On the Relationship between Pollen Size and Genome Size

Here we test whether genome size is a predictor of pollen size. If it were, inferences of ancient genome size would be possible using the abundant paleo-palynolgical record. We performed regression analyses across 464 species of pollen width and genome size. We found a significant positive trend. However, regression analysis using phylogentically independent contrasts did not support the correlated evolution of these traits. Instead, a large split between angiosperms and gymnosperms for both pollen width and genome size was revealed. Sister taxa were not more likely to show a positive contrast when compared to deeper nodes. However, significantly more congeneric species had a positive trend than expected by chance. These results may reflect the strong selection pressure for pollen to be small. Also, because pollen grains are not metabolically active when measured, their biology is different than other cells which have been shown to be strongly related to genome size, such as guard cells. Our findings contrast with previously published research. It was our hope that pollen size could be used as a proxy for inferring the genome size of ancient species. However, our results suggest pollen is not a good candidate for such endeavors.Peer Reviewe

Synchrony Matters More than Species Richness in Plant Community Stability at a Global Scale

The stability of ecological communities is critical for the stable provisioning of ecosystem services, such as food and forage production, carbon sequestration, and soil fertility. Greater biodiversity is expected to enhance stability across years by decreasing synchrony among species, but the drivers of stability in nature remain poorly resolved. Our analysis of time series from 79 datasets across the world showed that stability was associated more strongly with the degree of synchrony among dominant species than with species richness. The relatively weak influence of species richness is consistent with theory predicting that the effect of richness on stability weakens when synchrony is higher than expected under random fluctuations, which was the case in most communities. Land management, nutrient addition, and climate change treatments had relatively weak and varying effects on stability, modifying how species richness, synchrony, and stability interact. Our results demonstrate the prevalence of biotic drivers on ecosystem stability, with the potential for environmental drivers to alter the intricate relationship among richness, synchrony, and stability.National Science Foundation DEB-8114302, DEB8811884, DEB-9411972, DEB-0080382, DEB-0620652, DEB-1234162, DEB0618210National Science Foundation Research Coordination Network DEB-1042132Institute on the Environment DG-0001-13Agency of the Czech Republic GACR16-15012SCzech Academy of Sciences RVO 67985939Comunidad Autónoma de Madrid 2017-T2/AMB-5406Biotechnology and Biological Sciences Research Council BBS/E/C/000J030

All dispersal functions are wrong, but many are useful: a response to Cousens et al.

1. To address the lack of information about the shape and extent of real dispersal kernels, Bullock et al. (Journal of Ecology 105:6-19, 2017) synthesised empirical information on seed dispersal distances. Testing the fit of a variety of probability density functions, they found no function was the best-fitting for all datasets but some outperformed others. Cousens et al. (Journal of Ecology, 2017) focus on the specific finding of the generally poor fit of the WALD function to wind dispersal data and use this to argue that mechanistically derived functions would not be expected to fit data particularly well. 2. We agree in part with this argument and discuss the issues that may lead to poor fit, including the simplifying assumptions of the WALD and the complexity of the dispersal process. We explain the fundamental linkage between the mechanistic form of the WALD and the derived function used for fitting to data. 3. We demonstrate, however, that the logic that a mechanistically based function could fit to data is valid, under the hypothesis that it encompasses the key processes determining the dispersal kernel. This argument is supported by the facts that: (1) our analyses and others have shown the WALD performs well in a number of cases; and (2) the WALD is the best-fitting function for an example in which we simulate dispersal data using a realistic representation of variability in the wind dispersal process. 4. Synthesis. While there are reasons that mechanistically derived functions may not fit well to empirical data, they do in some empirical and simulated cases and this suggests they can capture the dispersal behaviour of real systems. Mechanistic functions should be explored along with other more general functions when describing empirical data to investigate their simplifying assumptions and to add to our arsenal of functions for analysing dispersal data. Analyses using these functions are critical if we are to move from simply describing the system in which the data were gathered to gaining more general insights into dispersal and predicting its consequences

Functional trait effects on ecosystem stability: assembling the jigsaw puzzle

Under global change, how biological diversity and ecosystem services are maintained in time is a fundamental question. Ecologists have long argued about multiple mechanisms by which local biodiversity might control the temporal stability of ecosystem properties. Accumulating theories and empirical evidence suggest that, together with different population and community parameters, these mechanisms largely operate through differences in functional traits among organisms. We review potential trait-stability mechanisms together with underlying tests and associated metrics. We identify various trait-based components, each accounting for different stability mechanisms, that contribute to buffering, or propagating, the effect of environmental fluctuations on ecosystem functioning. This comprehensive picture, obtained by combining different puzzle pieces of trait-stability effects, will guide future empirical and modeling investigations.This study is the result of an international workshop financed by the Valencian government in Spain (Generalitat Valenciana, reference AORG/2018/) and was supported by Spanish Plan Nacional de I+D+i (project PGC2018-099027-B-I00). E.V. was supported by the 2017 program for attracting and retaining talent of Comunidad de Madrid (no. 2017-T2/ AMB-5406)

Directional trends in species composition over time can lead to a widespread overemphasis of year‐to‐year asynchrony

Questions: Compensatory dynamics are described as one of the main mechanisms that increase community stability, e.g., where decreases of some species on a year‐to‐year basis are offset by an increase in others. Deviations from perfect synchrony between species (asynchrony) have therefore been advocated as an important mechanism underlying biodiversity effects on stability. However, it is unclear to what extent existing measures of synchrony actually capture the signal of year‐to‐year species fluctuations in the presence of long‐term directional trends in both species abundance and composition (species directional trends hereafter). Such directional trends may lead to a misinterpretation of indices commonly used to reflect year‐to‐year synchrony. Methods: An approach based on three‐term local quadrat variance (T3) which assesses population variability in a three‐year moving window, was used to overcome species directional trend effects. This “detrending” approach was applied to common indices of synchrony across a worldwide collection of 77 temporal plant community datasets comprising almost 7,800 individual plots sampled for at least six years. Plots included were either maintained under constant “control” conditions over time or were subjected to different management or disturbance treatments. Results: Accounting for directional trends increased the detection of year‐to‐year synchronous patterns in all synchrony indices considered. Specifically, synchrony values increased significantly in ~40% of the datasets with the T3 detrending approach while in ~10% synchrony decreased. For the 38 studies with both control and manipulated conditions, the increase in synchrony values was stronger for longer time series, particularly following experimental manipulation. Conclusions: Species’ long‐term directional trends can affect synchrony and stability measures potentially masking the ecological mechanism causing year‐to‐year fluctuations. As such, previous studies on community stability might have overemphasised the role of compensatory dynamics in real‐world ecosystems, and particularly in manipulative conditions, when not considering the possible overriding effects of long‐term directional trends

LOTVS: a global collection of permanent vegetation plots

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology

On the Relationship between Pollen Size and Genome Size

Here we test whether genome size is a predictor of pollen size. If it were, inferences of ancient genome size would be possible using the abundant paleo-palynolgical record. We performed regression analyses across 464 species of pollen width and genome size. We found a significant positive trend. However, regression analysis using phylogentically independent contrasts did not support the correlated evolution of these traits. Instead, a large split between angiosperms and gymnosperms for both pollen width and genome size was revealed. Sister taxa were not more likely to show a positive contrast when compared to deeper nodes. However, significantly more congeneric species had a positive trend than expected by chance. These results may reflect the strong selection pressure for pollen to be small. Also, because pollen grains are not metabolically active when measured, their biology is different than other cells which have been shown to be strongly related to genome size, such as guard cells. Our findings contrast with previously published research. It was our hope that pollen size could be used as a proxy for inferring the genome size of ancient species. However, our results suggest pollen is not a good candidate for such endeavors

Predicting species’ maximum dispersal distances from simple plant traits

Many studies have shown plant species' dispersal distances to be strongly related to life-history traits, but how well different traits can predict dispersal distances is not yet known. We used cross-validation techniques and a global data set (576 plant species) to measure the predictive power of simple plant traits to estimate the species' maximum dispersal distance. Including dispersal syndrome (wind, animal, ant, ballistic, and no special syndrome), growth form (tree, shrub, herb), seed mass, plant height, and terminal velocity as explanatory variables in different combinations we constructed models to explain variation in measured maximum dispersal distances and evaluated their ability to predict maximum dispersal distances. Predictions are more accurate, but also limited to a particular set of species, if data on more specific traits, such as terminal velocity, are available. The best model (R2 = 0.60) included dispersal syndrome, growth form and terminal velocity as fixed effects. Reasonable predictions of maximum dispersal distance (R2 = 0.53) are also possible when using only the simplest and most commonly measured traits; dispersal syndrome and growth form together with species taxonomy data. We provide a function dispeRsal to be run in the software package R. This enables researchers to estimate the maximum dispersal distance with confidence intervals for plant species using measured traits as predictors. Easily obtainable trait data, such as dispersal syndrome (inferred from seed morphology) and growth form, enables predictions to be made for a large number of species

Accounting for long-term directional trends on year-to-year synchrony in species fluctuations

What determines the stability of communities under environmental fluctuations remains one of the most debated questions in ecology. Scholars generally agree that the similarity in year-to-year fluctuations between species is an important determinant of this stability. Concordant fluctuations in species abundances through time (synchrony) decrease stability while discordance in fluctuations (anti-synchrony) should stabilize communities. Researchers have interpreted the community-wide degree of synchrony in temporal fluctuations as the outcome of different processes. However, existing synchrony measures depend not only on year-to-year species fluctuations, but also on long-term directional trends in species composition, for example due to land-use or climate change. The neglected effect of directional trends in species composition could cause an apparent increase in synchrony that is not due to year-to-year fluctuations, as species that simultaneously increase (or decrease) in abundance over time will appear correlated, even if they fluctuate discordantly from year to year. The opposite pattern is also conceivable, where different species show contrasting trends in their abundances, thus overestimating year-to-year anti-synchrony. Therefore, trends in species composition may limit our understanding of potential ecological mechanisms behind synchrony between species. We propose two easily implementable solutions, with corresponding R functions, for testing and accounting for the effect of trends in species composition on overall synchrony. The first approach is based on computing synchrony over the residuals of fitted species trends over time. The second approach, applicable to already existing indices, is based on three-terms local variance, i.e. computing variance over three-years-long, movable windows. We demonstrate these methods using simulations and data from real plant communities under long-term directional changes, discussing when one approach can be preferred. We show that accounting for long-term temporal trends is necessary and that separation of effect of trends and year-to-year fluctuation provides a better understanding of ecological mechanisms and their connections with ecological theory.This research was supported by the Czech Science Foundation (GAČR 16-15012S and GAČR 17-05506S