Causal impact of fire on a globally rare wetland plant: a 40-year Bayesian time series analysis

Fire Ecology

Original Research

Gabriel Devin Cahalan¹  Deborah Landau¹  Prathiba Natesan Batley² 

[1] The Nature Conservancy, 425 Barlow Place, Suite 100, 20814, Bethesda, MD, USA;University of Louisville, 1905 South 1st Street, 40208, Louisville, KY, USA;

关键词: Bayesian;    Delmarva bay;    Dropwort;    Endangered species;    Interrupted time series;    Maryland;    Prescribed fire;    Single-case designs;    Tiedemannia;    Wetland;    Oxypolis canbyi;   

DOI  :  10.1186/s42408-022-00154-3

 received in 2022-07-22, accepted in 2022-10-25,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundCanby’s dropwort (Oxypolis canbyi (J.M. Coult. & Rose) Fernald) was listed as federally endangered in 1986, yet the species has continued to decline and is no longer found in 11 counties throughout its former range. The seasonal wetlands in which this forb occurs are disappearing from the landscape, often closing in and transitioning to wet forest or are drained and converted to agriculture. We document the effects of reintroducing fire to the only population of O. canbyi in Maryland and examine the resulting population increase using Bayesian interrupted time series analysis with a counterfactual.ResultsAfter cutting woody vegetation, 3.74 times more stems of dropwort per year were produced over the baseline of no intervention. Subsequently, after fire was reintroduced, 10.80 times more dropwort stems per year were produced in comparison to the time period after cutting woody vegetation. The counterfactual prediction showed that in the absence of intervention with fire, dropwort stem production would likely have declined.ConclusionsCutting woody vegetation set the stage for the growth of fine fuels by increasing sun exposure on wetland grasses. It was only after fire was reintroduced that the population of plants expanded significantly in extent and flower production. A process for model selection with a directed acyclic graph followed by Bayesian interrupted time series analysis and a counterfactual was useful for causal inference. Application of fire is an important step in the recovery of the federally endangered dropwort.

【 授权许可】

CC BY   
© The Author(s) 2023

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