Climate-ecosystem modelling made easy: The Land Sites Platform.

Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.

Native range estimates for red-listed vascular plants.

Besides being central for understanding both global biodiversity patterns and associated anthropogenic impacts, species range maps are currently only available for a small subset of global biodiversity. Here, we provide a set of assembled spatial data for terrestrial vascular plants listed at the global IUCN red list. The dataset consists of pre-defined native regions for 47,675 species, density of available native occurrence records for 30,906 species, and standardized, large-scale Maxent predictions for 27,208 species, highlighting environmentally suitable areas within species' native regions. The data was generated in an automated approach consisting of data scraping and filtering, variable selection, model calibration and model selection. Generated Maxent predictions were validated by comparing a subset to available expert-drawn range maps from IUCN (n = 4,257), as well as by qualitatively inspecting predictions for randomly selected species. We expect this data to serve as a substitute whenever expert-drawn species range maps are not available for conducting large-scale analyses on biodiversity patterns and associated anthropogenic impacts.

Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes.

The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and processes that couple vegetation and climate. Dynamic global vegetation models (DGVMs) have been widely applied to describe the distribution of vegetation types and their future dynamics in response to climate change. As a process-based approach, it partly relies on hard-coded climate thresholds to constrain the distribution of vegetation. What thresholds to implement in DGVMs and how to replace them with more process-based descriptions remain among the major challenges. In this study, we employ machine learning using decision trees to extract large-scale relationships between the global distribution of vegetation and climatic characteristics from remotely sensed vegetation and climate data. We analyse how the dominant vegetation types are linked to climate extremes as compared to seasonally or annually averaged climatic conditions. The results show that climate extremes allow us to describe the distribution and eco-climatological space of the vegetation types more accurately than the averaged climate variables, especially those types which occupy small territories in a relatively homogeneous ecological space. Future predicted vegetation changes using both climate extremes and averaged climate variables are less prominent than that predicted by averaged climate variables and are in better agreement with those of DGVMs, further indicating the importance of climate extremes in determining geographic distributions of different vegetation types. We found that the temperature thresholds for vegetation types (e.g. grass and open shrubland) in cold environments vary with moisture conditions. The coldest daily maximum temperature (extreme cold day) is particularly important for separating many different vegetation types. These findings highlight the need for a more explicit representation of the impacts of climate extremes on vegetation in DGVMs.

Presence-absence of plant habitat specialists in 15 patches of dry calcareous grassland.

Background: Dry grasslands on calcareous bedrock in warm climates around the Oslo Fjord are naturally fragmented biodiversity hotspots. This habitat geographically coincides with the most densely populated area of Norway. Many habitat specialists, along with the habitat itself, are red-listed because of land-use change, forest encroachment, and invasive species that cause habitat loss and greater isolation of remaining patches. To ensure effective conservation, data on species presences and absences are necessary to quantify states, changes, and extinction risks in specific populations and habitat patches. New information: We present presence-absence data of 49 vascular plant species in 15 patches of dry calcareous grassland habitat, surveyed in 2009, 2019, and in 2020. The species are considered to be habitat specialists and, thus, unlikely to occur between the patches.

Phenotypic plasticity masks range-wide genetic differentiation for vegetative but not reproductive traits in a short-lived plant.

Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short-lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with observational field data throughout the range of a widespread short-lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait-environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field-observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness.

Biotic rescaling reveals importance of species interactions for variation in biodiversity responses to climate change.

Generality in understanding biodiversity responses to climate change has been hampered by substantial variation in the rates and even directions of response to a given change in climate. We propose that such context dependencies can be clarified by rescaling climate gradients in terms of the underlying biological processes, with biotic interactions as a particularly important process. We tested this rescaling approach in a replicated field experiment where entire montane grassland communities were transplanted in the direction of expected temperature and/or precipitation change. In line with earlier work, we found considerable variation across sites in community dynamics in response to climate change. However, these complex context dependencies could be substantially reduced or eliminated by rescaling climate drivers in terms of proxies of plant-plant interactions. Specifically, bryophytes limited colonization by new species into local communities, whereas the cover of those colonists, along with bryophytes, were the primary drivers of local extinctions. These specific interactions are relatively understudied, suggesting important directions for future work in similar systems. More generally, the success of our approach in explaining and simplifying landscape-level variation in climate change responses suggests that developing and testing proxies for relevant underlying processes could be a fruitful direction for building more general models of biodiversity response to climate change.

Hollow oaks and beetle functional diversity: Significance of surroundings extends beyond taxonomy.

Veteran hollow oaks (Quercus spp.) are keystone structures hosting high insect diversity but are declining in numbers due to intensification of land use and the abandonment of traditional management. The loss of this vital habitat is resulting in a reduction of biodiversity, and this likely has consequences for ecosystem functioning, especially if functional diversity is reduced. A considerable amount of research has been done on predictors of beetle taxonomic diversity in veteran oaks, but predictors of functional diversity have remained largely unexplored. The aim of this study was to establish whether the features and surroundings of veteran oaks are related to functional diversity within three functional groups of beetles (decomposers, predators, and flower visitors) and determine whether species richness and functional diversity within the groups are dependent on the same predictors. Sampling was carried out intermittently between 2004 and 2011 on 61 veteran oaks in Southern Norway. Of the 876 beetle species that were collected, 359 were determined to be decomposers, 284 were predators, and 85 were flower visitors. Species richness and functional diversity in all groups were consistently higher in traps mounted on veteran oaks in forests than in open landscapes. However, additional predictors differed between groups, and for species richness and functional diversity. Decomposer species richness responded to tree vitality, while functional diversity responded to habitat connectivity, predator species richness responded to regrowth of shrubs while functional diversity responded to tree circumference, and flower visitor richness and functional diversity did not respond to any additional predictors. Previous studies have found that the features and surroundings of veteran oaks are important for conservation of taxonomic diversity, and the results from this study indicate that they are also important for functional diversity within multiple functional groups.

The devil is in the detail: Nonadditive and context-dependent plant population responses to increasing temperature and precipitation.

In climate change ecology, simplistic research approaches may yield unrealistically simplistic answers to often more complicated problems. In particular, the complexity of vegetation responses to global climate change begs a better understanding of the impacts of concomitant changes in several climatic drivers, how these impacts vary across different climatic contexts, and of the demographic processes underlying population changes. Using a replicated, factorial, whole-community transplant experiment, we investigated regional variation in demographic responses of plant populations to increased temperature and/or precipitation. Across four perennial forb species and 12 sites, we found strong responses to both temperature and precipitation change. Changes in population growth rates were mainly due to changes in survival and clonality. In three of the four study species, the combined increase in temperature and precipitation reflected nonadditive, antagonistic interactions of the single climatic changes for population growth rate and survival, while the interactions were additive and synergistic for clonality. This disparity affects the persistence of genotypes, but also suggests that the mechanisms behind the responses of the vital rates differ. In addition, survival effects varied systematically with climatic context, with wetter and warmer + wetter transplants showing less positive or more negative responses at warmer sites. The detailed demographic approach yields important mechanistic insights into how concomitant changes in temperature and precipitation affect plants, which makes our results generalizable beyond the four study species. Our comprehensive study design illustrates the power of replicated field experiments in disentangling the complex relationships and patterns that govern climate change impacts across real-world species and landscapes.

Prediction of biodiversity hotspots in the Anthropocene: The case of veteran oaks.

Over the past centuries, humans have transformed large parts of the biosphere, and there is a growing need to understand and predict the distribution of biodiversity hotspots influenced by the presence of humans. Our basic hypothesis is that human influence in the Anthropocene is ubiquitous, and we predict that biodiversity hot spot modeling can be improved by addressing three challenges raised by the increasing ecological influence of humans: (i) anthropogenically modified responses to individual ecological factors, (ii) fundamentally different processes and predictors in landscape types shaped by different land use histories and (iii) a multitude and complexity of natural and anthropogenic processes that may require many predictors and even multiple models in different landscape types. We modeled the occurrence of veteran oaks in Norway, and found, in accordance with our basic hypothesis and predictions, that humans influence the distribution of veteran oaks throughout its range, but in different ways in forests and open landscapes. In forests, geographical and topographic variables related to the oak niche are still important, but the occurrence of veteran oaks is shifted toward steeper slopes, where logging is difficult. In open landscapes, land cover variables are more important, and veteran oaks are more common toward the north than expected from the fundamental oak niche. In both landscape types, multiple predictor variables representing ecological and human-influenced processes were needed to build a good model, and several models performed almost equally well. Models accounting for the different anthropogenic influences on landscape structure and processes consistently performed better than models based exclusively on natural biogeographical and ecological predictors. Thus, our results for veteran oaks clearly illustrate the challenges to distribution modeling raised by the ubiquitous influence of humans, even in a moderately populated region, but also show that predictions can be improved by explicitly addressing these anthropogenic complexities.

From facilitation to competition: temperature-driven shift in dominant plant interactions affects population dynamics in seminatural grasslands.

Biotic interactions are often ignored in assessments of climate change impacts. However, climate-related changes in species interactions, often mediated through increased dominance of certain species or functional groups, may have important implications for how species respond to climate warming and altered precipitation patterns. We examined how a dominant plant functional group affected the population dynamics of four co-occurring forb species by experimentally removing graminoids in seminatural grasslands. Specifically, we explored how the interaction between dominants and subordinates varied with climate by replicating the removal experiment across a climate grid consisting of 12 field sites spanning broad-scale temperature and precipitation gradients in southern Norway. Biotic interactions affected population growth rates of all study species, and the net outcome of interactions between dominants and subordinates switched from facilitation to competition with increasing temperature along the temperature gradient. The impacts of competitive interactions on subordinates in the warmer sites could primarily be attributed to reduced plant survival. Whereas the response to dominant removal varied with temperature, there was no overall effect of precipitation on the balance between competition and facilitation. Our findings suggest that global warming may increase the relative importance of competitive interactions in seminatural grasslands across a wide range of precipitation levels, thereby favouring highly competitive dominant species over subordinate species. As a result, seminatural grasslands may become increasingly dependent on disturbance (i.e. traditional management such as grazing and mowing) to maintain viable populations of subordinate species and thereby biodiversity under future climates. Our study highlights the importance of population-level studies replicated under different climatic conditions for understanding the underlying mechanisms of climate change impacts on plants.

Population dynamics in changing environments: the case of an eruptive forest pest species.

In recent decades we have seen rapid and co-occurring changes in landscape structure, species distributions and even climate as consequences of human activity. Such changes affect the dynamics of the interaction between major forest pest species, such as bark beetles (Coleoptera: Curculionidae, Scolytinae), and their host trees. Normally breeding mostly in broken or severely stressed spruce; at high population densities some bark beetle species can colonise and kill healthy trees on scales ranging from single trees in a stand to multi-annual landscape-wide outbreaks. In Eurasia, the largest outbreaks are caused by the spruce bark beetle, Ips typographus (Linnaeus), which is common and shares a wide distribution with its main host, Norway spruce (Picea abies Karst.). A large literature is now available, from which this review aims to synthesize research relevant for the population dynamics of I. typographus and co-occurring species under changing conditions. We find that spruce bark beetle population dynamics tend to be metastable, but that mixed-species and age-heterogeneous forests with good site-matching tend to be less susceptible to large-scale outbreaks. While large accumulations of logs should be removed and/or debarked before the next swarming period, intensive removal of all coarse dead wood may be counterproductive, as it reduces the diversity of predators that in some areas may play a role in keeping I. typographus populations below the outbreak threshold, and sanitary logging frequently causes edge effects and root damage, reducing the resistance of remaining trees. It is very hard to predict the outcome of interspecific interactions due to invading beetle species or I. typographus establishing outside its current range, as they can be of varying sign and strength and may fluctuate depending on environmental factors and population phase. Most research indicates that beetle outbreaks will increase in frequency and magnitude as temperature, wind speed and precipitation variability increases, and that mitigating forestry practices should be adopted as soon as possible considering the time lags involved.

Trees wanted--dead or alive! Host selection and population dynamics in tree-killing bark beetles.

Bark beetles (Coleoptera: Curculionidae, Scolytinae) feed and breed in dead or severely weakened host trees. When their population densities are high, some species aggregate on healthy host trees so that their defences may be exhausted and the inner bark successfully colonized, killing the tree in the process. Here we investigate under what conditions participating with unrelated conspecifics in risky mass attacks on living trees is an adaptive strategy, and what this can tell us about bark beetle outbreak dynamics. We find that the outcome of individual host selection may deviate from the ideal free distribution in a way that facilitates the emergence of tree-killing (aggressive) behavior, and that any heritability on traits governing aggressiveness seems likely to exist in a state of flux or cycles consistent with variability observed in natural populations. This may have implications for how economically and ecologically important species respond to environmental changes in climate and landscape (forest) structure. The population dynamics emerging from individual behavior are complex, capable of switching between "endemic" and "epidemic" regimes spontaneously or following changes in host availability or resistance. Model predictions are compared to empirical observations, and we identify some factors determining the occurrence and self-limitation of epidemics.

Importance of individual and environmental variation for invasive species spread: a spatial integral projection model.

Plant survival, growth, and flowering are size dependent in many plant populations but also vary among individuals of the same size. This individual variation, along with variation in dispersal caused by differences in, e.g., seed release height, seed characteristics, and wind speed, is a key determinant of the spread rate of species through homogeneous landscapes. Here we develop spatial integral projection models (SIPMs) that include both demography and dispersal with continuous state variables. The advantage of this novel approach over discrete-stage spread models is that the effect of variation in plant size and size-dependent vital rates can be studied at much higher resolution. Comparing Neubert-Caswell matrix models to SIPMs allowed us to assess the importance of including individual variation in the models. As a test case we parameterized a SIPM with previously published data on the invasive monocarpic thistle Carduus nutans in New Zealand. Spread rate (c*) estimates were 34% lower than for standard spatial matrix models and stabilized with as few as seven evenly distributed size classes. The SIPM allowed us to calculate spread rate elasticities over the range of plant sizes, showing the size range of seedlings that contributed most to c* through their survival, growth and reproduction. The annual transitions of these seedlings were also the most important ones for local population growth (lambda). However, seedlings that reproduced within a year contributed relatively more to c* than to lambda. In contrast, plants that grow over several years to reach a large size and produce many more seeds, contributed relatively more to lambda than to c*. We show that matrix models pick up some of these details, while other details disappear within wide size classes. Our results show that SIPMs integrate various sources of variation much better than discrete-stage matrix models. Simpler, heuristic models, however, remain very valuable in studies where the main goal is to investigate the general impact of a life history stage on population dynamics. We conclude with a discussion of future extensions of SIPMs, including incorporation of continuous time and environmental drivers.

The Nature Index: a general framework for synthesizing knowledge on the state of biodiversity.

The magnitude and urgency of the biodiversity crisis is widely recognized within scientific and political organizations. However, a lack of integrated measures for biodiversity has greatly constrained the national and international response to the biodiversity crisis. Thus, integrated biodiversity indexes will greatly facilitate information transfer from science toward other areas of human society. The Nature Index framework samples scientific information on biodiversity from a variety of sources, synthesizes this information, and then transmits it in a simplified form to environmental managers, policymakers, and the public. The Nature Index optimizes information use by incorporating expert judgment, monitoring-based estimates, and model-based estimates. The index relies on a network of scientific experts, each of whom is responsible for one or more biodiversity indicators. The resulting set of indicators is supposed to represent the best available knowledge on the state of biodiversity and ecosystems in any given area. The value of each indicator is scaled relative to a reference state, i.e., a predicted value assessed by each expert for a hypothetical undisturbed or sustainably managed ecosystem. Scaled indicator values can be aggregated or disaggregated over different axes representing spatiotemporal dimensions or thematic groups. A range of scaling models can be applied to allow for different ways of interpreting the reference states, e.g., optimal situations or minimum sustainable levels. Statistical testing for differences in space or time can be implemented using Monte-Carlo simulations. This study presents the Nature Index framework and details its implementation in Norway. The results suggest that the framework is a functional, efficient, and pragmatic approach for gathering and synthesizing scientific knowledge on the state of biodiversity in any marine or terrestrial ecosystem and has general applicability worldwide.

Population viability analysis with species occurrence data from museum collections.

The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi-extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available.

Is eradication of the pinewood nematode (Bursaphelenchus xylophilus) likely? An evaluation of current contingency plans.

The pinewood nematode (PWN) is one of the worst tree-killing exotic pests in East-Asian countries. The first European record of establishment in Portugal in 1999 triggered extensive surveys and contingency plans for eradication in European countries, including immediate removal of large areas of conifer host trees. Using Norway as an example, we applied a simulation model to evaluate the chance of successful eradication of a hypothetical introduction by the current contingency plan in a northern area where wilting symptoms are not expected to occur. Despite a highly variable spread of nematode infestations in space and time, the probability of successful eradication in 20 years was consistently low (mean 0.035, SE 0.02). The low success did not change significantly by varying the biological parameters in sensitivity analyses (SA), probably due to the late detection of infestations by the survey (mean 14.3 years). SA revealed a strong influence of management parameters. However, a high probability of eradication required unrealistic measures: achieving an eradication probability of 0.99 in 20 years required 10,000 survey samples per year and a host tree removal radius of 8,000 m around each detection point.

Optimal management strategies to control local population growth or population spread may not be the same.

The objective of most pest management programs is to "control" the pest species. However, optimal control of local abundance and population growth may require different management strategies than optimal control of spatial spread. We use coupled demographic-dispersal models to address the relative importance of different management approaches to these two main control objectives for the invasive thistle Carduus nutans. The models are parameterized with data from thistle populations in the native (France) and invaded ranges (Australia and New Zealand). We assess a wide range of commonly used management strategies for their absolute and relative impacts on population growth and spread in both invaded-range scenarios. The projected population growth rate in New Zealand is more than twice that in Australia, while the spread rate is more than four times the Australian value. In general, spread and growth are both most strongly affected by the same life cycle transitions; however, in a few cases certain vital rates disproportionately affect either spread or growth. The transition that represents the contribution of large rosettes in one year to the number of large rosettes in the following year (the large rosette-large rosette transition) in Australia is dominated by reproduction (rather than survival) and hence is relatively more important to spread than to population growth. In New Zealand, the small rosette-small rosette transition is also predominantly dispersal-related. However, establishment of small plants from the seed bank contributes more to population growth than spread, as no dispersal is involved. The fine-resolution vital-rate-based modeling approach allows us to identify potentially novel optimal management strategies: approaches that reduce microsite availability show promise for reducing both population growth and spread, while strategies that affect dispersal parameters will affect spread. Additionally, the relative ranking of some biocontrol agents shifts depending on whether control of population growth or population spread is the desired outcome and therefore could alter which of the agents are preferred for release in a new area. The possibility of differences in ranked agent effectiveness has been predicted theoretically, but never before demonstrated using field data.

Dispersal patterns, dispersal mechanisms, and invasion wave speeds for invasive thistles.

Understanding and predicting population spread rates is an important problem in basic and applied ecology. In this article, we link estimates of invasion wave speeds to species traits and environmental conditions. We present detailed field studies of wind dispersal and compare nonparametric (i.e., data-based) and mechanistic (fluid dynamics model-based) dispersal kernel and spread rate estimates for two important invasive weeds, Carduus nutans and Carduus acanthoides. A high-effort trapping design revealed highly leptokurtic dispersal distributions, with seeds caught up to 96 m from the source, far further than mean dispersal distances (approx. 2 m). Nonparametric wave speed estimates are highly sensitive to sampling effort. Mechanistic estimates are insensitive to sampling because they are obtained from independent data and more useful because they are based on the dispersal mechanism. Over a wide range of realistic conditions, mechanistic spread rate estimates were most sensitive to high winds and low seed settling velocities. The combination of integrodifference equations and mechanistic dispersal models is a powerful tool for estimating invasion spread rates and for linking these estimates to characteristics of the species and the environment.

Seed release by invasive thistles: the impact of plant and environmental factors.

Dispersal is a key process in biological studies of spatial dynamics, but the initiation of dispersal has often been neglected, despite strong indications that differential timing of dispersal can significantly affect dispersal distances. To investigate which plant and environmental factors determine the release of plumed seeds by the invasive thistles Carduus acanthoides and Carduus nutans, we exposed 192 flower heads of each species to increasing wind speeds in a full-factorial wind tunnel experiment with four air flow turbulence, three flower head wetness and two flower head temperature levels. The number of seed releases was highest under dry and turbulent conditions and from heads that had already lost a considerable number of seeds, but was not affected by flower head size, head angle or temperature. Inspection of the trials on video showed that higher wind speeds were needed to meet the seed release threshold in laminar flows and for C. acanthoides heads that had been wet for a longer time. Species differences were minimal, although seed release was more sensitive to lower levels of turbulence in the larger-headed and more open C. nutans heads. Knowledge of seed release biases towards weather conditions favourable for long-distance dispersal improves our understanding of the spread of invaders and allows managers to increase the efficiency of their containment strategies by applying them at crucial times.

Environmental variability and the initiation of dispersal: turbulence strongly increases seed release.

Dispersal is a critical process in ecology. It is an important biological driver of, for example, invasions, metapopulation dynamics, spatial pattern formation and pathogen movement. Much is known about the effect of environmental variability, including turbulence, on dispersal of diaspores. Here, we document experimentally the strong but under-explored influence of turbulence on the initiation of dispersal. Flower heads of two thistle species (Carduus nutans and Carduus acanthoides) with ripe seeds were exposed to series of laminar and turbulent air flows of increasing velocity in a wind tunnel. Seed release increased with wind speeds for both laminar and turbulent flows for both species. However, far more seeds were released, at significantly lower wind speeds, during turbulent flows. These results strongly suggest a need for more quantitative studies of abscission in the field, as well as dispersal models that incorporate variability in the diaspore release phase.