1. ABDULLAH AHMADI, BAHAREH KHORRAMI, NOORULLAH MURADI
Avian species richness in a frequently burned
ecosystem:
A link between pyrodiversity and biodiversity
Marcelo H. Jorge · L. Mike Conner · Elina P. Garrison · Michael J. Cherry

2. • Fire influences the extent and distribution of ecosystems
around the world. Environmental heterogeneity is a
primary driver of species richness, however fire’s proposed
role in the maintenance of heterogeneity has been largely
understudied until recently.
• This variation creates landscape heterogeneity which can
enhance biodiversity in a manner similar to the
Hutchinsonian niche concept in that heterogeneity
increases niche space and consequently species richness.
• Mosaic burning, an application of the pyrodiversity theory,
is commonly promoted throughout many fire-dependent
systems across the world.
Introduction
https://www.nwaonline.com/news/2022/sep/22/p
rescribed-burns-common-in-farming-but-farmers/

3. Conti…
• Fire-mediated changes in habitat structure and food resources can result in similar
responses within a guild because of traits shared across guide members.
• However, guild members that share a functional trait such as diet selection, can
also vary in terms of other traits such as nesting requirements, which can result in
variable responses to fire effects within a guild.
• We investigated the effects of fire history on avian community dynamics in a
frequently burned LLP ecosystem.
Introduction

4. Conti…
• We tested the ‘pyrodiversity begets biodiversity’ hypothesis by examining the
effect of spatial variation in heterogeneity in time-since-fire values on species
richness at community and guild levels.
• We tested this hypothesis at a scale that can inform fire management plans with
the goal of promoting biodiversity in LLP ecosystems. Our system was ideal to test
this hypothesis because, relative to studies which have fire effects that vary in
size, intensity, and frequency.
• The goal of our work was to examine the influence of fire and heterogeneity in fire
history relative to other ecological drivers such as soil productivity, land cover,
and habitat structure, and to facilitate conservation of biodiversity and improve
our understanding of avian communities in frequently burned conifer ecosystem.
Introduction

5. • We predicted pyrodiversity would increase species richness at the community
level, but fire history would have greater effects on the guild level because
members of a guild likely have similar responses to fire effects on nesting or
foraging resources.
Introduction

6. Study area
• This study was located on Camp Blanding Joint Training Center and
Wildlife Management Area in northeastern Florida.
• The Land was designed for military training with a 6500-ha ‘Impact
Zone’ where artillery strikes are targeted, as well as forest
management, sand mining, and wildlife habitat maintenance and
restoration.
• In the area during the previous 40 years, prescribed burning was used
for ecological restoration

7. Study design
• For recoding Arc-GIS 10.3 and a programmable acoustic recorder (to record the
avian vocalizations) is used to randomly generate 34 survey sites, separated by 3
km
• Acoustic surveys during breeding and chick-rearing seasons are conducted at
each site
• 3 to 5 minutes surveys are recorded at sunrise, 1 and 2 hours after sunrise
• 53 target species in frequently burned pine forests are grouped by nesting
behavior and forging behavior
https://www.wildlifeacoustics.com
/products/song-meter-sm4
https://wildlife.org/innovative-foraging-

8. Method and data analysis
Study design
• To evaluate the effects of environmental covariates, a 500 m buffer around
each survey site is created, which represents the fire history characteristics,
land cover type, soil productivity and forest structure.
• A spatiotemporal fire covariates that reflected the fire conditions on site is
created
• They classified Land cover into 3 types: hardwood forests, pine forests and
open areas
• A spatially explicit soil productivity metric using the US DAPI is created to
identify soil productivity

9. Data analysis
• The hierarchical Bayesian multispecies site occupancy models with parameter-expanded data
augmentation is used
• These models estimate the effects of variables on the occupancy of individual species, which is used to
estimate the effects of those variables on species richness
• The advantage of using this model is for both species-level effects as well as aggregated effects of
variables for a community
• To draw samples for each model two Markov chain Monte Carlo chains and Gibbs Sampler in the jagsUI
package in R is used

10. Results:
• Recorded 2590 and 2690 bird detections during the 6-day sampling periods in 2017 and 2018.
• Detected 48 of 53 target species at least once during the survey.
• The five species that did not detect were:

11. Florida Scrub Jay
Florida Grasshopper Sparrow
Hermith Thrush
Killdeer
Black-and-white Warbler
https://www.audubon.org/

12. • American crow was the most detected
species.
https://www.allaboutbirds.org/guide/American_Crow/id
• Mean community occupancy
probability was 36%;
• Average species detection
probability was 17%;
• Naïve mean species richness for the
48 detected species was 14.09
species per site.
• In the study:

13. 1- Pyrodiversity;
2- Distance to pine forest;
3- Distance to hardwood forest;
4- Canopy cover with a fixed effect of year on both the occupancy and detection
portion of the model.
Canopy cover, area of leaves, branches, and stems of trees covering the ground when viewed from above.
The model that used for predicting species richness at the community level used
the following parameters:

14. • Although included in the top model, the credible intervals for distance to hardwood
forests, distance to pine forests, canopy cover, and survey year overlapped zero and
were considered uninformative parameters.
• At the species level, within the community model, only the probability of Northern
Parula (Setophaga americana) occupancy increased with pyrodiversity (β = 0.299, CrI
0.042–0.718).
• At the community level, species richness increased with pyrodiversity (β = 0.136, CrI
0.009–0.260).
• The model shows:

15. A credible interval is an Interval within which
an unobserved parameter value falls with a
particular probability.
Solid red lines: the community posterior mean;
Dashed: credible interval;
The blue line: individual species credible interval.

16. • The study supports the “pyrodiversity begets biodiversity hypothesis” at the community
level and at a scale relevant to linking theory and practice.
• Did not identify any factors that strongly influenced richness at the guild and community
levels, reaffirming there is not one fire prescription that universally benefits avian species.
• The study also supports the findings that pyrodiversity, as defined by heterogeneity in
time since fire, benefits biodiversity at scales applicable to management action.
Discussion

17. • The study results highlight the importance of studying multiple levels of organization
simultaneously to gain a more complete understanding of the effects of fire on avian
community dynamics.
Suggestions
• The results and characterization of pyrodiversity suggests that managers can promote
avian community diversity by implementing burn regimes that increase proximity of
time since fire values.
• An important next step is to test the effect of diversity of other fire attributes including
seasonality and severity on biodiversity to determine if these fire attributes are
important drivers of avian biodiversity.

18. • A concurrent research found coyotes (Canis lupus) and bobcats (Lynx rufus) had lower
relative abundances in areas of greater pyrodiversity, suggesting that the use of fire in
this study system may also have altered predator distributions, which may benefit avian
species richness.
• The use of fire has been shown to promote avian species richness and has been shown to
alter predator distributions or activity. But this study is unique for they tested the
“pyrodiversity begets biodiversity hypotheses” which can be paired with a concurrent
study of predator responses.
One more thing:

19. • The underlying mechanisms behind the ‘pyrodiversity beget biodiversity’ hypothesis
remains an open question and identifying these mechanisms will benefit managers in
promoting avian biodiversity.
Conclusion

20. Thank you!
Questions & Suggestions?