Florian Hartig

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Advancing an interdisciplinary framework to study seed dispersal ecology

Noelle G Beckman, Clare E Aslan, Haldre S Rogers, Oleg Kogan, Judith L Bronstein, James M Bullock, Florian Hartig, Janneke HilleRisLambers, Ying Zhou, Damaris Zurell, Jedediah F Brodie, Emilio M Bruna, Robert Stephen Cantrell, Robin R Decker, Edu Efiom, Evan C Fricke, Katherine Gurski, Alan Hastings, Jeremy S Johnson, Bette A Loiselle, Maria N Miriti, Michael G Neubert, Liba Pejchar, John R Poulsen, Gesine Pufal, Onja H Razafindratsima, Manette E Sandor, Katriona Shea, Sebastian Schreiber, Eugene W Schupp, Rebecca S Snell, Christopher Strickland & Jenny Zambrano

AoB PLANTS, 12(2), plz048 (2020)
Cite this
@article{beckman2020advancing,
  author = {Noelle G Beckman and Clare E Aslan and Haldre S Rogers and Oleg Kogan and Judith L Bronstein and James M Bullock and Florian Hartig and Janneke HilleRisLambers and Ying Zhou and Damaris Zurell and Jedediah F Brodie and Emilio M Bruna and Robert Stephen Cantrell and Robin R Decker and Edu Efiom and Evan C Fricke and Katherine Gurski and Alan Hastings and Jeremy S Johnson and Bette A Loiselle and Maria N Miriti and Michael G Neubert and Liba Pejchar and John R Poulsen and Gesine Pufal and Onja H Razafindratsima and Manette E Sandor and Katriona Shea and Sebastian Schreiber and Eugene W Schupp and Rebecca S Snell and Christopher Strickland and Jenny Zambrano},
  title = {Advancing an interdisciplinary framework to study seed dispersal ecology},
  journal = {AoB PLANTS},
  volume = {12},
  number = {2},
  pages = {plz048},
  year = {2020},
  doi = {10.1093/aobpla/plz048},
}

DOI: 10.1093/aobpla/plz048
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Funding

This study was supported through funding by US National Science Foundation (DEB-1548194); National Socio-Environmental Synthesis Center under the US National Science Foundation (DBI-1052875); Swiss National Science Foundation (SNF) (PZ00P3_168136/1); German Science Foundation (DFG) (ZU 361/1-1).

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Abstract

Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity and interdependent processes occurring over multiple spatial and temporal scales. Current population models often use simple phenomenological descriptions of dispersal processes, limiting their ability to examine the role of population persistence and spread, especially under global change. To move seed dispersal ecology forward, we need to evaluate the impact of any single seed dispersal event within the full spatial and temporal context of a plant’s life history and environmental variability that ultimately influences a population’s ability to persist and spread. In this perspective, we provide guidance on integrating empirical and theoretical approaches that account for the context dependency of seed dispersal to improve our ability to generalize and predict the consequences of dispersal, and its anthropogenic alteration, across systems. We synthesize suitable theoretical frameworks for this work and discuss concepts, approaches and available data from diverse subdisciplines to help operationalize concepts, highlight recent breakthroughs across research areas and discuss ongoing challenges and open questions. We address knowledge gaps in the movement ecology of seeds and the integration of dispersal and demography that could benefit from such a synthesis. With an interdisciplinary perspective, we will be able to better understand how global change will impact seed dispersal processes, and potential cascading effects on plant population persistence, spread and biodiversity.

What the paper shows and why it matters

(AI-generated)

Seed dispersal matters for whether plant populations persist, spread and cope with global change, yet its contribution to their long-term dynamics is still poorly understood. The paper traces this to a split in the evidence: empirical studies are mostly short-term, local and limited to few species, while dispersal models often rest on simplified assumptions. Dispersal is also only one link in a long chain from flower to reproductive adult, so its demographic weight is hard to separate from that of later stages. The paper regards the seed dispersal effectiveness framework (Schupp et al. 2010), which weighs the quantity of seeds each dispersal vector delivers and the quality of that dispersal, as an important step towards handling the dependence of dispersal outcomes on their setting. The problem it takes on is how to evaluate a single dispersal event within the plant’s full life history, spatial setting and environment.

The paper argues that the contribution of seed dispersal to plant population dynamics can be quantified if data collection and modelling proceed together. It calls this closing the “seed dispersal loop”, a phrase it takes from Wang and Smith (2002). Models built alongside the data generate hypotheses that field work can test, are refined by the results, and can project dispersal consequences beyond what experiments allow. The paper develops this for two gaps: the movement ecology of seeds, including long-distance dispersal, and the link between dispersal and demography, where the effectiveness framework is combined with population models for local dynamics and for spread. It treats model choice as a trade-off, since simple models help generalisation while detailed ones serve predictions for one system, and names a balance between necessary complexity and tractability as the aim. It is a perspective that synthesises existing frameworks and studies, not new data.

Figure 1. To advance current knowledge gaps in seed dispersal ecology requires interdisciplinary collaboration in which researchers simultaneously and iteratively collect empirical data and develop mechanistic models that are integrated with statistics. From Beckman et al. (2020), AoB PLANTS, licensed under CC BY 4.0. Click the image to enlarge.

The paper offers a roadmap. It recommends collating scattered dispersal data sets and linking them to process-based models with Bayesian methods or, for simulation models whose likelihood cannot be written down, approximate Bayesian methods. Sensitivity analyses would show which parameters need better data, and coordinated networks with standardised protocols would fill remaining gaps. The paper presents these steps as a way towards better understanding and predicting how global change alters seed dispersal and, through it, plant persistence, spread and biodiversity.

References