived from RS data at individual level. With this precondition fulfilled, it is then possible to apply tools commonly used in field‐based trait ecology to partition trait variation among individuals into taxonomic and potentially even genetic variation, environmental variation, and interactions between the two. The method proposed here presents a promising way of assessing individual‐based trait information with complete spatial coverage and thus allowing analysis of functional diversity at different scales. This information can help to better understand processes shaping community structure, productivity, and stability of forests.

     

Evaluating the role of body size and habitat type in movement behavior in human‐dominated systems: A frog's eye view

1. Animal movement is a key process that connects and maintains populations on the landscape, yet for most species, we do not understand how intrinsic and extrinsic factors interact to influence individual movement behavior.
2. Land‐use/land‐cover changes highlight that connectivity among populations will depend upon an individual''s ability to traverse habitats, which may vary as a result of habitat permeability, individual condition, or a combination of these factors.
3. We examined the effects of intrinsic (body size) and extrinsic (habitat type) factors on desiccation tolerance, movement, and orientation in three anuran species (American toads, Anaxyrus americanus; northern leopard frogs, Lithobates pipiens; and Blanchard''s cricket frogs, Acris blanchardi) using laboratory and field studies to connect the effects of susceptibility to desiccation, size, and movement behavior in single‐habitat types and at habitat edges.
4. Smaller anurans were more vulnerable to desiccation, particularly for species that metamorphose at relatively small sizes. Habitat type had the strongest effect on movement, while body size had more situational and species‐specific effects on movement. We found that individuals moved the farthest in habitat types that, when given the choice, they oriented away from, suggesting that these habitats are less favorable and could represent barriers to movement.
5. Overall, our work demonstrated that differences in habitat type had strong impacts on individual movement behavior and influenced choices at habitat edges. By integrating intrinsic and extrinsic factors into our study, we provided evidence that population connectivity may be influenced not only by the habitat matrix but also by the condition of the individuals leaving the habitat patch.

     

Nonproductive exposure of PBMCs to SARS‐CoV‐2 induces cell‐intrinsic innate immune responses

Cell‐intrinsic responses mounted in PBMCs during mild and severe COVID‐19 differ quantitatively and qualitatively. Whether they are triggered by signals emitted by productively infected cells of the respiratory tract or result from physical interaction with virus particles remains unclear. Here, we analyzed susceptibility and expression profiles of PBMCs from healthy donors upon ex vivo exposure to SARS‐CoV and SARS‐CoV‐2. In line with the absence of detectable ACE2 receptor expression, human PBMCs were refractory to productive infection. RT–PCR experiments and single‐cell RNA sequencing revealed JAK/STAT‐dependent induction of interferon‐stimulated genes (ISGs) but not proinflammatory cytokines. This SARS‐CoV‐2‐specific response was most pronounced in monocytes. SARS‐CoV‐2‐RNA‐positive monocytes displayed a lower ISG signature as compared to bystander cells of the identical culture. This suggests a preferential invasion of cells with a low ISG baseline profile or delivery of a SARS‐CoV‐2‐specific sensing antagonist upon efficient particle internalization. Together, nonproductive physical interaction of PBMCs with SARS‐CoV‐2‐ and, to a much lesser extent, SARS‐CoV particles stimulate JAK/STAT‐dependent, monocyte‐accentuated innate immune responses that resemble those detected in vivo in patients with mild COVID‐19.     

Attenuation of SARS‐CoV‐2 replication and associated inflammation by concomitant targeting of viral and host cap 2'‐O‐ribose methyltransferases

The SARS‐CoV‐2 infection cycle is a multistage process that relies on functional interactions between the host and the pathogen. Here, we repurposed antiviral drugs against both viral and host enzymes to pharmaceutically block methylation of the viral RNA 2''‐O‐ribose cap needed for viral immune escape. We find that the host cap 2''‐O‐ribose methyltransferase MTr1 can compensate for loss of viral NSP16 methyltransferase in facilitating virus replication. Concomitant inhibition of MTr1 and NSP16 efficiently suppresses SARS‐CoV‐2 replication. Using in silico target‐based drug screening, we identify a bispecific MTr1/NSP16 inhibitor with anti‐SARS‐CoV‐2 activity in vitro and in vivo but with unfavorable side effects. We further show antiviral activity of inhibitors that target independent stages of the host SAM cycle providing the methyltransferase co‐substrate. In particular, the adenosylhomocysteinase (AHCY) inhibitor DZNep is antiviral in in vitro, in ex vivo, and in a mouse infection model and synergizes with existing COVID‐19 treatments. Moreover, DZNep exhibits a strong immunomodulatory effect curbing infection‐induced hyperinflammation and reduces lung fibrosis markers ex vivo. Thus, multispecific and metabolic MTase inhibitors constitute yet unexplored treatment options against COVID‐19.     

Intercolony variation in reproductive skipping in the African penguin

In long‐lived species, reproductive skipping is a common strategy whereby sexually mature animals skip a breeding season, potentially reducing population growth. This may be an adaptive decision to protect survival, or a non‐adaptive decision driven by individual‐specific constraints. Understanding the presence and drivers of reproductive skipping behavior can be important for effective population management, yet in many species such as the endangered African penguin (Spheniscus demersus), these factors remain unknown. This study uses multistate mark‐recapture methods to estimate African penguin survival and breeding probabilities at two colonies between 2013 and 2020. Overall, survival (mean ± SE) was higher at Stony Point (0.82 ± 0.01) than at Robben Island (0.77 ± 0.02). Inter‐colony differences were linked to food availability; under decreasing sardine (Sardinops sagax) abundance, survival decreased at Robben Island and increased at Stony Point. Additionally, reproductive skipping was evident across both colonies; at Robben Island the probability of a breeder becoming a nonbreeder was ~0.22, versus ~0.1 at Stony Point. Penguins skipping reproduction had a lower probability of future breeding than breeding individuals; this lack of adaptive benefit suggests reproductive skipping is driven by individual‐specific constraints. Lower survival and breeding propensity at Robben Island places this colony in greater need of conservation action. However, further research on the drivers of inter‐colony differences is needed.     

Engineering defensin α‐helix to produce high‐affinity SARS‐CoV‐2 spike protein binding ligands

The binding of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) spike protein to the angiotensin‐converting enzyme 2 (ACE2) receptor expressed on the host cells is a critical initial step for viral infection. This interaction is blocked through competitive inhibition by soluble ACE2 protein. Therefore, developing high‐affinity and cost‐effective ACE2 mimetic ligands that disrupt this protein–protein interaction is a promising strategy for viral diagnostics and therapy. We employed human and plant defensins, a class of small (2–5 kDa) and highly stable proteins containing solvent‐exposed alpha‐helix, conformationally constrained by two disulfide bonds. Therefore, we engineered the amino acid residues on the constrained alpha‐helix of defensins to mimic the critical residues on the ACE2 helix 1 that interact with the SARS‐CoV‐2 spike protein. The engineered proteins (h‐deface2, p‐deface2, and p‐deface2‐MUT) were soluble and purified to homogeneity with a high yield from a bacterial expression system. The proteins demonstrated exceptional thermostability (Tm 70.7°C), high‐affinity binding to the spike protein with apparent K _d values of 54.4 ± 11.3, 33.5 ± 8.2, and 14.4 ± 3.5 nM for h‐deface2, p‐deface2, and p‐deface2‐MUT, respectively, and were used in a diagnostic assay that detected SARS‐CoV‐2 neutralizing antibodies. This work addresses the challenge of developing helical ACE2 mimetics by demonstrating that defensins provide promising scaffolds to engineer alpha‐helices in a constrained form for designing of high‐affinity ligands.     

Non‐invasive monitoring of multiple wildlife health factors by fecal microbiome analysis

Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (Cervus canadensis) and four host factors including sex, age, population, and physical condition (body‐fat). We paired a feature‐selection algorithm with an LDA‐classifier trained on elk differential bacterial abundance (16S‐rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave‐one‐out cross‐validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body‐fat, sex, and age‐class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non‐invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome‐based monitoring of wildlife populations and supports hypothetical expectations found in host‐microbiome theory.     

How low can you go? Introducing SeXY: sex identification from low‐quantity sequencing data despite lacking assembled sex chromosomes

Accurate sex identification is crucial for elucidating the biology of a species. In the absence of directly observable sexual characteristics, sex identification of wild fauna can be challenging, if not impossible. Molecular sexing offers a powerful alternative to morphological sexing approaches. Here, we present SeXY, a novel sex‐identification pipeline, for very low‐coverage shotgun sequencing data from a single individual. SeXY was designed to utilize low‐effort screening data for sex identification and does not require a conspecific sex‐chromosome assembly as reference. We assess the accuracy of our pipeline to data quantity by downsampling sequencing data from 100,000 to 1000 mapped reads and to reference genome selection by mapping to a variety of reference genomes of various qualities and phylogenetic distance. We show that our method is 100% accurate when mapping to a high‐quality (highly contiguous N50 > 30 Mb) conspecific genome, even down to 1000 mapped reads. For lower‐quality reference assemblies (N50 < 30 Mb), our method is 100% accurate with 50,000 mapped reads, regardless of reference assembly quality or phylogenetic distance. The SeXY pipeline provides several advantages over previously implemented methods; SeXY (i) requires sequencing data from only a single individual, (ii) does not require assembled conspecific sex chromosomes, or even a conspecific reference assembly, (iii) takes into account variation in coverage across the genome, and (iv) is accurate with only 1000 mapped reads in many cases.     

TNF‐α/IFN‐γ synergy amplifies senescence‐associated inflammation and SARS‐CoV‐2 receptor expression via hyper‐activated JAK/STAT1

Older age and underlying conditions such as diabetes/obesity or immunosuppression are leading host risk factors for developing severe complications from COVID‐19 infection. The pathogenesis of COVID‐19‐related cytokine storm, tissue damage, and fibrosis may be interconnected with fundamental aging processes, including dysregulated immune responses and cellular senescence. Here, we examined effects of key cytokines linked to cellular senescence on expression of SARS‐CoV‐2 viral entry receptors. We found exposure of human umbilical vein endothelial cells (HUVECs) to the inflammatory cytokines, TNF‐α + IFN‐γ or a cocktail of TNF‐α + IFN‐γ + IL‐6, increased expression of ACE2/DPP4, accentuated the pro‐inflammatory senescence‐associated secretory phenotype (SASP), and decreased cellular proliferative capacity, consistent with progression towards a cellular senescence‐like state. IL‐6 by itself failed to induce substantial effects on viral entry receptors or SASP‐related genes, while synergy between TNF‐α and IFN‐γ initiated a positive feedback loop via hyper‐activation of the JAK/STAT1 pathway, causing SASP amplification. Breaking the interactive loop between senescence and cytokine secretion with JAK inhibitor ruxolitinib or antiviral drug remdesivir prevented hyper‐inflammation, normalized SARS‐CoV‐2 entry receptor expression, and restored HUVECs proliferative capacity. This loop appears to underlie cytokine‐mediated viral entry receptor activation and links with senescence and hyper‐inflammation.     

High diversity in Delta variant across countries revealed by genome‐wide analysis of SARS‐CoV‐2 beyond the Spike protein

The highly contagious Delta variant of SARS‐CoV‐2 has become a prevalent strain globally and poses a public health challenge around the world. While there has been extensive focus on understanding the amino acid mutations in the Delta variant’s Spike protein, the mutational landscape of the rest of the SARS‐CoV‐2 proteome (25 proteins) remains poorly understood. To this end, we performed a systematic analysis of mutations in all the SARS‐CoV‐2 proteins from nearly 2 million SARS‐CoV‐2 genomes from 176 countries/territories. Six highly prevalent missense mutations in the viral life cycle‐associated Membrane (I82T), Nucleocapsid (R203M, D377Y), NS3 (S26L), and NS7a (V82A, T120I) proteins are almost exclusive to the Delta variant compared to other variants of concern (mean prevalence across genomes: Delta = 99.74%, Alpha = 0.06%, Beta = 0.09%, and Gamma = 0.22%). Furthermore, we find that the Delta variant harbors a more diverse repertoire of mutations across countries compared to the previously dominant Alpha variant. Overall, our study underscores the high diversity of the Delta variant between countries and identifies a list of amino acid mutations in the Delta variant’s proteome for probing the mechanistic basis of pathogenic features such as high viral loads, high transmissibility, and reduced susceptibility against neutralization by vaccines.     

The role of context in elucidating drivers of animal movement

Despite its consequences for ecological processes and population dynamics, intra‐specific variability is frequently overlooked in animal movement studies. Consequently, the necessary resolution to reveal drivers of individual movement decisions is often lost as animal movement data are aggregated to infer average or population patterns. Thus, an empirical understanding of why a given movement pattern occurs remains patchy for many taxa, especially in marine systems. Nonetheless, movement is often rationalized as being driven by basic life history requirements, such as acquiring energy (feeding), reproduction, predator‐avoidance, and remaining in suitable environmental conditions. However, these life history requirements are central to every individual within a species and thus do not sufficiently account for the high intra‐specific variability in movement behavior and hence fail to fully explain the occurrence of multiple movement strategies within a species. Animal movement appears highly context dependent as, for example, within the same location, the behavior of both resident and migratory individuals is driven by life history requirements, such as feeding or reproduction, however different movement strategies are utilized to fulfill them. A systematic taxa‐wide approach that, instead of averaging population patterns, incorporates and utilizes intra‐specific variability to enable predictions as to which movement patterns can be expected under a certain context, is needed. Here, we use intra‐specific variability in elasmobranchs as a case study to introduce a stepwise approach for studying animal movement drivers that is based on a context‐dependence framework. We examine relevant literature to illustrate how this context‐focused approach can aid in reliably identifying drivers of a specific movement pattern. Ultimately, incorporating behavioral variability in the study of movement drivers can assist in making predictions about behavioral responses to environmental change, overcoming tagging biases, and establishing more efficient conservation measures.     

An ultra‐high affinity protein–protein interface displaying sequence‐robustness

Protein–protein interactions are crucial in biology and play roles in for example, the immune system, signaling pathways, and enzyme regulation. Ultra‐high affinity interactions (K _d <0.1 nM) occur in these systems, however, structures and energetics behind stability of ultra‐high affinity protein–protein complexes are not well understood. Regulation of the starch debranching barley limit dextrinase (LD) and its endogenous cereal type inhibitor (LDI) exemplifies an ultra‐high affinity complex (K _d of 42 pM). In this study the LD–LDI complex is investigated to unveil how robust the ultra‐high affinity is to LDI sequence variation at the protein–protein interface and whether alternative sequences can retain the ultra‐high binding affinity. The interface of LD–LDI was engineered using computational protein redesign aiming at identifying LDI variants predicted to retain ultra‐high binding affinity. These variants present a very diverse set of mutations going beyond conservative and alanine substitutions typically used to probe interfaces. Surface plasmon resonance analysis of the LDI variants revealed that high affinity of LD–LDI requires interactions of several residues at the rim of the protein interface, unlike the classical hotspot arrangement where key residues are found at the center of the interface. Notably, substitution of interface residues in LDI, including amino acids with functional groups different from the wild‐type, could occur without loss of affinity. This demonstrates that ultra‐high binding affinity can be conferred without hotspot residues, thus making complexes more robust to mutational drift in evolution. The present mutational analysis also demonstrates how energetic coupling can emerge between residues at large distances at the interface.     

Concordant geographic and genetic structure revealed by genotyping‐by‐sequencing in a New Zealand marine isopod

Population genetic structure in the marine environment can be influenced by life‐history traits such as developmental mode (biphasic, with distinct adult and larval morphology, and direct development, in which larvae resemble adults) or habitat specificity, as well as geography and selection. Developmental mode is thought to significantly influence dispersal, with direct developers expected to have much lower dispersal potential. However, this prediction can be complicated by the presence of geophysical barriers to dispersal. In this study, we use a panel of 8,020 SNPs to investigate population structure and biogeography over multiple spatial scales for a direct‐developing species, the New Zealand endemic marine isopod Isocladus armatus. Because our sampling range is intersected by two well‐known biogeographic barriers (the East Cape and the Cook Strait), our study provides an opportunity to understand how such barriers influence dispersal in direct developers. On a small spatial scale (20 km), gene flow between locations is extremely high, suggestive of an island model of migration. However, over larger spatial scales (600 km), populations exhibit a clear pattern of isolation‐by‐distance. Our results indicate that I. armatus exhibits significant migration across the hypothesized barriers and suggest that large‐scale ocean currents associated with these locations do not present a barrier to dispersal. Interestingly, we find evidence of a north‐south population genetic break occurring between Māhia and Wellington. While no known geophysical barrier is apparent in this area, it coincides with the location of a proposed border between bioregions. Analysis of loci under selection revealed that both isolation‐by‐distance and adaption may be contributing to the degree of population structure we have observed here. We conclude that developmental life history largely predicts dispersal in the intertidal isopod I. armatus. However, localized biogeographic processes can disrupt this expectation, and this may explain the potential meta‐population detected in the Auckland region.     

Risky movements? Natal dispersal does not decrease survival of a large herbivore

Natal dispersal is assumed to be a particularly risky movement behavior as individuals transfer, often long distances, from birth site to site of potential first reproduction. Though, because this behavior persists in populations, it is assumed that dispersal increases the fitness of individuals despite the potential for increased risk of mortality. The extent of dispersal risk, however, has rarely been tested, especially for large mammals. Therefore, we aimed to test the relationship between dispersal and survival for both males and females in a large herbivore. Using a radio‐transmittered sample of 398 juvenile male and 276 juvenile female white‐tailed deer (Odocoileus virginianus), we compared survival rates of dispersers and nondispersers. We predicted that dispersing deer would experience greater overall mortality than philopatric deer due to direct transfer‐related risks (e.g., vehicular collision), indirect immigration‐related mortality attributable to colonization of unfamiliar habitat, and increased overwinter mortality associated with energetic costs of movement and unfamiliarity with recently colonized habitat. For both male and female yearlings, survival rates of dispersers (male = 49.9%, female = 64.0%) did not differ from nondispersers (male = 51.6%, female = 70.7%). Only two individuals (both female) were killed by vehicular collision during transfer, and overwinter survival patterns were similar between the two groups. Although dispersal movement likely incurs energetic costs on dispersers, these costs do not necessarily translate to decreased survival. In many species, including white‐tailed deer, dispersal is likely condition‐dependent, such that larger and healthier individuals are more likely to disperse; therefore, costs associated with dispersal are more likely to be borne successfully by those individuals that do disperse. Whether low‐risk dispersal of large mammals is the rule or the exception will require additional research. Further, future research is needed to evaluate nonsurvival fitness‐related costs and benefits of dispersal (e.g., increased reproductive opportunities for dispersers).     

Classifying behavior from short‐interval biologging data: An example with GPS tracking of birds

1. Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.
2. We apply a framework for using K‐means clustering to classify bird behavior using points from short time interval GPS tracks. K‐means clustering is a well‐known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K‐means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free‐flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life‐stage‐ and age‐related variation in behavior.
3. After filtering for data quality, the K‐means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non‐moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.
4. The K‐means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short‐interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high‐dimensional movement data, it provides insight into small‐scale variation in behavior that would not be possible with many other analytical approaches.

     

Individual‐level leaf trait variation and correlation across biological and spatial scales

Even with increasing interest in the ecological importance of intraspecific trait variation (ITV) for better understanding ecological processes, few studies have quantified ITV in seedlings and assessed constraints imposed by trade‐offs and correlations among individual‐level leaf traits. Estimating the amount and role of ITV in seedlings is important to understand tree recruitment and long‐term forest dynamics. We measured ten different size, economics, and whole leaf traits (lamina and petiole) for more than 2,800 seedlings (height ≥ 10 cm and diameter at breast height < 1 cm) in 283 seedling plots and then quantified the amount of ITV and trait correlations across two biological (intraspecific and interspecific) and spatial (within and among plots) scales. Finally, we explored the effects of trait variance and sample size on the strength of trait correlations. We found about 40% (6%–63%) variation in leaf‐level traits was explained by ITV across all traits. Lamina and petiole traits were correlated across biological and spatial scales, whereas leaf size traits (e.g., lamina area) were weakly correlated with economics traits (e.g., specific lamina area); lamina mass ratio was strongly related to the petiole length. Trait correlations varied among species, plots, and different scales but there was no evidence that the strength of trait relationships was stronger at broader than finer biological and spatial scales. While larger trait variance increased the strength of correlations, the sample size was the most important factor that was negatively related to the strength of trait correlations. Our results showed that a large amount of trait variation was explained by ITV, which highlighted the importance of considering ITV when using trait‐based approaches in seedling ecology. In addition, sample size was an important factor that influenced the strength of trait correlations, which suggests that comparing trait correlations across studies should consider the differences in sample size.     

TMPRSS2 expression dictates the entry route used by SARS‐CoV‐2 to infect host cells

SARS‐CoV‐2 is a newly emerged coronavirus that caused the global COVID‐19 outbreak in early 2020. COVID‐19 is primarily associated with lung injury, but many other clinical symptoms such as loss of smell and taste demonstrated broad tissue tropism of the virus. Early SARS‐CoV‐2–host cell interactions and entry mechanisms remain poorly understood. Investigating SARS‐CoV‐2 infection in tissue culture, we found that the protease TMPRSS2 determines the entry pathway used by the virus. In the presence of TMPRSS2, the proteolytic process of SARS‐CoV‐2 was completed at the plasma membrane, and the virus rapidly entered the cells within 10 min in a pH‐independent manner. When target cells lacked TMPRSS2 expression, the virus was endocytosed and sorted into endolysosomes, from which SARS‐CoV‐2 entered the cytosol via acid‐activated cathepsin L protease 40–60 min post‐infection. Overexpression of TMPRSS2 in non‐TMPRSS2 expressing cells abolished the dependence of infection on the cathepsin L pathway and restored sensitivity to the TMPRSS2 inhibitors. Together, our results indicate that SARS‐CoV‐2 infects cells through distinct, mutually exclusive entry routes and highlight the importance of TMPRSS2 for SARS‐CoV‐2 sorting into either pathway.