Abstract Predicting the outcome of species or pathogen strain competition is a fundamental aim in both community ecology and infectious disease dynamics. Recent work revealed major challenges in predicting strain co-circulation from ecological coexistence theory due to overcompensatory competition among pathogens for susceptible resources, which can prevent the re-invasion of other competing strains. This resource overcompensation is ubiquitous across host-pathogen systems, but not apparent in simple Lotka-Volterra competition system, highlighting fundamental differences between pathogen strain and species competition. To address this gap, we begin by deriving classical models of pathogen strain and species competition from a resource-consumer model. This generalization illustrates that the relative time scale between resource and consumer dynamics limits the degree of resource overcompensation and therefore dictates the outcome of stochastic competition. Moreover, by introducing a mathematical framework for quantifying pairwise and higher-order terms from general competition systems, we show that a simple, ecological competition model can accurately predict the equilibrium dynamics of strain competition. A case study of rotavirus strain competition reveals that the ability to predict the outcome of strain competition from ecological theory depends on the underlying cross immunity structure. This work synthesizes coexistence theory across two fields by providing a unifying framework for predicting the outcome of complex ecological competition.

Pigmentation has been widely studied by evolutionary biologists due to both ease of measure and relationship to fitness. Drosophila melanogaster pigmentation has represented a particularly useful avenue of investigation, as extensive genetic tools have enabled the characterization of the trait's complex architecture. Drosophila pigmentation also varies predictably across space and time in wild populations, suggesting pigmentation is a component of adaptation to local environmental conditions. Despite this, the impact of D. melanogaster pigmentation on fitness, and the environmental factors that drive the evolution of pigmentation, are not well understood. To address this gap, we experimentally evolved replicated D. melanogaster populations in field mesocosms to determine whether and how pigmentation evolves in response to environmental variation. We found that pigmentation rapidly and predictably adapted to a direct manipulation of temperature, supportive of melanization playing a role in thermoregulation. However, we also determined that pigmentation responded adaptively to direct manipulations of numerous additional factors, including intraspecific competition, diet, and the microbiome. These findings suggest that the selective landscape acting on pigmentation is complex and multifaceted, and that patterns of melanization may be driven, at least in part, by indirect selection due to correlations with other fitness-related traits.

Ecological communities frequently exhibit remarkable taxonomic and trait diversity, and this diversity is consistently shown to regulate ecosystem function and resilience. However, ecologists lack a synthetic theory for how this diversity is maintained when species compete for limited resources, hampering our ability to project the future of biodiversity under climate change. Water-limited plant communities are an ideal system in which to study these questions given (1) the diversity of hydraulic traits they exhibit, (2) the importance of this diversity for ecosystem productivity and drought resilience, and (3) forecast changes to precipitation and evapotranspiration under climate change. We developed an analytically tractable model of water and light competition in age-structured perennial plant communities and demonstrated that high diversity is maintained through phenological division of the time between storms. We modeled a system where water arrives in the form of intermittent storms, between which plants consume the limited pool of soil water until it becomes dry enough that they must physiologically shut down to avoid embolism. Competition occurs because individuals, by consuming the shared water pool, cause their competitors to shut down earlier, harming their long-term growth and reproduction. When total precipitation is low, plants in the model compete only for water. However, increases in precipitation can cause the canopy to close and individuals to begin competing for light. Variation among species in the minimum soil water content at which they can sustain growth without embolizing leads to emergent phenological variation, as species will shut down at varying points between storm events. When this variation is paired with a trade-off such that species that shut down early are compensated by faster biomass accumulation, higher fecundity, or lower mortality, there is no limit to the number that can coexist. These results are robust to variation in both total precipitation and the time between storms. The model therefore offers a plausible explanation for how hydraulic trait diversity is maintained in a wide array of natural systems. More broadly, this work illustrates how the phenological division of an apparently singular resource can emerge because of common trade-offs and ultimately foster high taxonomic and trait diversity.

Abstract Our ecological understanding of how biodiversity will respond to global change is to a large extent based on projections from presence‐only species distribution models. Despite the incredible utility of these models, we know that the predictions they generate can be heavily influenced by user decisions about model structure or parameter choices. Here, we test how the function used to convert relative suitability to probably of occurrence in presence‐only species distributions models can affect predictions of both the magnitude and location of biodiversity change. We used MaxEnt models to create maps of relative suitability for 354 avian species under both current climate conditions and climate conditions in the year 1981. In a back‐casting analysis we tested how well three functions relating relative suitability to probably of occurrence perform in recovering observed changes in range size: (1) a logistic curve with informed, species‐specific, prevalence values, (2) the default logistic curve, or (3) a commonly used statistical threshold. We then quantified the implications of these functions for projections of species' future range shifts with climate change. We found that using either the default logistic function or a common threshold function for habitat suitability tends to (1) estimate larger effects of past climate change on species range size than observed in the time‐series data, (2) inflate projections of how much future climate change will impact species range size and (3) potentially misidentify the locations of greatest range expansion or contraction. We further provide a mathematical basis for these biases, suggesting their general applicability to other systems. Last, we show that these biases can be avoided by analysing proportional rather than absolute changes in range with climate change, and by abandoning the use of habitat suitability thresholds. Incorporating these practices can facilitate a more predictive use of species distribution models when forecasting the response of biodiversity to global change.

Understanding the anatomical and genetic basis of complex phenotypic traits has long been a challenge for biological research. Domestic dogs offer a compelling model as they demonstrate more phenotypic variation than any other vertebrate species. Dogs have been intensely selected for specific traits and abilities, directly or indirectly, over the past 15,000 years since their initial domestication from the gray wolf. Because olfaction plays a central role in critical tasks, such as the detection of drugs, diseases, and explosives, as well as human rescue, we compared relative olfactory capacity across dog breeds and assessed changes to the canine olfactory system to their direct ancestors, wolves, and coyotes. We conducted a cross-disciplinary survey of olfactory anatomy, olfactory receptor (OR) gene variation, and OR gene expression in domestic dogs. Through comparisons to their closest wild canid relatives, the gray wolf and coyote, we show that domestic dogs might have lost functional OR genes commensurate with a documented reduction in nasal morphology as an outcome of the domestication process prior to breed formation. Critically, within domestic dogs alone, we found no genetic or morphological profile shared among functional or genealogical breed groupings, such as scent hounds, that might indicate evidence of any human-directed selection for enhanced olfaction. Instead, our results suggest that superior scent detection dogs likely owe their success to advantageous behavioral traits and training rather than an "olfactory edge" provided by morphology or genes.

The competitive effect of one individual on another can have impacts beyond just reductions in performance. Because species plastically respond to their environment, competition can also induce changes in species traits, and in turn, these modified traits can then affect interactions with yet other individuals. In this context, plasticity is often argued to favor species coexistence by increasing the niche differentiation between species, though experimental evidence for this hypothesis that explicitly projects competitive outcomes is largely lacking. Here, we transiently subjected four annual plant species to early-season intraspecific or interspecific competition to explicitly induce plastic responses and then examined the response of these individuals to competitors faced later in life. Competing with nearby individuals early in the growing season tended to amplify the sensitivity of individuals to competition, and particularly so for interspecific competition, but the strength of this effect depended on the identity of the focal species. This increase in interspecific relative to intraspecific competition caused plasticity to decrease the predicted likelihood of pairwise coexistence. By combining recent theory with a new experimental approach, we provide a pathway toward integrating phenotypic plasticity into our quantitative understanding of coexistence.

Pathways to achieving net zero carbon emissions commonly involve deploying reforestation, afforestation, and bioenergy crops across millions of hectares of land. It is often assumed that by helping to mitigate climate change, these strategies indirectly benefit biodiversity. Here, we modeled the climate and habitat requirements of 14,234 vertebrate species and show that the impact of these strategies on species’ habitat area tends not to arise through climate mitigation, but rather through habitat conversion. Across locations, reforestation tends to provide species more habitat through both land-cover change and climate mitigation, whereas habitat loss from afforestation and bioenergy cropping typically outweighs the climate mitigation benefits. This work shows how and where land-based mitigation strategies can be deployed without inadvertently reducing the area of habitat for global biodiversity.

Spatial patterns are widespread in ecology, but their effects on species interactions remain unresolved, especially in diverse communities. In principle, the degree of spatial clustering could alter the concentration of higher-order interactions, which occur when one (or more) species modifies competition between two others. When species are well mixed, heterospecific neighbors have ample opportunity to modify a competitor’s interactions with other species. In contrast, species clustering can reduce the concentration of interspecific higher-order interactions. In a field experiment with annual grassland plants in California, we manipulated the spatial arrangement — but not the number or identity — of two competitors and measured how they jointly affected a focal individual. We found that focal plants produced more seeds when their competitors were clustered than when they were mixed. These results suggest that interspecific higher-order interactions generally had a stronger competitive (or weaker facilitative) effect than intraspecific ones. However, the effect of clustering varied across species. Larger differences in focal fecundity were correlated with competitors that had greater differences in size and/or functional traits between the spatial arrangements. Additionally, a competitive hierarchy among our study species predicted the effects of clustered versus mixed competitors on focal seed production. Altogether, our work suggests that the spatial arrangement of competitors changes the realized strength of competition in diverse plant communities by modifying the concentration of higher-order interactions. Given the extensive variation in spatial aggregation in plant communities, this mechanism is likely to be a powerful but underappreciated force shaping competition in nature. Significance Statement Plant species coexist in remarkably diverse assemblages throughout the world. Spatial patterns, including aggregation and intermixing, are also widespread in these communities. One potentially underappreciated mechanism that may structure the spatial dynamics of plant communities is interactions that uniquely occur in diverse systems, often called higher-order interactions. Here, we experimentally demonstrated that spatially mediated higher-order interactions operate among annual plants. These higher-order interactions, and their associated changes in competitor size and functional traits, were correlated with the competitive imbalance between competitors. Because both spatial aggregation and competitive hierarchies are widespread in nature, higher-order interactions emerging from their combination may be a more common driver of biodiversity patterns in plant communities than previously thought. ### Competing Interest Statement The authors have declared no competing interest. National Science Foundation, https://ror.org/021nxhr62, DGE-2444107, DEB-2022213, DEB-2022810 High Meadows Environmental Institute at Princeton University through the Mary and Randall Hack ‘69 Research Fund

Observations of pathogen community structure provide evidence for both the coexistence and replacement of related strains. Despite many studies of specific host-pathogen systems, a unifying framework for predicting the outcomes of interactions among pathogens has remained elusive. We address this gap by developing a pathogen invasion theory (PIT) based on modern ecological coexistence theory and testing the resulting framework against empirical systems. Across major human pathogens, PIT predicts near-universal mutual susceptibility of one strain to invasion by another strain. However, predicting co-circulation from mutual invasion also depends on the degree to which susceptible abundance is reduced below the invasion threshold by overcompensatory epidemic dynamics, and the time it takes for susceptibles to replenish. The transmission advantage of an invading strain and the strength and duration of immunity are key determinants of susceptible dynamics. PIT unifies existing ideas about pathogen co-circulation, offering a quantitative framework for predicting the emergence of novel pathogen strains.

Land-based mitigation strategies (LBMS) are critical to reducing climate change and will require large areas for their implementation. Yet few studies have considered how and where LBMS compete for land or are mutually compatible across Earth’s surface. We derived high resolution estimates of the spatial distribution of 19 different LBMS. We estimated 8.9 billion ha suitable for LBMS across the Earth, including 5.6 Bha suitable for only one of the studied strategies and 3.3 Bha suitable for multiple LBMS. We identified significant conflicts between better carbon management of existing land cover types, and restoration-based strategies such as reforestation. At the same time, several agricultural management LBMS were compatible over large areas, including for example, enhanced weathering and improved plantation rotations. Our analysis presents local stakeholders, communities, and governments with the range of LBMS options, and the opportunity costs associated with scaling up any given LBMS to reduce global climate change.### Competing Interest StatementThe authors have declared no competing interest.

Understanding how diversity is maintained in plant communities requires that we first understand the mechanisms of competition for limiting resources. In ecology, there is an underappreciated, but fundamental distinction between systems in which the depletion of limiting resources reduces the growth rates of competitors versus systems in which resource depletion reduces the time available for competitors to grow, a mechanism we call “competition for time.” Importantly, modern community ecology, and our framing of the coexistence problem are built on the implicit assumption that competition reduces the growth rate. However, recent theoretical work suggests competition for time may be the predominant competitive mechanism in a broad array of natural communities, a significant advance given coexistence follows naturally when species compete for time. In this study we first introduce competition for time conceptually using a simple model of interacting species. Then, we perform an experiment in a Mediterranean annual grassland to determine whether competition for time is an important competitive mechanism in a field system. Indeed, we find that species respond to increased competition through reductions in their lifespan rather than their rate of growth. In total, our study suggests competition for time may be overlooked as a mechanism of biodiversity maintenance.

Land-based mitigation strategies (LBMS) are critical to reducing climate change and will require large areas for their implementation. Yet few studies have considered how and where LBMS either compete for land or could be deployed jointly across the Earth's surface. To assess the opportunity costs of scaling up LBMS, we derived high-resolution estimates of the land suitable for 19 different LBMS, including ecosystem maintenance, ecosystem restoration, carbon-smart agricultural and forestry management, and converting land to novel states. Each 1 km resolution map was derived using the Earth's current geographic and biophysical features without socioeconomic constraints. By overlaying these maps, we estimated 8.56 billion hectares theoretically suitable for LBMS across the Earth. This includes 5.20 Bha where only one of the studied strategies is suitable, typically the strategy that involves maintaining the current ecosystem and the carbon it stores. The other 3.36 Bha is suitable for more than one LBMS, framing the choices society has among which LBMS to implement. The majority of these regions of overlapping LBMS include strategies that conflict with one another, such as the conflict between better management of existing land cover types and restoration-based strategies such as reforestation. At the same time, we identified several agricultural management LBMS that were geographically compatible over large areas, including for example, enhanced chemical weathering and improved plantation rotations. Our analysis presents local stakeholders, communities, and governments with the range of LBMS options, and the opportunity costs associated with scaling up any given LBMS to reduce global climate change.

How terrestrial ecosystems will accumulate carbon as the climate continues to change is a major source of uncertainty in projections of future climate. Under growth-stimulating environmental change, time lags inherent in population and community dynamic processes have been posed to dampen, or alternatively amplify, short-term carbon gain in terrestrial vegetation, but these outcomes can be difficult to predict. To theoretically frame this problem, we developed a simple model of vegetation dynamics that identifies the stage-structured demographic and competitive processes that could govern the timescales of carbon storage and loss. We show that demographic lags associated with growth-stimulating environmental change can allow a rapid increase in population-level carbon storage that is lost back to the atmosphere in later years. However, this transient carbon storage only emerges when environmental change increases the transition of adult individuals into a larger size class that suffers markedly higher mortality. Otherwise, demographic lags simply slow carbon accumulation. Counterintuitively, an analogous tradeoff between maximum adult size and survivorship in two-species models, coupled with environmental change-driven replacement, does not generate the transient carbon gain seen in the single-species models. Instead lags in competitive replacement slow the approach to the eventual carbon trajectory. Together, our results suggest that time lags inherent in demographic and compositional turnover tend to slow carbon accumulation in systems responding to growth-stimulating environmental change. Only under specific conditions will lagged demographic processes in such systems drive transient carbon accumulation, conditions that investigators can examine in nature to help project future carbon trajectories.

Most ecological models are based on the assumption that species interact in pairs. Diverse communities, however, can have higher-order interactions, in which two or more species jointly impact the growth of a third species. A pitfall of the common pairwise approach is that it misses the higher-order interactions potentially responsible for maintaining natural diversity. Here, we explore the stability properties of systems where higher-order interactions guarantee that a specified set of abundances is a feasible equilibrium of the dynamics. Even these higher-order interactions which lead to equilibria do not necessarily produce stable coexistence. Instead, these systems are more likely to be stable when the pairwise interactions are weak or facilitative. Correlations between the pairwise and higher-order interactions, however, do permit robust coexistence even in diverse systems. Our work not only reveals the challenges in generating stable coexistence through higher-order interactions but also uncovers interaction patterns that can enable diversity.

Species can modify their traits in response to changes in the environment – a process known as phenotypic plasticity. Because species traits can plastically respond to competition, the competitive effect of one individual on another involves not only reductions in performance, but also changes in morphology, behavior, phenology or physiology that affect interactions with other individuals. In this context, plasticity is often argued to favor species coexistence by increasing the niche differentiation between species, though experimental support that explicitly considers competitive outcomes is largely lacking. Here, we transiently subjected four annual plant species to early-season intraspecific or interspecific competition to explicitly induce plastic responses, and then examined the response of these individuals to other competitors. By measuring the interactions between the species with and without early-season competitors, we isolated the impact of plasticity on species interactions and coexistence. Growing with nearby competitors early in life impacted plant traits including height and morphology. These plastic responses tended to amplify the sensitivity of individuals to competition, and particularly so for interspecific competition. This increase in inter-relative to intraspecific competition caused plasticity to decrease the predicted likelihood of pairwise coexistence. By combining recent theory with a new experimental approach, we provide a pathway towards integrating phenotypic plasticity into our quantitative understanding of coexistence. ### Competing Interest Statement The authors have declared no competing interest.

The rationale behind trait-based ecology is that shifting focus from species’ taxonomic names to their measurable characteristics (‘functional traits’) leads to greater generality and predictive power. This idea has been applied to one of ecology’s most intractable problems: the coexistence of competing species. But after 20 years, we lack clear evidence that functional traits effectively predict coexistence. Here, we present a theory-based argument for why this might be the case. Specifically, we argue that coexistence often depends on special quantities called ‘process-informed metrics’ (PIMs), which combine multiple traits and demographic characteristics in non-intuitive ways, obscuring any direct ties between individual traits and coexistence. We then lay a path forward for trait-based coexistence research that builds on mechanistic models of competition.

The complexity of ecosystems poses a formidable challenge for confidently invalidating ecological models, as current practices struggle to distinguish model inadequacies from the confounding effects of unobserved biotic or abiotic factors. The prevailing inability to falsify models has resulted in an accumulation of models but not an accumulation of confidence. Here, we introduce a new approach rooted in queueing theory, termed the covariance criteria, that establishes a rigorous test for model validity based on covariance relationships between observable quantities. These criteria set a high bar for models to pass by specifying necessary conditions that must hold regardless of unobserved factors. We demonstrate the broad applicability and discriminatory power of the covariance criteria by applying them to three long-standing challenges in ecological theory: resolving competing models of predator-prey functional responses, disentangling ecological and evolutionary dynamics in systems with rapid evolution, and detecting the often-elusive influence of higher-order species interactions. Across these diverse case studies, the covariance criteria consistently rule out inadequate models, while building strong confidence in those that provide strategically useful approximations. The covariance criteria approach is mathematically rigorous, computationally efficient, and often non-parametric, making it immediately applicable to existing data and models. ### Competing Interest Statement The authors have declared no competing interest.

The "claw sign" is a radiographic sign studied in human imaging to determine if a mass arises from a solid structure or organ versus a close adjacent location, resulting in distortion of the outline of an organ. We investigated its utility in characterizing MRI axial localization of peripherally located intracranial glioma versus meningioma, due to their overlap in MRI appearance. This retrospective, secondary analysis, cross-sectional study aimed to report the sensitivity, specificity, and inter- and intraobserver variabilities using kappa statistics, hypothesizing that the claw sign will have strong inter- and intraobserver agreement (κ > 0.8). Dogs with a histologically confirmed diagnosis of peripherally located glioma or meningioma and available 3T MRI data were retrieved from medical record archives from 2009 to 2021. A total of 27 cases, 11 glioma and 16 meningioma, were included. The postcontrast T1-weighted images were provided to five blinded image evaluators in two separate randomized sessions separated by a 6-week wash out period. Prior to the first evaluation, evaluators were provided with a training video and set of training cases for the "claw sign," which were excluded from the study. Evaluators were asked to rate cases as "positive," "negative," or "indeterminate" for the "claw sign." The sensitivity and specificity for the "claw sign" for the first session were 85.5% and 80%, respectively. The interobserver agreement for identifying the "claw sign" was moderate (κ = 0.48), and the intraobserver agreement across the two sessions was substantial (κ = 0.72). These findings indicate the claw sign is supportive but not pathognomonic for intra-axial localization in cases of canine glioma on MRI.