Progressing beyond colonization strategies to understand arbuscular mycorrhizal fungal life history.

Knowledge of differential life-history strategies in arbuscular mycorrhizal (AM) fungi is relevant for understanding the ecology of this group and its potential role in sustainable agriculture and carbon sequestration. At present, AM fungal life-history theories often focus on differential investment into intra- vs extraradical structures among AM fungal taxa, and its implications for plant benefits. With this Viewpoint we aim to expand these theories by integrating a mycocentric economics- and resource-based life-history framework. As in plants, AM fungal carbon and nutrient demands are stoichiometrically coupled, though uptake of these elements is spatially decoupled. Consequently, investment in morphological structures for carbon vs nutrient uptake is not in competition. We argue that understanding the ecology and evolution of AM fungal life-history trade-offs requires increased focus on variation among structures foraging for the same element, that is within intra- or extraradical structures (in our view a 'horizontal' axis), not just between them ('vertical' axis). Here, we elaborate on this argument and propose a range of plausible life-history trade-offs that could lead to the evolution of strategies in AM fungi, providing testable hypotheses and creating opportunities to explain AM fungal co-existence, and the context-dependent effects of AM fungi on plant growth and soil carbon dynamics.

Incorporating citizen science into IUCN Red List assessments.

Many citizen scientists are highly motivated to help address the current extinction crisis. Their work is making valuable contributions to protecting species by raising awareness, identifying species occurrences, assessing population trends, and informing direct management actions, such as captive breeding. However, clear guidance is lacking about how to use existing citizen science data sets and how to design effective citizen science programs that directly inform extinction risk assessments and resulting conservation actions based on the International Union for Conservation of Nature (IUCN) Red List criteria. This may be because of a mismatch between what citizen science can deliver to address extinction risk and the reality of what is needed to inform threatened species listing based on IUCN criteria. To overcome this problem, we examined each IUCN Red List criterion (A-E) relative to the five major types of citizen science outputs relevant to IUCN assessments (occurrence data, presence-absence observations, structured surveys, physical samples, and narratives) to recommend which outputs are most suited to use when applying the IUCN extinction risk assessment process. We explored real-world examples of citizen science projects on amphibians and fungi that have delivered valuable data and knowledge for IUCN assessments. We found that although occurrence data are routinely used in the assessment process, simply adding more observations of occurrence from citizen science information may not be as valuable as inclusion of more nuanced data types, such as presence-absence data or information on threats from structured surveys. We then explored the characteristics of citizen science projects that have already delivered valuable data to support assessments. These projects were led by recognized experts who champion and validate citizen science data, thereby giving greater confidence in its accuracy. We urge increased recognition of the value of citizen science data within the assessment process.

Integración de la ciencia ciudadana a las evaluaciones de la Lista Roja de la UICN Resumen Existe mucha motivación entre los ciudadanos científicos para ayudar a enfrentar la actual crisis de extinción. Sus contribuciones son valiosas para la protección de las especies mediante la concientización, la detección de especies, la evaluación de las tendencias poblacionales y la información sobre acciones directas de gestión, como la cría en cautiverio. Sin embargo, faltan directrices claras sobre cómo utilizar los conjuntos de datos de ciencia ciudadana existentes y cómo diseñar programas de ciencia ciudadana eficaces que informen directamente las evaluaciones del riesgo de extinción y las acciones de conservación resultantes basadas en los criterios de la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN). Esto puede deberse a un desajuste entre lo que la ciencia ciudadana puede aportar para abordar el riesgo de extinción y la realidad de lo que se necesita para fundamentar la inclusión de especies amenazadas en las listas según los criterios de la UICN. Para superar este obstáculo, analizamos cada criterio de la Lista Roja de la UICN (A­E) en relación a los cinco tipos principales de resultados de la ciencia ciudadana relevantes para las evaluaciones de la UICN (datos de presencia, observaciones de presencia­ausencia, encuestas estructuradas, muestras físicas y narraciones) para recomendar cuáles resultados son los más adecuados para la evaluación del riesgo de extinción de la UICN. Exploramos ejemplos reales de proyectos de ciencia ciudadana sobre anfibios y hongos que han aportado datos y conocimientos valiosos para las evaluaciones de la UICN. Descubrimos que, aunque los datos de presencia se utilizan de forma rutinaria en el proceso de evaluación, la adición de más observaciones de presencia a partir de información de ciencia ciudadana puede no ser tan valioso como la inclusión de tipos de datos más matizados, como datos de presencia­ausencia o información sobre amenazas a partir de encuestas estructuradas. Después analizamos las características de los proyectos de ciencia ciudadana que ya han aportado datos valiosos en apoyo de las evaluaciones. Estos proyectos fueron dirigidos por expertos reconocidos que defienden y validan los datos de la ciencia ciudadana, lo que da mayor confianza en su exactitud. Instamos a un mayor reconocimiento del valor de los datos de la ciencia ciudadana en el proceso de evaluación.

Multi-taxon biodiversity responses to the 2019-2020 Australian megafires.

Conditions conducive to fires are becoming increasingly common and widespread under climate change. Recent fire events across the globe have occurred over unprecedented scales, affecting a diverse array of species and habitats. Understanding biodiversity responses to such fires is critical for conservation. Quantifying post-fire recovery is problematic across taxa, from insects to plants to vertebrates, especially at large geographic scales. Novel datasets can address this challenge. We use presence-only citizen science data from iNaturalist, collected before and after the 2019-2020 megafires in burnt and unburnt regions of eastern Australia, to quantify the effect of post-fire diversity responses, up to 18 months post-fire. The geographic, temporal, and taxonomic sampling of this dataset was large, but sampling effort and species discoverability were unevenly spread. We used rarefaction and prediction (iNEXT) with which we controlled sampling completeness among treatments, to estimate diversity indices (Hill numbers: q = 0-2) among nine broad taxon groupings and seven habitats, including 3885 species. We estimated an increase in species diversity up to 18 months after the 2019-2020 Australian megafires in regions which were burnt, compared to before the fires in burnt and unburnt regions. Diversity estimates in dry sclerophyll forest matched and likely drove this overall increase post-fire, while no taxon groupings showed clear increases inconsistent with both control treatments post-fire. Compared to unburnt regions, overall diversity across all taxon groupings and habitats greatly decreased in areas exposed to extreme fire severity. Post-fire life histories are complex and species detectability is an important consideration in all post-fire sampling. We demonstrate how fire characteristics, distinct taxa, and habitat influence biodiversity, as seen in local-scale datasets. Further integration of large-scale datasets with small-scale studies will lead to a more robust understanding of fire recovery.

Insect pollination for most of angiosperm evolutionary history.

Most contemporary angiosperms (flowering plants) are insect pollinated, but pollination by wind, water or vertebrates occurs in many lineages. Though evidence suggests insect pollination may be ancestral in angiosperms, this is yet to be assessed across the full phylogeny. Here, we reconstruct the ancestral pollination mode of angiosperms and quantify the timing and environmental associations of pollination shifts. We use a robust, dated phylogeny and species-level sampling across all angiosperm families to model the evolution of pollination modes. Data on the pollination system or syndrome of 1160 species were collated from the primary literature. Angiosperms were ancestrally insect pollinated, and insects have pollinated angiosperms for c. 86% of angiosperm evolutionary history. Wind pollination evolved at least 42 times, with few reversals to animal pollination. Transitions between insect and vertebrate pollination were more frequent: vertebrate pollination evolved at least 39 times from an insect-pollinated ancestor with at least 26 reversals. The probability of wind pollination increases with habitat openness (measured by Leaf Area Index) and distance from the equator. Our reconstruction gives a clear overview of pollination macroevolution across angiosperms, highlighting the long history of interactions between insect pollinators and angiosperms still vital to biodiversity today.

Quantifying research interests in 7,521 mammalian species with h-index: a case study.

BACKGROUND: Taxonomic bias is a known issue within the field of biology, causing scientific knowledge to be unevenly distributed across species. However, a systematic quantification of the research interest that the scientific community has allocated to individual species remains a big data problem. Scalable approaches are needed to integrate biodiversity data sets and bibliometric methods across large numbers of species. The outputs of these analyses are important for identifying understudied species and directing future research to fill these gaps. FINDINGS: In this study, we used the species h-index to quantity the research interest in 7,521 species of mammals. We tested factors potentially driving species h-index, by using a Bayesian phylogenetic generalized linear mixed model (GLMM). We found that a third of the mammals had a species h-index of zero, while a select few had inflated research interest. Further, mammals with higher species h-index had larger body masses; were found in temperate latitudes; had their humans uses documented, including domestication; and were in lower-risk International Union for Conservation of Nature Red List categories. These results surprisingly suggested that critically endangered mammals are understudied. A higher interest in domesticated species suggested that human use is a major driver and focus in mammalian scientific literature. CONCLUSIONS: Our study has demonstrated a scalable workflow and systematically identified understudied species of mammals, as well as identified the likely drivers of this taxonomic bias in the literature. This case study can become a benchmark for future research that asks similar biological and meta-research questions for other taxa.

Lichens buffer tundra microclimate more than the expanding shrub Betula nana.

BACKGROUND AND AIMS: In tundra systems, soil-borne lichens are often the dominant groundcover organisms, and act to buffer microclimate extremes within or at the surface of the soil. However, shrubs are currently expanding across tundra systems, potentially causing major shifts in the microclimate landscape. METHODS: Here, we compared soil temperature and moisture underneath the dwarf birch Betula nana and seven abundant lichen species in sub-alpine Norway. We also examined mixtures of lichens and dwarf birch - an intermediate phase of shrubification - and measured several functional traits relating to microclimate. KEY RESULTS: We found that all lichen species strongly buffered the daily temperature range, on average reducing maximum temperatures by 6.9 °C (± 0.7 s.d.) and increasing minimum temperatures by 1.0 °C (± 0.2 s.d.) during summer. The dwarf birch had a much weaker effect (maximum reduced by 2.4 ±â€…5.0 °C and minimum raised by 0.2 ± 0.9 °C). In species mixtures, the lichen effect predominated, affecting temperature extremes by more than would be expected from their abundance. Lichens also tended to reduce soil moisture, which could be explained by their ability to intercept rainfall. Our trait measurements under laboratory conditions suggest that, on average, lichens can completely absorb a 4.09 mm (± 1.81 s.d.) rainfall event, which might be an underappreciated part of lichen-vascular plant competition in areas where summer rainfall events are small. CONCLUSIONS: In the context of shrubification across tundra systems, our findings suggest that lichens will continue to have a large effect on microclimate until they are fully excluded, at which point microclimate extremes will increase greatly.

Sexual dimorphism in trait variability and its eco-evolutionary and statistical implications.

Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioural traits. Sex differences in trait variability, however, are yet to receive similar recognition. In medical science, mammalian females are assumed to have higher trait variability due to estrous cycles (the 'estrus-mediated variability hypothesis'); historically in biomedical research, females have been excluded for this reason. Contrastingly, evolutionary theory and associated data support the 'greater male variability hypothesis'. Here, we test these competing hypotheses in 218 traits measured in >26,900 mice, using meta-analysis methods. Neither hypothesis could universally explain patterns in trait variability. Sex bias in variability was trait-dependent. While greater male variability was found in morphological traits, females were much more variable in immunological traits. Sex-specific variability has eco-evolutionary ramifications, including sex-dependent responses to climate change, as well as statistical implications including power analysis considering sex difference in variance.

Males and females differ in appearance, physiology and behavior. But we do not fully understand the health and evolutionary consequences of these differences. One reason for this is that, until recently, females were often excluded from medical studies. This made it difficult to know if a treatment would perform as well in females as males. To correct this, organizations that fund research now require scientists to include both sexes in studies. This has led to some questions about how to account for sex differences in studies. One reason females have historically been excluded from medical studies is that some scientists assumed that they would have more variable responses to a particular treatment based on their estrous cycles. Other scientists, however, believe that males of a given species might be more variable because of the evolutionary pressures they face in competing for mates. Better understanding how males and females vary would help scientists better design studies to ensure they provide accurate answers. Now, Zajitschek et al. debunk both the idea that males are more variable and the idea that females are more variable. To do this, Zajitschek et al. analyzed differences in 218 traits, like body size or certain behaviors, among nearly 27,000 male and female mice. This showed that neither male mice nor female mice were universally more different from other mice of their sex across all features. Instead, sex differences in how much variation existed in male or female mice depended on the individual trait. For example, males varied more in physical features like size, while females showed more differences in their immune systems. The results suggest it is particularly important to consider sex-specific variability in both medical and other types of studies. To help other researchers better design experiments to factor in such variability, Zajitschek et al. created an interactive tool that will allow scientists to look at sex-based differences in individual features among male or female mice.

When and where soil is important to modify the carbon and water economy of leaves.

Photosynthetic 'least-cost' theory posits that the optimal trait combination for a given environment is that where the summed costs of photosynthetic water and nutrient acquisition/use are minimised. The effects of soil water and nutrient availability on photosynthesis should be stronger as climate-related costs for both resources increase. Two independent datasets of photosynthetic traits, Globamax (1509 species, 288 sites) and Glob13C (3645 species, 594 sites), were used to quantify biophysical and biochemical limitations of photosynthesis and the key variable Ci /Ca (CO2 drawdown during photosynthesis). Climate and soil variables were associated with both datasets. The biochemical photosynthetic capacity was higher on alkaline soils. This effect was strongest at more arid sites, where water unit-costs are presumably higher. Higher values of soil silt and depth increased Ci /Ca , likely by providing greater H2 O supply, alleviating biophysical photosynthetic limitation when soil water is scarce. Climate is important in controlling the optimal balance of H2 O and N costs for photosynthesis, but soil properties change these costs, both directly and indirectly. In total, soil properties modify the climate-demand driven predictions of Ci /Ca by up to 30% at a global scale.

Phylogenetic comparative methods.

Phylogenetic comparative methods (PCMs) enable us to study the history of organismal evolution and diversification. PCMs comprise a collection of statistical methods for inferring history from piecemeal information, primarily combining two types of data: first, an estimate of species relatedness, usually based on their genes, and second, contemporary trait values of extant organisms. Some PCMs also incorporate information from geological records, especially fossils, but also other gradual and episodic events in the Earth's history (for example, trait data from fossils or the global oxygen concentration as an independent variable). It is important to note at the outset that PCMs are not concerned with reconstructing the evolutionary relationships among species; this has to do with estimating the phylogeny from genetic, fossil and other data, and a separate set of methods for this process makes up the field of phylogenetics. PCMs as a set of methods are distinct from, but are not completely independent of, phylogenetics. PCMs are used to address the questions: how did the characteristics of organisms evolve through time and what factors influenced speciation and extinction?

The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change.

Species are the unit of analysis in many global change and conservation biology studies; however, species are not uniform entities but are composed of different, sometimes locally adapted, populations differing in plasticity. We examined how intraspecific variation in thermal niches and phenotypic plasticity will affect species distributions in a warming climate. We first developed a conceptual model linking plasticity and niche breadth, providing five alternative intraspecific scenarios that are consistent with existing literature. Secondly, we used ecological niche-modeling techniques to quantify the impact of each intraspecific scenario on the distribution of a virtual species across a geographically realistic setting. Finally, we performed an analogous modeling exercise using real data on the climatic niches of different tree provenances. We show that when population differentiation is accounted for and dispersal is restricted, forecasts of species range shifts under climate change are even more pessimistic than those using the conventional assumption of homogeneously high plasticity across a species' range. Suitable population-level data are not available for most species so identifying general patterns of population differentiation could fill this gap. However, the literature review revealed contrasting patterns among species, urging greater levels of integration among empirical, modeling and theoretical research on intraspecific phenotypic variation.