Ecosystem decay exacerbates biodiversity loss with habitat loss.

Although habitat loss is the predominant factor leading to biodiversity loss in the Anthropocene1,2, exactly how this loss manifests-and at which scales-remains a central debate3-6. The 'passive sampling' hypothesis suggests that species are lost in proportion to their abundance and distribution in the natural habitat7,8, whereas the 'ecosystem decay' hypothesis suggests that ecological processes change in smaller and more-isolated habitats such that more species are lost than would have been expected simply through loss of habitat alone9,10. Generalizable tests of these hypotheses have been limited by heterogeneous sampling designs and a narrow focus on estimates of species richness that are strongly dependent on scale. Here we analyse 123 studies of assemblage-level abundances of focal taxa taken from multiple habitat fragments of varying size to evaluate the influence of passive sampling and ecosystem decay on biodiversity loss. We found overall support for the ecosystem decay hypothesis. Across all studies, ecosystems and taxa, biodiversity estimates from smaller habitat fragments-when controlled for sampling effort-contain fewer individuals, fewer species and less-even communities than expected from a sample of larger fragments. However, the diversity loss due to ecosystem decay in some studies (for example, those in which habitat loss took place more than 100 years ago) was less than expected from the overall pattern, as a result of compositional turnover by species that were not originally present in the intact habitats. We conclude that the incorporation of non-passive effects of habitat loss on biodiversity change will improve biodiversity scenarios under future land use, and planning for habitat protection and restoration.

The potential of multispectral imaging flow cytometry for environmental monitoring.

Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.

Dissecting macroecological and macroevolutionary patterns of forest biodiversity across the Hawaiian archipelago.

Biodiversity patterns emerge as a consequence of evolutionary and ecological processes. Their relative importance is frequently tested on model ecosystems such as oceanic islands that vary in both. However, the coarse-scale data typically used in biogeographic studies have limited inferential power to separate the effects of historical biogeographic factors (e.g., island age) from the effects of ecological ones (e.g., island area and habitat heterogeneity). Here, we describe local-scale biodiversity patterns of woody plants using a database of more than 500 forest plots from across the Hawaiian archipelago, where these volcanic islands differ in age by several million years. We show that, after controlling for factors such as island area and heterogeneity, the oldest islands (Kaua'i and O'ahu) have greater native species diversity per unit area than younger islands (Maui and Hawai'i), indicating an important role for macroevolutionary processes in driving not just whole-island differences in species diversity, but also local community assembly. Further, we find that older islands have a greater number of rare species that are more spatially clumped (i.e., higher within-island ß-diversity) than younger islands. When we included alien species in our analyses, we found that the signal of macroevolutionary processes via island age was diluted. Our approach allows a more explicit test of the question of how macroevolutionary factors shape not just regional-scale biodiversity, but also local-scale community assembly patterns and processes in a model archipelago ecosystem, and it can be applied to disentangle biodiversity drivers in other systems.

Seeing through the static: the temporal dimension of plant-animal mutualistic interactions.

Most studies of plant-animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human-driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant-animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.

Pollen analysis using multispectral imaging flow cytometry and deep learning.

Pollen identification and quantification are crucial but challenging tasks in addressing a variety of evolutionary and ecological questions (pollination, paleobotany), but also for other fields of research (e.g. allergology, honey analysis or forensics). Researchers are exploring alternative methods to automate these tasks but, for several reasons, manual microscopy is still the gold standard. In this study, we present a new method for pollen analysis using multispectral imaging flow cytometry in combination with deep learning. We demonstrate that our method allows fast measurement while delivering high accuracy pollen identification. A dataset of 426 876 images depicting pollen from 35 plant species was used to train a convolutional neural network classifier. We found the best-performing classifier to yield a species-averaged accuracy of 96%. Even species that are difficult to differentiate using microscopy could be clearly separated. Our approach also allows a detailed determination of morphological pollen traits, such as size, symmetry or structure. Our phylogenetic analyses suggest phylogenetic conservatism in some of these traits. Given a comprehensive pollen reference database, we provide a powerful tool to be used in any pollen study with a need for rapid and accurate species identification, pollen grain quantification and trait extraction of recent pollen.

Lagged and dormant season climate better predict plant vital rates than climate during the growing season.

Understanding the effects of climate on the vital rates (e.g., survival, development, reproduction) and dynamics of natural populations is a long-standing quest in ecology, with ever-increasing relevance in the face of climate change. However, linking climate drivers to demographic processes requires identifying the appropriate time windows during which climate influences vital rates. Researchers often do not have access to the long-term data required to test a large number of windows, and are thus forced to make a priori choices. In this study, we first synthesize the literature to assess current a priori choices employed in studies performed on 104 plant species that link climate drivers with demographic responses. Second, we use a sliding-window approach to investigate which combination of climate drivers and temporal window have the best predictive ability for vital rates of four perennial plant species that each have over a decade of demographic data (Helianthella quinquenervis, Frasera speciosa, Cylindriopuntia imbricata, and Cryptantha flava). Our literature review shows that most studies consider time windows in only the year preceding the measurement of the vital rate(s) of interest, and focus on annual or growing season temporal scales. In contrast, our sliding-window analysis shows that in only four out of 13 vital rates the selected climate drivers have time windows that align with, or are similar to, the growing season. For many vital rates, the best window lagged more than 1 year and up to 4 years before the measurement of the vital rate. Our results demonstrate that for the vital rates of these four species, climate drivers that are lagged or outside of the growing season are the norm. Our study suggests that considering climatic predictors that fall outside of the most recent growing season will improve our understanding of how climate affects population dynamics.

Intraspecific trait variation and reversals of trait strategies across key climate gradients in native Hawaiian plants and non-native invaders.

BACKGROUND AND AIMS: Displacement of native plant species by non-native invaders may result from differences in their carbon economy, yet little is known regarding how variation in leaf traits influences native-invader dynamics across climate gradients. In Hawaii, one of the most heavily invaded biodiversity hotspots in the world, strong spatial variation in climate results from the complex topography, which underlies variation in traits that probably drives shifts in species interactions. METHODS: Using one of the most comprehensive trait data sets for Hawaii to date (91 species and four islands), we determined the extent and sources of variation (climate, species and species origin) in leaf traits, and used mixed models to examine differences between natives and non-native invasives. KEY RESULTS: We detected significant differences in trait means, such that invasives were more resource acquisitive than natives over most of the climate gradients. However, we also detected trait convergence and a rank reversal (natives more resource acquisitive than invasives) in a sub-set of conditions. There was significant intraspecific trait variation (ITV) in leaf traits of natives and invasives, although invasives expressed significantly greater ITV than natives in water loss and photosynthesis. Species accounted for more trait variation than did climate for invasives, while the reverse was true for natives. Incorporating this climate-driven trait variation significantly improved the fit of models that compared natives and invasives. Lastly, in invasives, ITV was most strongly explained by spatial heterogeneity in moisture, whereas solar energy explains more ITV in natives. CONCLUSIONS: Our results indicate that trait expression and ITV vary significantly between natives and invasives, and that this is mediated by climate. These findings suggest that although natives and invasives are functionally similar at the regional scale, invader success at local scales is contingent on climate.

The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis.

Approximately 25% of mammals are currently threatened with extinction, a risk that is amplified under climate change. Species persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development and reproduction), and hence, population dynamics. Thus, to quantify which species and regions on Earth are most vulnerable to climate-driven extinction, a global understanding of how different demographic rates respond to climate is urgently needed. Here, we perform a systematic review of literature on demographic responses to climate, focusing on terrestrial mammals, for which extensive demographic data are available. To assess the full spectrum of responses, we synthesize information from studies that quantitatively link climate to multiple demographic rates. We find only 106 such studies, corresponding to 87 mammal species. These 87 species constitute <1% of all terrestrial mammals. Our synthesis reveals a strong mismatch between the locations of demographic studies and the regions and taxa currently recognized as most vulnerable to climate change. Surprisingly, for most mammals and regions sensitive to climate change, holistic demographic responses to climate remain unknown. At the same time, we reveal that filling this knowledge gap is critical as the effects of climate change will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others, often depending on the specific environmental context, complicating simple projections of population fates. Assessments of population viability under climate change are in critical need to gather data that account for multiple demographic responses, and coordinated actions to assess demography holistically should be prioritized for mammals and other taxa.

Automated conservation assessment of the orchid family with deep learning.

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.

Evaluación Automatizada de la Conservación de la Familia Orchidaceae mediante Aprendizaje Profundo Resumen Los análisis de la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) son esenciales para la priorización de las necesidades de conservación, pero requieren de muchos recursos y por lo tanto están disponibles sólo para una fracción de la riqueza mundial de especies. Las evaluaciones automatizadas de la conservación basadas en los registros disponibles de presencia geográfica pueden ser una alternativa rápida pero no está claro cuán confiables son estas evaluaciones. Realizamos evaluaciones automatizadas de la conservación para 13,910 especies (47.3% de las especies conocidas de la familia) de la diversa y mundialmente distribuida familia de las orquídeas (Orchidaceae), en la cual la mayoría de las especies (13,049) no tenían una valoración previa por parte de la UICN. Usamos un método novedoso basado en una red neural profunda (IUC-NN). Identificamos 4,342 especies de orquídeas (31.2% de las especies evaluadas) como posiblemente amenazadas por la extinción (equivalente a las categorías de la UICN en peligro crítico [CR], en peligro [EN] o vulnerable [VU]) y a Madagascar, África Occidental, el sudeste de Asia y varias islas oceánicas como áreas prioritarias para la conservación de orquídeas. La familia Orchidaceae proporcionó un modelo con el cual probar la sensibilidad de los métodos de evaluación automatizada ante problemas con la disponibilidad de datos, la calidad de los datos y los sesgos de muestreo geográfico. La IUC-NN identificó posibles especies amenazadas con una certeza de 84.3% con un sesgo de evaluación geográfica significativamente más bajo en relación con la Lista Roja de la UICN y mostró solidez incluso cuando la disponibilidad de datos fue baja y hubo errores geográficos en los datos de entrada. En general, nuestros resultados demostraron que las evaluaciones automatizadas tienen un papel importante que desempeñar en la identificación de especies con mayor riesgo de extinción.

Areas Requiring Restoration Efforts are a Complementary Opportunity to Support the Demand for Pollination Services in Brazil.

Crop pollination is one of Nature's Contributions to People (NCP) that reconciles biodiversity conservation and agricultural production. NCP benefits vary across space, including among distinct political-administrative levels within nations. Moreover, initiatives to restore ecosystems may enhance NCP provision, such as crop pollination delivered by native pollinators. We mapped crop pollination demand (PD), diversity of pollinator-dependent crops, and vegetation deficit (VD) (vis-a-vis Brazilian legal requirements) across all 5570 municipalities in Brazil. Pollinator-dependent crops represented ∼55% of the annual monetary value of agricultural production and ∼15% of the annual crop production. Municipalities with greater crop PD (i.e., higher degree of pollinator dependence of crop production) also had greater VD, associated with large properties and monocultures. In contrast, municipalities with a greater diversity of pollinator-dependent crops and predominantly small properties presented a smaller VD. Our results support that ecological restoration prompted by legal requirements offers great potential to promote crop productivity in larger properties. Moreover, conservation of vegetation remnants could support food security in small properties. We provided the first steps to identify spatial patterns linking biodiversity conservation and pollination service. Using Brazilian legal requirements as an example, we show that land-use management policies may be successfully used to ensure agricultural sustainability and crop production.

Phylogenetic and functional distinctiveness explain alien plant population responses to competition.

Several invasion hypotheses predict a positive association between phylogenetic and functional distinctiveness of aliens and their performance, leading to the idea that distinct aliens compete less with their resident communities. However, synthetic pattern relationships between distinctiveness and alien performance and direct tests of competition as the driving mechanism have not been forthcoming. This is likely because different patterns are observed at different spatial grains, because functional trait and phylogenetic information are often incomplete, and because of the need for competition experiments that measure demographic responses across a variety of alien species that vary in their distinctiveness. We conduct a competitor removal experiment and parameterize matrix population and integral projection models for 14 alien plant species. More novel aliens compete less strongly with co-occurring species in their community, but these results dissipate at a larger spatial grain of investigation. Further, we find that functional traits used in conjunction with phylogeny improve our ability to explain competitive responses. Our investigation shows that competition is an important mechanism underlying the differential success of alien species.

We need more realistic climate change experiments for understanding ecosystems of the future.

Experiments that alter local climate and measure community- and ecosystem-level responses are an important tool for understanding how future ecosystems will respond to climate change. Here, we synthesized data from 76 studies that manipulated climate and measured plant community responses, and found that most climate change experiments do not correspond to model-projected climate scenarios for their respective regions. This mismatch constrains our ability to predict responses of plant biodiversity and ecosystem functions to climate change, and we conclude with suggestions for a way forward. See also the Commentary on this article by Muller et al., 26, e4-e5 and De Boeck et al.,26, e6-e7.

Understanding plant communities of the future requires filling knowledge gaps.

In their response to our letter, De Boek et al. (2019) and Muller, Ballhausen, Lakovic, and Rillig (2019) argue that our conclusion that we need more realistic climate change experiments is too "gloomy" and that we need a plurality of experiments including extremes and multifactorial approaches. We agree that a diversity of experimental approaches is required in order to anticipate the consequences for plant communities of alternative future environmental conditions. However, we argue that "realistic" experiments are underrepresented in the portfolio of previous experiments, and are urgently needed to understand how species communities of the future will look like and how they will function. This article is a response to Muller et al., 26, e4-e5 and De Boeck et al., 26, e6-e7.

Similar factors underlie tree abundance in forests in native and alien ranges.

AIM: Alien plant species can cause severe ecological and economic problems, and therefore attract a lot of research interest in biogeography and related fields. To identify potential future invasive species, we need to better understand the mechanisms underlying the abundances of invasive tree species in their new ranges, and whether these mechanisms differ between their native and alien ranges. Here, we test two hypotheses: that greater relative abundance is promoted by (a) functional difference from locally co-occurring trees, and (b) higher values than locally co-occurring trees for traits linked to competitive ability. LOCATION: Global. TIME PERIOD: Recent. MAJOR TAXA STUDIED: Trees. METHODS: We combined three global plant databases: sPlot vegetation-plot database, TRY plant trait database and Global Naturalized Alien Flora (GloNAF) database. We used a hierarchical Bayesian linear regression model to assess the factors associated with variation in local abundance, and how these relationships vary between native and alien ranges and depend on species' traits. RESULTS: In both ranges, species reach highest abundance if they are functionally similar to co-occurring species, yet are taller and have higher seed mass and wood density than co-occurring species. MAIN CONCLUSIONS: Our results suggest that light limitation leads to strong environmental and biotic filtering, and that it is advantageous to be taller and have denser wood. The striking similarities in abundance between native and alien ranges imply that information from tree species' native ranges can be used to predict in which habitats introduced species may become dominant.

Nonadditive effects among threats on rare plant species.

The current loss of biodiversity has put 50,000 plant species at an elevated risk of extinction worldwide. Conserving at-risk species is often complicated by covariance or nonadditivity among threats, which makes it difficult to determine optimal management strategies. We sought to demographically quantify covariance and nonadditive effects of more threats on more rare plant species than ever attempted in a single analysis. We used 1082 population reports from 186 populations across 3 U.S. states of 27 rare, herbaceous plant species collected over 15 years by citizen scientists. We used a linear mixed-effects model with 4 threats and their interactions as fixed predictors, species as a random predictor, and annual growth rates as the response. We found a significant 3-way interaction on annual growth rates; rare plant population sizes were reduced by 46% during the time immediately after disturbance when populations were also browsed by deer (Odocoileus virginianus) and had high levels of encroachment by woody species. This nonadditive effect should be considered a major threat to the persistence of rare plant species. Our results highlight the need for comprehensive, multithreat assessments to determine optimal conservation actions.

Efectos No Acumulativos entre las Amenazas para las Especies Raras de Plantas Resumen La actual pérdida de biodiversidad ha colocado a 50,000 especies de plantas en un riesgo elevado de extinción global. La conservación de las especies en riesgo frecuentemente se complica por la covarianza o la no acumulabilidad entre las amenazas, lo que dificulta la determinación de las estrategias óptimas de manejo. Buscamos cuantificar demográficamente la covarianza y los efectos no acumulativos de más amenazas sobre un mayor número de especies raras de plantas, lo más que se ha intentado en un solo análisis. Utilizamos 1,082 reportes poblacionales tomados de 186 poblaciones en tres estados de los Estados Unidos. Estas poblaciones fueron de 27 especies raras de plantas herbáceas recolectadas a lo largo de 15 años por ciudadanos científicos. Usamos un modelo lineal de efectos mixtos con cuatro amenazas y sus interacciones como pronosticadoras fijas, las especies como pronosticadoras aleatorias y las tasas anuales de crecimiento como las respuestas. Encontramos una interacción significativa de tres vías en las tasas anuales de crecimiento; el tamaño poblacional de las plantas raras se redujo en un 46% durante el tiempo transcurrido inmediatamente después de una perturbación, cuando a la vez las poblaciones también eran ramoneadas por venados (Odocoileus virginianus) y tenían niveles altos de invasión por parte de especies leñosas. Este efecto no acumulativo debería considerarse una amenaza mayor para la persistencia de las especies raras de plantas. Nuestros resultados resaltan la necesidad de tener evaluaciones completas que consideren amenazas múltiples para así determinar las acciones óptimas de conservación.

Plant traits moderate pollen limitation of introduced and native plants: a phylogenetic meta-analysis of global scale.

The role of pollination in the success of invasive plants needs to be understood because invasives have substantial effects on species interactions and ecosystem functions. Previous research has shown both that reproduction of invasive plants is often pollen limited and that invasive plants can have high seed production, motivating the questions: How do invasive populations maintain reproductive success in spite of pollen limitation? What species traits moderate pollen limitation for invaders? We conducted a phylogenetic meta-analysis with 68 invasive, 50 introduced noninvasive and 1931 native plant populations, across 1249 species. We found that invasive populations with generalist pollination or pollinator dependence were less pollen limited than natives, but invasives and introduced noninvasives did not differ. Invasive species produced 3× fewer ovules/flower and >250× more flowers per plant, compared with their native relatives. While these traits were negatively correlated, consistent with a tradeoff, this did not differ with invasion status. Invasive plants that produce many flowers and have floral generalisation are able to compensate for or avoid pollen limitation, potentially helping to explain the invaders' reproductive successes.

Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities.

Because biodiversity is multidimensional and scale-dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale-dependence matters for empirical studies, and (2) if it does matter, how exactly we should quantify biodiversity change. To address the first question, we analysed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity - species richness - was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale-dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi-dimensional and multi-scale perspective informs the responses of biodiversity to ecological drivers.

Exotic plant species receive adequate pollinator service despite variable integration into plant-pollinator networks.

Both exotic and native plant species rely on insect pollinators for reproductive success, and yet few studies have evaluated whether and how exotic plant species receive services from native pollinators for successful reproduction in their introduced range. Plant species are expected to successfully reproduce in their exotic range if they have low reliance on animal pollinators or if they successfully integrate themselves into resident plant-pollinator networks. Here, we quantify the breeding system, network integration, and pollen limitation for ten focal exotic plant species in North America. Most exotic plant species relied on animal pollinators for reproduction, and these species varied in their network integration. However, plant reproduction was limited by pollen receipt for only one plant species. Our results demonstrate that even poorly integrated exotic plant species can still have high pollination service and high reproductive success. The comprehensive framework considered here provides a method to consider the contribution of plant breeding systems and the pollinator community to pollen limitation, and can be applied to future studies to provide a more synthetic understanding of the factors that determine reproductive success of exotic plant species.

Habitat size modulates the influence of heterogeneity on species richness patterns in a model zooplankton community.

Habitat heterogeneity is a primary mechanism influencing species richness. Despite the general expectation that increased heterogeneity should increase species richness, there is considerable variation in the observed relationship, including many studies that show negative effects of heterogeneity on species richness. One mechanism that can create such disparate results is the predicted trade-off between habitat area and heterogeneity, sometimes called the area-heterogeneity-trade-off (AHTO) hypothesis. The AHTO hypothesis predicts positive effects of heterogeneity on species richness in large habitats, but negative effects in small habitats. We examined the interplay between habitat size and habitat heterogeneity in experimental mesocosms that mimic freshwater ponds, and measured responses in a species-rich zooplankton community. We used the AHTO hypothesis and related mechanisms to make predictions about how heterogeneity would affect species richness and diversity in large compared to small habitats. We found that heterogeneity had a positive influence on species richness in large, but not small habitats, and that this likely resulted because habitat specialists were able to persist only when habitat size was sufficiently large, consistent with the predictions of the AHTO hypothesis. Our results emphasize the importance of considering context (e.g., habitat size in this case) when investigating the relative importance of ecological drivers of diversity, like heterogeneity.

Effects of seed density and proximity to refuge habitat on seed predation rates for a rare and a common Lupinus species.

PREMISE OF THE STUDY: Biotic interactions such as seed predation can play a role in explaining patterns of abundance among plant species. The effect of seed predation will depend on how the strength of predation differs across species and environments, and on the degree to which seed loss at one life-cycle phase increases fitness at another phase. Few studies have simultaneously quantified predispersal and postdispersal predation in co-occurring rare and common congeners, despite the value of estimating both for understanding causes of rarity. METHODS: We quantified predispersal seed predation on the rare, herbaceous species Lupinus tidestromii (Fabaceae) and its common, shrubby congener L. chamissonis across multiple years in the same community. We experimentally measured postdispersal seed predation at two seed densities and locations near or far from an exotic grass housing high densities of deer mice (Peromyscus maniculatus), their primary, native seed predator. KEY RESULTS: The common L. chamissonis had the lowest predispersal seed predation of the two lupine species, potentially because of its height: its high racemes received less predation than those low to the ground. By contrast, the same species experienced higher postdispersal seed predation, and at predators traveled long distances away from refuge habitat to consume their seeds. Across both plant species, mice preferentially predated high-density seed sources. CONCLUSIONS: Our results show differences in the magnitude and direction of seed predation between the species across different life-cycle phases. We demonstrated possible roles of proximity to refuge habitat, seed density, and seed size in these patterns. Congeneric comparisons would benefit from a comprehensive framework that considers seed predation across different life-cycle phases and the environmental context of predation.