Forecasting seed production in perennial plants: identifying challenges and charting a path forward

Abstract

Interannual variability and spatial synchrony of seed production, known as masting, have far-reaching ecological impacts including effects on forest regeneration and the population dynamics of seed consumers, predators, parasites, and diseases. Because the relative timing of management and conservation efforts in ecosystems dominated by masting species often determines their success, there is an urgent need to study masting mechanisms and develop anticipatory forecasting tools for seed production. In this study, we aim to establish seed production forecasting ("mast casts") as a new branch of the discipline. To assess the current state of the ability to model intrinsic and extrinsic drivers of masting, we evaluate the predictive capabilities of three models -foreMast, ΔT, and a sequential model based on the developmental steps of seed production - designed to predict seed production in trees using a pan-European dataset of Fagus sylvatica seed production as a case study. Our hindcasting analysis indicates that the models are moderately successful in recreating seed production dynamics, with the best-performing model achieving R2 = 0.66. The availability of high-quality data on prior seed production significantly improved the model's predictive power, with R2 = 0.78 in the sequential model, suggesting that effective seed production monitoring methods are crucial for creating reliable forecasting tools. In terms of extreme events, the models were 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. To create widely applicable tools, we need models that can make forecasts over large areas with readily available data. We summarize the current challenges and provide a roadmap to help advance the discipline and encourage the further development of mast forecasting.

Tail-dependence of masting synchrony results in continent-wide seed scarcity

“…The timing of that cue is conservative across the whole species range, as it is anchored to the summer solstice (Journé et al, 2024). These two parameters (temperature in T1 and T2) can be collapsed into one by taking their difference (ΔT) (Kelly et al, 2013).…”

“…The relationship between masting and ΔT was estimated with a generalized additive mixed model (GAMM) in which annual, per-site seed production was included as a response, site ID as a random intercept, and ΔT as a predictor. To accommodate among-site variation in methods of seed production monitoring, we scaled seed production for each site between 0 and 1 and őtted the GAMM with a beta family error term Journé et al, 2024).…”

“…In this study, we analyzed data from 99 populations of the major European species, European beech (Fagus sylvatica), sampled across the species' range, to investigate the presence of taildependence in regional masting synchrony. The regional synchronization of beech masting is attributed to the Moran effect (Vacchiano et al, 2017;Bogdziewicz et al, 2021aBogdziewicz et al, , 2023aJourné et al, 2024). However, previous research investigated mechanisms leading to largescale synchrony in overall masting pattern (Vacchiano et al, 2017;Bogdziewicz et al, 2023a), but a clear understanding of the relative importance of peaks and troughs synchrony remains unexplored.…”

Relatives reproduce in synchrony: kinship and individual condition shape intraspecific variation in masting phenotype

“…Periodicity is the variance that is concentrated at low frequency [35,39]. While the return intervals between large-seeding years is not fixed, periodicity allows to estimate the average difference among individuals (or population and species) in that return interval, which is relevant for seed consumers, food webs and conservation [13,39]. The comparisons of volatility and CV behaviour are detailed in [35], including the equations on how the metrics are derived.…”

“…As such, investigating variations in seed production patterns among individuals forms the fundamental basis for understanding the mechanisms behind masting [8,9]. Studying individuals is imperative to understand the contributions of genetic and environmental factors to the reproductive phenotype [11], clarify the role of population composition on masting [12], facilitate conservation planning [10] and enhance the ability to forecast mast seeding [13]. However, the inherent large variation in seed production among plants and years in masting [14] requires the implementation of long-term, individual-level monitoring programmes [15,16], that hinder efforts to disentangle drivers of intraspecific variations in mast seeding.…”