Herkogamy, a Principal Functional Trait of Plant Reproductive Biology

Premise of research. Phenotypic traits that consistently mediate species' responses to environmental variation (functional traits) provide a promising approach toward generalizing ecological and evolutionary patterns and thereby gaining insights into the processes generating them. In the plant functional ecology literature, most trait-based studies have focused on traits mediating either resource competition or responses to variation in the abiotic environment, while traits mediating reproductive interactions have often been neglected. Methodology. Here, I discuss the value of herkogamy, the spatial separation of male and female functions in flowers, as a functional trait in plant reproductive biology and review the evidence relevant to the hypothesis that taxa exhibiting greater herkogamy have historically experienced more reliable pollination and more outcrossed mating systems. Pivotal results. A large body of work in the field of plant reproductive biology has identified a set of nearly ubiquitous correlations between average herkogamy and features of plant mating systems, notably, autofertility (seed set in the absence of pollinators) and outcrossing rate. Herkogamy often varies extensively among populations and species, and the adaptive interpretation is that herkogamy exhibits local adaptation to the reliability of the pollination environment. Conclusions. These results underline the value of herkogamy as a functional trait representing variation in mating histories. Many important insights are likely to emerge from studies leveraging herkogamy as an easily measured proxy of plant mating systems, as already demonstrated in comparative studies and studies of reproductive interactions. Greater consideration of herkogamy and other reproductive-function traits in studies of species coexistence may provide a more complete understanding of community assembly processes.Peer reviewe

A database and synthesis of euglossine bee assemblages collected at fragrance baits

Euglossine bees are an ecologically important group, which due to their diverse resource needs act as pollinators of many neotropical plants. Male euglossines collect fragrant compounds used in mating displays from diverse sources, including the flowers of orchids and other plants. This aspect of euglossine biology has proven exceptionally useful for studies of euglossine bee populations, because male bees can be readily attracted to fragrance baits deployed in natural habitats. We synthesise the data accumulated over the 50 years since the introduction of euglossine bee baiting inventories and make these data openly available in the EUGCOMM database. By fitting hierarchical joint species distribution models to presence-absence and abundance data, we reveal that the assemblages of bees attracted depend on the baits used in interaction with species-specific fragrance preferences and that bee assemblages are most diverse at sites in landscapes characterised by partial but not complete forest cover. We suggest that these results reflect the diverse resource needs of euglossine bees and are consistent with the hypothesis that male euglossines establish home ranges incorporating multiple habitat types. These results may have important consequences for the design of nature reserves in the tropics, if these iconic pollinators are to be conserved for the future.Peer reviewe

Host-plant availability drives the spatiotemporal dynamics of interacting metapopulations across a fragmented landscape

The dynamics of ecological communities depend partly on species interactions within and among trophic levels. Experimental work has demonstrated the impact of species interactions on the species involved, but it remains unclear whether these effects can also be detected in long-term time series across heterogeneous landscapes. We analyzed a 19-year time series of patch occupancy by the Glanville fritillary butterflyMelitaea cinxia, its specialist parasitoid waspCotesia melitaearum, and the specialist fungal pathogenPodosphaera plantaginisinfectingPlantago lanceolata,a host plant of the Glanville fritillary. These species share a network of more than 4,000 habitat patches in the angstrom land islands, providing a metacommunity data set of unique spatial and temporal resolution. To assess the influence of interactions among the butterfly, parasitoid, and mildew on metacommunity dynamics, we modeled local colonization and extinction rates of each species while including or excluding the presence of potentially interacting species in the previous year as predictors. The metapopulation dynamics of all focal species varied both along a gradient in host plant abundance, and spatially as indicated by strong effects of local connectivity. Colonization and to a lesser extent extinction rates depended also on the presence of interacting species within patches. However, the directions of most effects differed from expectations based on previous experimental and modeling work, and the inferred influence of species interactions on observed metacommunity dynamics was limited. These results suggest that although local interactions among the butterfly, parasitoid, and mildew occur, their roles in metacommunity spatiotemporal dynamics are relatively weak. Instead, all species respond to variation in plant abundance, which may in turn fluctuate in response to variation in climate, land use, or other environmental factors.Peer reviewe

Measuring, comparing and interpreting phenotypic selection on floral scent

Natural selection on floral scent composition is a key element of the hypothesis that pollinators and other floral visitors drive scent evolution. The measure of such selection is complicated by the high-dimensional nature of floral scent data and uncertainty about the cognitive processes involved in scent-mediated communication. We use dimension reduction through reduced-rank regression to jointly estimate a scent composite trait under selection and the strength of selection acting on this trait. To assess and compare variation in selection on scent across species, time and space, we reanalyse 22 datasets on six species from four previous studies. The results agreed qualitatively with previous analyses in terms of identifying populations and scent compounds subject to stronger selection but also allowed us to evaluate and compare the strength of selection on scent across studies. Doing so revealed that selection on floral scent was highly variable, and overall about as common and as strong as selection on other phenotypic traits involved in pollinator attraction or pollen transfer. These results are consistent with an important role of floral scent in pollinator attraction. Our approach should be useful for further studies of plant-animal communication and for studies of selection on other high-dimensional phenotypes. In particular, our approach will be useful for studies of pollinator-mediated selection on complex scent blends comprising many volatiles, and when no prior information on the physiological responses of pollinators to scent compounds is available

Measuring, comparing and interpreting phenotypic selection on floral scent

Natural selection on floral scent composition is a key element of the hypothesis that pollinators and other floral visitors drive scent evolution. The measure of such selection is complicated by the high-dimensional nature of floral scent data and uncertainty about the cognitive processes involved in scent-mediated communication. We use dimension reduction through reduced-rank regression to jointly estimate a scent composite trait under selection and the strength of selection acting on this trait. To assess and compare variation in selection on scent across species, time and space, we reanalyse 22 datasets on six species from four previous studies. The results agreed qualitatively with previous analyses in terms of identifying populations and scent compounds subject to stronger selection but also allowed us to evaluate and compare the strength of selection on scent across studies. Doing so revealed that selection on floral scent was highly variable, and overall about as common and as strong as selection on other phenotypic traits involved in pollinator attraction or pollen transfer. These results are consistent with an important role of floral scent in pollinator attraction. Our approach should be useful for further studies of plant-animal communication and for studies of selection on other high-dimensional phenotypes. In particular, our approach will be useful for studies of pollinator-mediated selection on complex scent blends comprising many volatiles, and when no prior information on the physiological responses of pollinators to scent compounds is available.Peer reviewe

Joint species distribution modelling with the r-package Hmsc

Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analysing data in community ecology. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs. HMSC allows the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships and the spatio-temporal context of the study, providing predictive insights into community assembly processes from non-manipulative observational data of species communities. The full range of functionality of HMSC has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce Hmsc 3.0, a user-friendly r implementation. We illustrate the use of the package by applying Hmsc 3.0 to a range of case studies on real and simulated data. The real data consist of bird counts in a spatio-temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. Vignettes on simulated data involve single-species models, models of small communities, models of large species communities and models for large spatial data. We demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. We demonstrate how to construct and fit models with different types of random effects, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates and how to make predictions. We further demonstrate how Hmsc 3.0 can be applied to normally distributed data, count data and presence-absence data. The package, along with the extended vignettes, makes JSDM fitting and post-processing easily accessible to ecologists familiar with r.Peer reviewe

Joint species distribution modelling with the r-package Hmsc

Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analysing data in community ecology. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs. HMSC allows the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships and the spatio-temporal context of the study, providing predictive insights into community assembly processes from non-manipulative observational data of species communities. The full range of functionality of HMSC has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce Hmsc 3.0, a user-friendly r implementation. We illustrate the use of the package by applying Hmsc 3.0 to a range of case studies on real and simulated data. The real data consist of bird counts in a spatio-temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. Vignettes on simulated data involve single-species models, models of small communities, models of large species communities and models for large spatial data. We demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. We demonstrate how to construct and fit models with different types of random effects, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates and how to make predictions. We further demonstrate how Hmsc 3.0 can be applied to normally distributed data, count data and presence-absence data. The package, along with the extended vignettes, makes JSDM fitting and post-processing easily accessible to ecologists familiar with r.Peer reviewe

Predicting fish community responses to environmental policy targets

The European Union adopted the Water Framework Directive (WFD) in the year 2000 to tackle the rapid degradation of freshwater systems. However, biological, hydromorphological, and physico-chemical water quality targets are currently not met, and identifying successful policy implementation and management actions is of key importance. We built a joint species distribution model for riverine fish in Flanders (Belgium) to better understand the response of fish communities to current environmental policy goals. Environmental covariates included physico-chemical variables and hydromorphological quality indices, while waterway distances accounted for spatial effects. We detected strong effects of physico-chemistry on fish species' distributions. Evaluation of fish community responses to simulated policy scenarios revealed that targeting a 'good' status, following the WFD, increases average species richness with a fraction of species (0.13-0.69 change in accumulated occurrence probabilities). Targeting a 'very good' status, however, predicted an increase of 0.17-1.38 in average species richness. These simulations indicated that riverbed quality, nitrogen, and conductivity levels should be the focal point of policy. However, the weak response of species to a 'good' quality together with the complexity of nutrient-associated problems, suggest a challenging future for river restoration in Flanders.Peer reviewe

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications