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Abstract Biology has an increasing need to reconsider the tools used to assess the variability of measurements, in addition to their central tendency. More than 100 years after Pearson's publication, most biologists still use the “good old” Pearson's coefficient of variation, PCV, despite its documented flaws such as sensitivity to excess zero values and/or irrelevant low mean values, which may compromise its use in some biological applications. A new statistic was developed in 2017 by Kvålseth, KCV, which is easy to implement. Unlike PCV, KCV is bounded (between 0 and 1), and it can be computed from PCV, ensuring backward compatibility with past studies. In addition to simulated data, we used the recent MASTREE+ database comprising the time series of the fruiting dynamics of perennial plants worldwide to compare the properties of PCV and KCV. Using as a benchmark the loose hump‐shaped relationship between the interannual variability of fruiting and latitude, KCV led to significant increase in statistical power as it required almost half as many time series as PCV to detect the relationship. Perhaps most importantly, simulated data showed that KCV allows huge reductions in the length of time series required to estimate the population true variability, saving more than half the duration of long‐term monitoring if fruiting fluctuations are very large, which is common in perennial plant species. Compared to the widely used PCV, KCV has great accuracy for estimating and analysing variability in biology, while strongly increasing statistical power. Selecting appropriate tools to assess the variability of measurements is crucial, particularly where the variability is of primary biological interest. Using Kvålseth's KCV is a promising avenue to circumvent the well‐known issues of the former Pearson’ PCV, its properties remain to be explored in other fields of biology, for purposes other than purely statistical ones (e.g. estimating heritability or evolvability of traits).

Climate change effects on tree reproduction are poorly understood, even though the resilience of populations relies on sufficient regeneration to balance increasing rates of mortality. Forest‐forming tree species often mast, i.e. reproduce through synchronised year‐to‐year variation in seed production, which improves pollination and reduces seed predation. Recent observations in European beech show, however, that current climate change can dampen interannual variation and synchrony of seed production and that this masting breakdown drastically reduces the viability of seed crops. Importantly, it is unclear under which conditions masting breakdown occurs and how widespread breakdown is in this pan‐European species. Here, we analysed 50 long‐term datasets of population‐level seed production, sampled across the distribution of European beech, and identified increasing summer temperatures as the general driver of masting breakdown. Specifically, increases in site‐specific mean maximum temperatures during June and July were observed across most of the species range, while the interannual variability of population‐level seed production (CVp) decreased. The declines in CVp were greatest, where temperatures increased most rapidly. Additionally, the occurrence of crop failures and low seed years has decreased during the last four decades, signalling altered starvation effects of masting on seed predators. Notably, CVp did not vary among sites according to site mean summer temperature. Instead, masting breakdown occurs in response to warming local temperatures (i.e. increasing relative temperatures), such that the risk is not restricted to populations growing in warm average conditions. As lowered CVp can reduce viable seed production despite the overall increase in seed count, our results warn that a covert mechanism is underway that may hinder the regeneration potential of European beech under climate change, with great potential to alter forest functioning and community dynamics. [ABSTRACT FROM AUTHOR]

Biology has an increasing need to reconsider the tools used to assess the variability of measurements, in addition to their central tendency. More than 100 years after Pearson's publication, most biologists still use the "good old" Pearson's coefficient of variation, PCV, despite its documented flaws such as sensitivity to excess zero values and/or irrelevant low mean values, which may compromise its use in some biological applications.A new statistic was developed in 2017 by Kvålseth, KCV, which is easy to implement. Unlike PCV, KCV is bounded (between 0 and 1), and it can be computed from PCV, ensuring backward compatibility with past studies. In addition to simulated data, we used the recent MASTREE+ database comprising the time series of the fruiting dynamics of perennial plants worldwide to compare the properties of PCV and KCV.Using as a benchmark the loose hump‐shaped relationship between the interannual variability of fruiting and latitude, KCV led to significant increase in statistical power as it required almost half as many time series as PCV to detect the relationship. Perhaps most importantly, simulated data showed that KCV allows huge reductions in the length of time series required to estimate the population true variability, saving more than half the duration of long‐term monitoring if fruiting fluctuations are very large, which is common in perennial plant species. Compared to the widely used PCV, KCV has great accuracy for estimating and analysing variability in biology, while strongly increasing statistical power.Selecting appropriate tools to assess the variability of measurements is crucial, particularly where the variability is of primary biological interest. Using Kvålseth's KCV is a promising avenue to circumvent the well‐known issues of the former Pearson' PCV, its properties remain to be explored in other fields of biology, for purposes other than purely statistical ones (e.g. estimating heritability or evolvability of traits). [ABSTRACT FROM AUTHOR]

Summary: Interannual variability of seed production, known as masting, has far‐reaching ecological impacts including effects on forest regeneration and the population dynamics of seed consumers. Because the relative timing of management and conservation efforts in ecosystems dominated by masting species often determines their success, there is a need to study masting mechanisms and develop forecasting tools for seed production. Here, we aim to establish seed production forecasting as a new branch of the discipline. We evaluate the predictive capabilities of three models – foreMast, ΔT, and a sequential model – designed to predict seed production in trees using a pan‐European dataset of Fagus sylvatica seed production. The models are moderately successful in recreating seed production dynamics. The availability of high‐quality data on prior seed production improved the sequential model's predictive power, suggesting that effective seed production monitoring methods are crucial for creating forecasting tools. In terms of extreme events, the models are better at predicting crop failures than bumper crops, likely because the factors preventing seed production are better understood than the processes leading to large reproductive events. We summarize the current challenges and provide a roadmap to help advance the discipline and encourage the further development of mast forecasting. [ABSTRACT FROM AUTHOR]

Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long‐lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time‐series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population‐level time‐series from 974 species in 66 countries. The mean and median time‐series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well‐studied species, MASTREE+ includes extensive replication of time‐series across geographical and climatic gradients. Here we describe the open‐access data set, available as a.csv file, and we introduce an associated web‐based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long‐lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics. [ABSTRACT FROM AUTHOR]

Climate change is reshaping global vegetation through its impacts on plant mortality, but recruitment creates the next generation of plants and will determine the structure and composition of future communities. Recruitment depends on mean seed production, but also on the interannual variability and among-plant synchrony in seed production, the phenomenon known as mast seeding. Thus, predicting the long-term response of global vegetation dynamics to climate change requires understanding the response of masting to changing climate. Recently, data and methods have become available allowing the first assessments of long-term changes in masting. Reviewing the literature, we evaluate evidence for a fingerprint of climate change on mast seeding and discuss the drivers and impacts of these changes. We divide our discussion into the main characteristics of mast seeding: interannual variation, synchrony, temporal autocorrelation and mast frequency. Data indicate that masting patterns are changing but the direction of that change varies, likely reflecting the diversity of proximate factors underlying masting across taxa. Experiments to understand the proximate mechanisms underlying masting, in combination with the analysis of long-term datasets, will enable us to understand this observed variability in the response of masting. This will allow us to predict future shifts in masting patterns, and consequently ecosystem impacts of climate change via its impacts on masting. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'. [ABSTRACT FROM AUTHOR]

Highly variable and synchronised production of seeds by plant populations, known as masting, is implicated in many important ecological processes, but how it arises remains poorly understood. The lack of experimental studies prevents underlying mechanisms from being explicitly tested, and thereby precludes meaningful predictions on the consequences of changing environments for plant reproductive patterns and global vegetation dynamics. Here we review the most relevant proximate drivers of masting and outline a research agenda that takes the biology of masting from a largely observational field of ecology to one rooted in mechanistic understanding. We divide the experimental framework into three main processes: resource dynamics, pollen limitation and genetic and hormonal regulation, and illustrate how specific predictions about proximate mechanisms can be tested, highlighting the few successful experiments as examples. We envision that the experiments we outline will deliver new insights into how and why masting patterns might respond to a changing environment. [ABSTRACT FROM AUTHOR]

• Long time-series of seed production are critical to masting studies. • Dendrochronology may enable the extension of observational records of masting. • Quercus ring-width does not respond strongly to masting. • Analysing seasonwood or subsampling super-producers does not enhance the signal. • Quercus tree-rings show low potential for the reconstruction of masting. Oak (Quercus) are a dominant and important tree genus in the Central Hardwood Region (USA) due to their commercial timber value, and food value of their protein-rich seed – acorns – to wildlife. Acorn production is characteristic of masting, with highly variable crop sizes that are synchronized within populations, but with consideration variation among individual trees. Critical to acorn masting studies are longitudinal datasets, which are often difficult to maintain due to a host of constraints. One possible approach to extending mast datasets involves the use of dendrochronology, where tree-ring-width variability serves as a proxy for annual acorn production. In this study, we addressed the future utility of mast reconstructions by examining relationships between acorn production, climate, and tree-ring data from five common oak species in southern Appalachian hardwood forests (Bent Creek Experimental Forest). We found little evidence to suggest that acorn production influences seasonally resolved tree-ring data, even when we considered early and latewood growth separately, or when we analyzed trees with substantially higher overall investment in acorn production (i.e., super producers). Monthly climate (temperature, precipitation) correlated to acorn production was strongest when lagged, which could indicate weather conditions were more important for phases of flower production and fertilization than acorn maturation. However, relationships were relatively weak, indicating limited potential for the forecasting of acorn crops, or for reconstruction methods that combine observed weather data and tree-ring responses to masting. Overall, our findings provide some support for the role of resource dynamics in regulating masting in oaks, but relationships between radial growth and acorn production are not sufficiently strong, at least in this location, to permit tree-ring based reconstruction of masting in these oak species. [ABSTRACT FROM AUTHOR]

Interannual variation in radial growth is influenced by a range of physiological processes, including variation in annual reproductive effort, although the importance of reproductive allocation has rarely been quantified. In this study, we use long stand-level records of annual seed production, radial growth (tree ring width) and meteorological conditions to analyse the relative importance of summer drought and reproductive effort in controlling the growth of Fagus sylvatica L., a typical masting species. We show that both summer drought and reproductive effort (masting) influenced growth. Importantly, the effects of summer drought and masting were interactive, with the greatest reductions in growth found in years when high reproductive effort (i.e., mast years) coincided with summer drought. Conversely, mast years that coincided with non-drought summers were associated with little reduction in radial growth, as were drought years that did not coincide with mast years. The results show that the strength of an inferred trade-off between growth and reproduction in this species (the cost of reproduction) is dependent on environmental stress, with a stronger trade-off in years with more stressful growing conditions. These results have widespread implications for understanding interannual variability in growth, and observed relationships between growth and climate. [ABSTRACT FROM AUTHOR]

Tree growth is frequently linked to weather conditions prior to the growing season but our understanding of these lagged climate signatures is still poorly developed. We investigated the influence of masting behaviour on the relationship between growth and climate in European Beech (Fagus sylvatica L.) using a rare long-term dataset of seed production and a new regional tree ring chronology. Fagus sylvatica is a masting species with synchronous variations in seed production which are strongly linked to the temperature in the previous two summers. We noted that the weather conditions associated with years of heavy seed production (mast years) were the same as commonly reported correlations between growth and climate for this species. We tested the hypothesis that a trade-off between growth and reproduction in mast years could be responsible for the observed lagged correlations between growth and previous summers' temperatures. We developed statistical models of growth based on monthly climate variables, and show that summer drought (negative correlation), temperature of the previous summer (negative) and temperature of the summer 2 years previous (positive) are significant predictors of growth. Replacing previous summers' temperature in the model with annual seed production resulted in a model with the same predictive power, explaining the same variance in growth. Masting is a common behaviour in many tree species and these findings therefore have important implications for the interpretation of general climate-growth relationships. Lagged correlations can be the result of processes occurring in the year of growth (that are determined by conditions in previous years), obviating or reducing the need for 'carry-over' processes such as carbohydrate depletion to be invoked to explain this climate signature in tree rings. Masting occurs in many tree species and these findings therefore have important implications for the interpretation of general climate-growth relationships. [ABSTRACT FROM AUTHOR]

Masting is the highly variable and synchronous production of seeds by plants. Masting can have cascading effects on plant population dynamics and forest properties such as tree growth, carbon stocks, regeneration, nutrient cycling, or future species composition. However, masting has often been missing from forest models. Those few that simulate masting have done so using relatively simple empirical rules, and lack an implementation of process-based mechanisms that control such events. Here we review more than 200 published papers on mechanistic formulations of masting, and summarize how the main processes involved in masting and their related patterns can be incorporated in forest models at different degrees of complexity. Our review showed that, of all proximate causes of masting, resource acquisition, storage and allocation were the processes studied most often. Hormonal and genetic regulation of bud formation, floral induction, and anthesis were less frequently addressed. We outline the building blocks of a general process-based model of masting that can be used to improve the oversimplified functions in different types of forest models, and to implement them where missing. A complete implementation of masting in forest models should include functions for resource allocation and depletion, and for pollination, as regulated by both forest structure and weather in the years prior to seed production. When models operate at spatio-temporal scales mismatched with the main masting processes, or if calibration data are not available, simulation can be based on parameterizing masting patterns (variability, synchrony, or frequency). Also, observed masting patterns have the potential to be used as “reality checks” for more process-based forest models wishing to accurately reproduce masting as an emergent phenomenon. [ABSTRACT FROM AUTHOR]