The role of large environmental noise in masting: General model and example from pistachio trees

Lyles, Danielle; Rosenstock, Todd S.; Hastings, Alan; Brown, Patrick H.

doi:10.1016/j.jtbi.2009.04.015

Cited by 48 publications

(60 citation statements)

References 51 publications

(67 reference statements)

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“…When the spatial distribution of a given population (or substance) exhibits a considerable variability in space, which is rather typical in ecology [25,43,53 -56] and agroecology [13,36,37,57], the number of collected samples may not always be sufficient to resolve the details of the spatial configuration. Moreover, information about the spatial pattern of the population density distribution, e.g.…”

Section: Discussionmentioning

confidence: 99%

“…Synchronization is frequently reported in the literature [15][16][17][18][19][29][30][31][32][33][34][35][36][37]; however, technical details of the data collection, such as the properties of the sampling grid, are often omitted. Also, the effect of the spatial pattern in the distribution of the corresponding populations usually remains obscure.…”

Section: Introductionmentioning

confidence: 99%

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Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

Petrovskaya

Petrovskii

2017

J. R. Soc. Interface.

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Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error-i.e. the difference between the true value of the population size and its estimated value-can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe 'ghost synchronization' when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

Petrovskaya

Petrovskii

2017

J. R. Soc. Interface.

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“…Mast seeding is the "synchronous highly variable seed production among years by a population of plants" (Kelly 1994), observed in a wide range of plant species including Fagus, Fuscospora, Quercus, Chionochloa, Dipterocarp and pistachio (Lyles et al 2009;Pearse et al 2014;Sakai 2002;Schauber et al 2002). Total annual seed production is usually continuous rather than bi-modal, making it difficult (and sometimes foolhardy: (Kelly 1994)) to categorize individual years as mast or non-mast.…”

Section: Introductionmentioning

confidence: 99%

“…Being able to predict when a mast event is imminent is crucial for managers of both crop species (e.g. pistachio, (Lyles et al 2009)) and ecosystems where masting may precipitate a trophic meltdown (e.g. invasive rodent consumers in Fuscospora forests in New Zealand (Ruscoe et al 2005)).…”

Section: Introductionmentioning

confidence: 99%

Assessing the efficacy of population-level models of mast seeding

Holland

James

2014

Theor Ecol

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We compare five models of mast seeding: the wellestablished resource-based model of Isagi et al. (more recent Delta temperature (ΔT) model of Kelly et al. (Ecol Lett 16:90-98, 2013), the resource model of Pearse et al. (Oikos 123:179-184, 2014) and the long-used temperature model. We discuss fitting methods for each model and compare the theoretical overlap between the models. Population level data from 28 seed sets and corresponding mean summer temperature are used and the error of each model is compared. On average, the ΔT model provides a better fit than the other models tested.

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“…Exogenous mechanisms remain the most common explanation for synchronous mast seeding (Koenig and Knops 1998;Schauber et al 2002;Kelly and Sork 2002;Kelly et al 2008). However, three modeling studies have shown that endogenous resource dynamics are necessary to explain synchrony, whereas exogenous factors alone cannot (Rees et al 2002;Crone et al 2005;Lyles et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Desynchronization and re‐synchronization of reproduction by Astragalus scaphoides, a plant that flowers in alternate years

Crone

2012

Ecological Research

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Mast seeding, the synchronous seed production by plants at irregular intervals, has been widely studied from the perspective of its fitness benefits, but much less is known about the proximate factors that cause plants to reproduce synchronously. In this article, I follow up on more than two decades of research investigating proximate mechanisms of mast seeding by Astragalus scaphoides, an iteroparous perennial forb. We use longterm monitoring in relation to two environmental manipulations to evaluate the importance of exogenous environmental factors versus endogenous feedbacks for synchrony in this species. Our past research showed that synchrony in this species is explained by the pollencoupling hypothesis: plants that flower synchronously set seed and deplete stored resources, whereas plants that happen to flower asynchronously are pollen limited, set fewer seeds, and do not deplete resources, and flower again until they are resynchronized. Continued monitoring of two experimental manipulations, water addition, and flower removal, provides additional support for this model, and also reveals subtle effects of water availability on synchrony. Water addition decreased flowering, rather than increasing it as expected based on simple correlations with weather variables, suggesting that precipitation does not synchronize reproduction. Exogenous drivers are generally considered to be the primary synchronizing factors in plant reproduction. Our work in this system suggests that endogenous feedbacks may be more important than has been previously assumed.

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The role of large environmental noise in masting: General model and example from pistachio trees

Cited by 48 publications

References 51 publications

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

Assessing the efficacy of population-level models of mast seeding

Desynchronization and re‐synchronization of reproduction by Astragalus scaphoides, a plant that flowers in alternate years

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