Matthew A. Keller’s research while affiliated with Bucknell University and other places

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Publications (4)


2021 Abrahamson et al FL Fire Supplement ecm1444-sup-0001-appendixs1
  • Article
  • Full-text available

April 2021

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30 Reads

Ecological Monographs

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Christy R. Abrahamson

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Matthew A. Keller

Appendix S1 Appendix S1: Table S1. Dates and percentage of the 200-m transect burned by (E) escaped prescribed, (L) lightning, (P) prescribed, or (R) railroad-origin fires that impacted wet prairie and flatwoods stands during the 38-yr. study, 1977-2015. Mean % burned ± sample std. dev. and mean fire-return intervals (yr.) ± std. dev. from the initial documented fire for each transect are compared to Main and Menges' (1997) proposed fire-return intervals. Date of Fire Fire Type Wet Prairie Wet Prairie/ Flatwoods Cutthroat grass Flatwoods Wiregrass Flatwoods Wiregrass Flatwoods WS20 WS21 WS30 WS42 WSP1 % Burned % Burned % Burned % Burned % Burned

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Lessons from Four Decades of Monitoring Vegetation and Fire: Maintaining Diversity and Resilience in Florida’s Uplands

April 2021

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36 Reads

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3 Citations

The Bulletin of the Ecological Society of America

Worldwide, humans are altering the fire regimes of fire-prone ecosystems. Efforts to restore fire regimes in natural areas are usually guided by fire-management plans (FMP) using prescribed burning. We assessed an FMP by repeatedly sampling 11 Florida uplands impacted by 2 to 11 fires each during a 38-year period. Stands exhibited ecological resilience with little plant composition change and modest abundance shifts. Resilience was not eroded by repeated FMP-prescribed fires. Species richness and diversity were significantly higher at the end vs. beginning of our study, suggesting that FMP-applied fire regimes are within the range of those with which species evolved.


Percent change in species richness (number of species), evenness (Pielou’s J), and species diversity (Shannon H′), 1977–2014/2015. Percent change is shown for each stand and for the mean ± 95% confidence interval of all 11 stands. Sites are wet prairie WS20, wet prairie/flatwoods WS21, cutthroat grass flatwoods WS30, wiregrass flatwoods WS42 and WSP1, oak scrub WS26 and WSP2, oak scrub/rosemary scrub WS24 and WS25, rosemary scrub WS27, and hickory scrub WS29. Absolute richness, evenness, and diversity measures are available in Appendix S1 (Table S4, S5, Figs. S2, S3).
Top: nonmetric mutidimensional scaling (NMS) model for wet prairie/flatwoods WS21 based on species cover (proportion) over 10 sampling times, 1977–2015. A slow and thorough NMS analysis using a log(X + 1) transformation produced a two‐dimensional model with a stress of 3.4 and 0.0 instability, 42 iterations, R² for axis 1 = 0.74, R² for axis 2 = 0.22, and cumulative R² = 0.96. The occurrences of 11 fires are indicated. Blue lines originating from the centroid illustrate the magnitude (length) and direction of correlation with axes (slash pine [axis 1 r = 0.70], shortspike bluestem [axis 1 r = 0.96], gallberry [axis 1 r = 0.86], saw palmetto [axis 1 r = 0.91], fetterbush [axis 1 r = 0.70], wax myrtle [axis 1 r = 0.54], shiny blueberry [axis 2 r = −0.88], and dwarf huckleberry [axis 2 r = −0.87]). Bottom: percent cover for slash pine, saw palmetto, fetterbush, and shiny blueberry at wet prairie WS21 as a function of time, 1977–2015. Each red triangle along the x‐axis marks a fire. Dates of the 11 fires and their extents are available in Appendix S1: Table S1.
Top: NMS model for wiregrass flatwoods WS42 based on species cover (proportion) over 10 sampling times, 1977–2015. A slow and thorough NMS analysis using a log(X + 1) transformation produced a two‐dimensional model with a stress of 0.07 and 0.0 instability, 124 iterations, R² for axis 1 = 0.85, R² for axis 2 = 0.10, and cumulative R² = 0.95. The occurrences of five fires are indicated. Blue lines originating from the centroid illustrate the magnitude (length) and direction of correlation with axes (% Bare [axis 1 r = 0.96], scrub palmetto [axis 1 r = −0.78], wiregrass [axis 1 r = −0.78], saw palmetto [axis 1 r = −0.83], dwarf live oak and sand live oak [axis 1 r = −0.56, axis 2 r = 0.62], Atlantic St. John’s‐wort [Hypericum tenuifolium; axis 2 r = 0.71], and gopher apple [axis 2 r = 0.68]). Bottom: percent cover for wiregrass, saw palmetto, dwarf live oak and sand live oak, and percent bare ground (% Bare) at flatwoods WS42 as a function of time, 1977–2015. Each red triangle along the x‐axis marks a fire. Dates of the five fires and their extents are available in Appendix S1: Table S1.
Top: NMS model for oak scrub WS26 based on species cover (proportion) over 11 sampling times, 1977–2014. A slow and thorough NMS analysis using a log(X + 1) transformation produced a two‐dimensional model with a stress of 2.8 and 0.0 instability, 59 iterations, R² for axis 1 = 0.91, R² for axis 2 = 0.06, and cumulative R² = 0.97. The occurrences of four fires are indicated. Blue lines originating from the centroid illustrate the magnitude (length) and direction of correlation with axes (% Bare [axis 1 r = −0.93], prickly pear [axis 2 r = −0.85], sand live oak [axis 1 r = 0.76], saw and scrub palmettos [axis 1 r = 0.95], fetterbush and coastalplain staggerbush [axis 1 r = 0.76], and shiny blueberry [axis 1 r = 0.71, axis 2 r = 0.64]). Bottom: percent cover for shiny blueberry, fetterbush and coastalplain staggerbush, sand live oak, and saw and scrub palmetto at oak scrub WS26 as a function of time, 1977–2014. Each red triangle along the x‐axis marks a fire. Dates of the four fires and their extents are available in Appendix S1: Table S2.
Top: NMS model for oak/rosemary scrub WS25 based on species cover (proportion) over 10 sampling times, 1977–2014. A slow and thorough NMS analysis using no transformation produced a two‐dimensional model with a stress of 4.5 and 0.0 instability, 48 iterations, R² for axis 1 = 0.84, R² for axis 2 = 0.10, and the cumulative R² = 0.94. The occurrences of four fires are indicated. Blue lines originating from the centroid illustrate the magnitude (length) and direction of correlation with axes (% Bare [axis 1 r = −0.81], FL rosemary [axis 1 r = −0.62, axis 2 r = −0.66], scrub palmetto [axis 2 r = −0.83], saw palmetto [axis 1 r = 0.76], fetterbush [axis 1 r = 0.77], and oaks [axis 1 r = 0.85]). Bottom: percent cover for oaks, saw palmetto, and FL rosemary at oak/rosemary scrub WS25 as a function of time, 1977–2014. Each red triangle along the x‐axis marks a fire. Dates of the four fires and their extents are available in Appendix S1: Table S2.

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Lessons from four decades of monitoring vegetation and fire: maintaining diversity and resilience in Florida’s uplands

February 2021

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169 Reads

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9 Citations

Worldwide, humans are altering the fire regimes (fire‐return intervals, severity, seasonality) of fire‐prone ecosystems, fragmenting natural landscapes, and altering climates. Efforts to restore fire regimes in natural areas are usually guided by fire management plans (FMP) that rely on prescribed burning. Despite the common use of FMPs, limited efforts have gone to assessing vegetative and faunal responses. While some insights into responses to fire from short‐term studies are available, there is less knowledge about FMP outcomes applied over multiple decades. Peninsular Florida hosts many fire‐prone communities including globally threatened Florida scrub. We repeatedly sampled species composition and abundance during a 38‐yr period (1977–2015) at 11 upland stands including wet prairies, flatwoods, and Florida scrub (i.e., oak scrub, rosemary scrub, hickory scrub). A total of 22 fires impacted the stands with individual stands experiencing as few as 2 and up to 11 fires. There was no invasion of non‐native plants following fires and stands showed remarkable ecological resilience with limited change in species composition and modest abundance shifts due to differential recovery rates. Importantly, ecological resilience was not eroded with repeated fire. Species richness, evenness, and diversity were significantly higher at the end vs. beginning of our study, suggesting that current fire regimes are within the range of those with which species evolved. While resprouting shrubs and trees persevered under a range of fire‐return intervals, an obligate‐seeding shrub was adversely impacted by fires more frequent than FMP‐recommended intervals. Several lessons are apparent from our findings. Best practice should: use the full range of fire‐return variation at evolutionarily appropriate intervals; utilize natural fire seasons to the extent possible; compare outcomes and modify prescriptions as necessary to meet FMP goals; give special consideration to burn units with embedded associations of widely differing fire regimes than principal associations in order to maintain diversity of both associations; and account for climate change in FMPs since fire behavior, frequency, and community responses to fire will likely change in the coming decades. Outcomes of FMPs must be carefully evaluated to ensure prescriptions are evolutionarily appropriate and to ameliorate the impacts of altered climates.


Fire, land management, and vegetation change: Have we got our fire-management plans right?

August 2010

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16 Reads

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1 Citation

Background/Question/Methods Anthropogenic landscape changes have markedly altered fire-return patterns in many fire-prone ecosystems. Fire-management plans are aimed at restoring fire-return patterns that match those with which the organisms composing the ecosystem have evolved. Despite the common use of fire-management plans, little effort has gone into the assessment of the floral and faunal responses to prescribed treatments. The goal of our study is to assess the successes and shortcomings of fire-management planning using long-term vegetation change data. We used a 31-yr data set (1977-2008) to assess the consequences of the Archbold Biological Station fire-management plan on plant-species composition and cover at 13 permanent, 200-m line transects located in rosemary scrub, scrubby flatwoods, hickory sandhill, flatwoods, seasonal ponds, wet prairie/bayhead associations that have experienced differing fire occurrences. We used nonmetric multidimensional scaling (NMS) ordination to assess vegetative changes over time. Results/Conclusions Vegetation recovery following fires was rapid with associations expressing considerable resiliency. Species responses and NMS-determined community-structure changes confirmed that associations at some sites were stable in response to fire treatments but other associations diverged appreciably from their desired state. Conclusions include the importance of monitoring and fine-tuning of fire-return intervals. Long fire-return-interval associations embedded in shorter return-time matrix associations suffer if matrix fire-return intervals are applied in burn units with multiple vegetation associations. In our study, rosemary scrub with 20-60 yr fire-return intervals is embedded within a scrubby flatwoods matrix, which has a shorter (6-9 yr) fire-return interval. Three fires within 3 decades resulted in rosemary scrub strongly shifting towards scrubby flatwoods. Florida rosemary, the foundation species, declined from 50% cover in 1977 to only 6% by 2008, while oak coverage markedly increased as a consequence of short-interval fire returns. Similarly, frequent fire returns (7 fires during 3 decades) coupled with spring dry-season fires at a wet prairie site (2-5 yr return time) prevented the development and maturation of an embedded bayhead association (60-100 yr return time). Many fire-management plans provide relatively narrow ranges of fire-return intervals and extend prescribed burning beyond the natural fire season. If wrong, narrow intervals and burning outside the natural fire season have the potential to alter species composition and abundance. Our results suggest that best practice should use broad variation in fire-return times, continual comparison of management goals with actual vegetation cover, careful management of embedded associations, and use of the natural fire season for prescription burns.

Citations (2)


... In Florida, such studies The hatching delineates the presettlement extent of subtropical grasslands within the Kissimmee River region that once covered 2,037 km 2 in south-central Florida have focused on longleaf pine (Pinus palustris), a foundation species, wiregrass (Aristida beyrichiana), a keystone groundcover species, and saw-palmetto (Serenoa repens) (Abrahamson 1984b(Abrahamson , 1995Abrahamson and Abrahamson 2006;Fill et al. 2012;Wahlenberg 1946;Shibu et al. 2006). Post-fire recovery strategies and belowground organs were studied for Lake Wales Ridge xeric plant communities (Florida scrub and sandhills) (Abrahamson 1984a, b;Menges and Kohfeldt 1995;Maguire and Menges 2011;Menges et al. 2020;Saha et al. 2010) and for a smaller set of species from other Florida plant communities (Hierro and Menges 2002;Maliakal et al. 2000;Abrahamson et al. 2021). Some of these plants also occur in FSGs, particularly the geoxyle shrubs and subshrubs. ...

Reference:

Florida’s fiery subtropical grasslands: Growth forms, belowground organs, and post-fire recovery strategies
Lessons from Four Decades of Monitoring Vegetation and Fire: Maintaining Diversity and Resilience in Florida’s Uplands

The Bulletin of the Ecological Society of America

... Natural and anthropogenic disturbances (e.g., droughts, fires, highways) generate a myriad of impacts to natural communities. Fire is a recurrent disturbance in many ecosystems worldwide that influences the evolution of organisms and the composition of fire-prone communities (Abrahamson et al. 2021). We know a good deal about how fire impacts plant communities, but we know far less about fire's effects on insect herbivores and higher trophic levels. ...

Lessons from four decades of monitoring vegetation and fire: maintaining diversity and resilience in Florida’s uplands