Filling in the gaps in survival analysis: using field data to infer plant responses to environmental stressors.

Abstract:

:Elucidating how organismal survival depends on the environment is a core component of ecological and evolutionary research. To reconcile high-frequency covariates with lower-frequency demographic censuses, many statistical tools involve aggregating environmental conditions over long periods, potentially obscuring the importance of fluctuating conditions in driving mortality. Here, we introduce a flexible model designed to infer how survival probabilities depend on changing environmental covariates. Specifically, the model (1) quantifies effects of environmental covariates at a higher frequency than the census intervals, and (2) allows partitioning of environmental drivers of individual survival into acute (short-term) and chronic (accumulated) effects. By applying our method to a long-term observational data set of eight annual plant species, we show we can accurately infer daily survival probabilities as temperature and moisture levels change. Next, we show that a species' water use efficiency, known to mediate annual plant population dynamics, is positively correlated with the importance of "chronic stress" inferred by the model. This suggests that model parameters can reflect underlying physiological mechanisms. This method is also applicable to other binary responses (hatching, phenology) or systems (insects, nestlings). Once known, environmental sensitivities can be used for ecological forecasting even when the frequency or variability of environments are changing.

journal_name

Ecology

journal_title

Ecology

authors

Tomasek BJ,Burghardt LT,Shriver RK

doi

10.1002/ecy.2778

subject

Has Abstract

pub_date

2019-10-01 00:00:00

pages

e02778

issue

10

eissn

0012-9658

issn

1939-9170

journal_volume

100

pub_type

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