About

Jason Vogel is an Associate Professor in the School of Forest, Fisheries, and Geomatics Sciences at the University of Florida. His research group studies forest nutrient cycling, structure, and growth, with a focus on how these forest processes and attributes respond to climate change, disturbance, and management decisions. He investigates how silviculture can be used to restore and maintain the attributes of forests that are important to society. Vogel's educational background includes a PhD from the University of Alaska-Fairbanks obtained in 2004, an MSc from the University of Wisconsin-Madison in 1997, and a BSc from the same university in 1994.

Research topics

• Geography
• Environmental science
• Computer Science
• Ecology
• Artificial Intelligence
• Geology
• Atmospheric sciences
• Meteorology
• Chemistry
• Remote sensing
• Soil science
• Mathematics
• Biology
• Materials science

Selected publications

• Do soil enzymes respond to silvicultural management?

  Forest Ecology and Management · 2025-03-14 · 2 citations

  article
  PublisherDOI

• Replacing Peat with Biochar: Can Adding Biochar to Peat Moss Reduce Carbon Dioxide Fluxes?

  Sustainability · 2025-05-03 · 1 citations

  articleOpen accessSenior author

  Replacing peat with biochar in nursery growing media could help offset carbon emissions and reduce environmental degradation caused by mining wetlands for peat. However, the effects of replacing peat with biochar on CO2 emissions are little known. In this study, we measured CO2 flux rates in growing media with varying proportions of biochar (0%, 25%, 50%, 75%, and 100% levels) as a replacement for peat. Overall, we found that higher biochar levels (≥75%) in growing media resulted in a reduction in CO2 fluxes compared to pure peat (0% biochar), approaching near-zero emissions. In contrast, lower biochar levels (≤25%) had little to no effect on CO2 fluxes. When the growing media was fertigated or irrigated, we observed a decrease in CO2 fluxes in mixes containing 25%, 50%, and 75% biochar, though this effect was absent in mixes that were pure peat or pure biochar, suggesting that irrigation and fertilization regimes could be strategized to enhance biochar’s carbon emission impacts. Our study offers insights into the development of sustainable growing media to reduce the carbon footprint of horticulture and forestry nursery production systems and may help balance productivity with environmental conservation.

  PublisherOA PDFDOI

• Growth dynamics of longleaf pine during conversion to uneven-aged stands

  Forest Ecosystems · 2025-02-14 · 1 citations

  articleOpen accessSenior author

  A growing recognition that uneven-aged silviculture can offer multiple benefits to forested ecosystems has encouraged some landowners in the southern region of the United States to convert even-aged pine stands into multi-aged stands. For shade-intolerant pines of the southern United States, however, few studies have examined residual tree growth following silvicultural treatments that convert even-aged stands to multi-aged stands. Understanding the growth response of residual trees to different kinds of stand conversion treatments is critical to stand development and sustainability, as trees must be recruited into larger size classes during the conversion process to develop the desired stand structure and maintain productivity. In this study, we utilized a replicated, long-term silvicultural experimental trial in the southeastern United States to assess the effects of two cutting treatments (dispersed “single tree cutting” that created small canopy gaps and the “patch cutting” that created 0.1–0.8 ​ha patch openings) and an uncut control on the 14-year growth (∼cutting cycle length) of residual longleaf pine ( Pinus palustris Mill.) trees. We found that tree growth, measured as mean basal area increment (BAI), was significantly higher following patch cutting (mean BAI of 16.97 ​cm 2 ) compared to both the single tree cutting (13.33 ​cm 2 ) and the uncut control (12.68 ​cm 2 ) ( p ​< ​0.001). In patch cutting, the size of the patch opening, the location of trees surrounding the patch opening, and the position of the tree canopy all had a significant effect on BAI. Trees surrounding patch openings of 0.4 ​ha exhibited greater growth, with a mean BAI of 19.24 ​cm 2 , compared to those surrounding 0.1 and 0.8 ​ha patch openings, which had mean BAI values of 15.89 and 15.71 ​cm 2 , respectively ( p ​< ​0.001). The position of a tree around the patch opening also influenced tree growth, as residual trees more to the North, South, and East sides exhibited significantly higher mean BAI than trees on the West side of the patch openings ( p ​< ​0.001). However, distance from the patch opening border did not significantly affect the mean BAI ( p ​= ​0.522). In all treatments, dominant and co-dominant trees exhibited higher BAI than intermediate and overtopped trees, indicating that tree canopy position significantly influenced tree growth ( p ​< ​0.001). Understanding how residual trees grow after these silvicultural treatments is crucial for thoroughly assessing their efficacy with longleaf pine. This study's findings will enhance our understanding of stand dynamics during stand conversion and help land managers anticipate the growth of longleaf pine into larger size categories after single tree and patch cuttings.

  PublisherDOI

• A retrospective on the performance and viability of planted Southeastern-Mediterranean conifer forests as determined by abiotic factors controlling water availability

  Forestry An International Journal of Forest Research · 2025-11-10

  article

  Abstract Water availability limits the growth of Mediterranean forests. Projected warming and drying could pose a risk to maintaining the cover of these forests. Water availability is primarily determined by precipitation, but other climatic, topographic, and edaphic factors also modify soil water content and evaporative demand. Here, we assessed how topographic aspect, elevation, and bedrock type interacted with precipitation to affect mature (&amp;gt;40 years) Pinus halepensis (native to the region, n = 96) and P. brutia (exotic to the region, n = 74) forests in Mediterranean Israel. Individual tree (height, stem diameter, and increment) and stand metrics (stem density, basal area, NDVI, natural regeneration, and understory growth) were analyzed with multiple regression models. The performance of P. halepensis forests was mainly and positively influenced by precipitation (40%–92% of explained variation), with additional positive influence of north- vs. south-facing aspects and negative influence of elevation. For P. brutia forests, precipitation × bedrock interactions and elevation (positive effect) were most significant for stand metrics, while aspect × elevation interactions were most significant for tree characteristics. Natural regeneration in P. brutia forests was generally minor, while regeneration of P. halepensis was substantial and responded mostly and positively to soft bedrock types. In both species, understory growth increased with precipitation. The differences between the two species could reflect their respective sensitivities to water limitations and to other climatic and/or topo-edaphic factors (e.g. temperature). Our study offers new insights on how abiotic factors influence forest performance, and we propose site- and species-specific recommendations for managing these water-limited forest ecosystems.

  PublisherDOI

• Comparing Terrestrial and Mobile Laser Scanning Approaches for Multi-Layer Fuel Load Prediction in the Western United States

  Remote Sensing · 2025-08-08 · 1 citations

  articleOpen access

  Effective estimation of fuel load is critical for mitigating wildfire risks. Here, we evaluate the performance of mobile laser scanning (MLS) and terrestrial laser scanning (TLS) to estimate fuel loads across multiple vegetation layers. Data were collected in two forest regions: the North Kaibab (NK) Plateau in Arizona and Monroe Mountain (MM) in Utah. We used random forest models to predict vegetation attributes, evaluating the performance of full models and transferred models using R2, RMSE, and bias. The MLS consistently outperformed the TLS system, particularly for canopy-related attributes and woody biomass components. However, the TLS system showed potential for capturing canopy structure attributes, while offering advantages like operational simplicity, low equipment demands, and ease of deployment in the field, making it a cost-effective alternative for managers without access to more complex and expensive mobile or airborne systems. Our results show that model transferability between NK and MM is highly variable depending on the fuel attributes. Attributes related to canopy biomass showed better transferability, with small losses in predictive accuracy when models were transferred between the two sites. Conversely, surface fuel attributes showed more significant challenges for model transferability, given the difficulty of laser penetration in the lower vegetation layers. In general, models trained in NK and validated in MM consistently outperformed those trained in MM and transferred to NK. This may suggest that the NK plots captured a broader complexity of vegetation structure and environmental conditions from which models learned better and were able to generalize to MM. This study highlights the potential of ground-based LiDAR technologies in providing detailed information and important insights into fire risk and forest structure.

  PublisherOA PDFDOI

• Upscaling Frameworks Drive Prediction Accuracy and Uncertainty When Mapping Aboveground Biomass Density from the Synergism of Spaceborne LiDAR, SAR, and Passive Optical Data

  Remote Sensing · 2025-07-08 · 6 citations

  articleOpen access

  Accurate mapping of aboveground biomass density (AGBD) is vital for ecological research and carbon cycle monitoring. Integrating multi-source remote sensing data offers significant potential to enhance the accuracy and coverage of AGBD estimates. This study evaluated three upscaling frameworks for integrating GEDI LiDAR, SAR, and optical satellite data to create wall-to-wall AGBD maps. The frameworks tested in this paper were: (1) a single-step approach using optical imagery, (2) a two-stage approach with GEDI-derived variables, and (3) a three-stage approach combining imagery and in situ-derived allometries. Internal validation showed that framework 1 achieved the lowest root mean square difference (%RMSD) of 53.3% and highest coefficient of determination (R2) of 0.53. An independent external validation of the AGBD map was performed using in situ observations, also revealing that framework 1 was the most accurate (%RMSD = 39.3% and R2 = 0.93), while frameworks 2 and 3 were less accurate (%RMSD = 54.7, 44.7 and R2 = 0.95, 0.90, respectively). Herein, we show that upscaling frameworks significantly impacted AGBD map uncertainty and the magnitude of estimate differences. Our findings suggest that upscaling framework 1 based on a single step approach was the most effective for capturing detailed AGBD variations, while careful consideration of model sensitivity and map uncertainties is essential for reliable AGBD estimation. This study provides valuable insights for advancing forest AGBD monitoring and highlights the potential for further enhancements in remote sensing methodologies.

  PublisherOA PDFDOI

• Cyclones reduce growth and mortality differences between liana‐laden and liana‐free trees in Belize

  Journal of Ecology · 2025-07-16 · 2 citations

  articleOpen access

  Abstract Lianas—woody vines—are often abundant and strong competitors in tropical forests, shaping forest structure and diversity by affecting tree growth and mortality. Tropical cyclones damage trees and create canopy openings that favour lianas, but the combined effects of lianas and cyclones on tree dynamics remain largely unexplored. Using long‐term forest inventory data from Belize along with estimates of cyclone wind exposure, we assessed how cyclone disturbances influence liana prevalence (i.e. the proportion of liana‐laden trees in a stand) and how cyclone–liana interactions modulate tree growth and mortality patterns. Cyclone wind exposure reduced liana prevalence in the short term (5‐ and 10‐year intervals) but increased it over a longer timeframe (20 years). Precipitation also strongly influenced liana prevalence, with drier conditions promoting tree infestation by lianas. Lianas typically suppressed tree growth and increased mortality risk. However, increasing wind exposure diminished these effects, causing growth rates and mortality risk of liana‐free and liana‐laden trees to converge. Liana‐free tree mortality risk rose more steeply, showing a trend towards higher mortality risk than liana‐laden trees under high wind exposure, potentially due to the stabilising benefits of lianas and their association with cyclone‐resistant tree species. Synthesis . Our findings reveal a time‐dependent influence of cyclones on liana prevalence and demonstrate that cyclones moderate liana effects on growth and mortality by favouring liana‐prone, cyclone‐resistant species while disproportionately impacting liana‐free trees. These insights highlight the importance of considering cyclone disturbances when predicting liana‐tree interactions and their impacts on forest dynamics and carbon storage in tropical forests.

  PublisherOA PDFDOI

• The Impacts of Monetization on Host‐Country Agriculture: The Case of Peru

  Preprints.org · 2025-04-09

  preprintOpen accessSenior author

  This research analyzes with statistical evidence and complete economic specifications the effects of the U. S. Department of Agriculture’s (USDA’s) monetization of a U. S. commodity to support its Food for Progress projects. Since the beginning of the monetization program, its possible effects on agricultural producers in the receiving countries has been a concern. In this case, the country is Peru and the commodity is crude degummed soybean oil (CDSO). Effects were measured statistically on domestic prices and production in Peru, including effects on substitute commodities. The first stage of the research involved the identification of data needed and subsequent data collection, and model formulation. A 25-year time series was used for the statistical analysis. A sequence of progressively more complete models was used to capture the impact of monetization based on available price information on the monetized commodity and related products in domestic production and consumption. Our model specifications are based on the time series nature of our data and the classical demand and supply models in economic analysis. To account for potential lagged impacts, we employ a distributed lags specification in our time series analysis. The statistical analysis here modifies in important ways the approach of Appendix II of the GAO’s 2017 report on monetization [11]. Differences include: 1) Incorporating quantities and prices of substitutes into price equations in addition to testing the role of time trends in explaining prices. Attempting to explaining price movements only with time trends, as the GAO report did, does not have support in economic theory, and statistically time trends did not prove to have a significant explanatory effect when the other variables were included. 2) Analyzing a wider set of commodities potentially affected by the monetization program. The existence of substitution effects in both production and consumption calls for analysis of monetization effects on a number of locally produced commodities.

  PublisherOA PDFDOI

• Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida

  Scientific Data · 2025-07-10 · 3 citations

  articleOpen access

  Hurricane Ian caused aboveground biomass density (AGBD) losses across Florida’s forests in the United States, highlighting the need for accurate, large-scale monitoring tools. We combined Global Ecosystem Dynamics Investigation (GEDI) LiDAR data with synthetic aperture radar (SAR) and passive optical satellite imagery to model GEDI AGBD as a function of image-derived data, enabling predictions across the study area and producing continuous AGBD maps. Validation using in situ field data demonstrated high model performance, with an R2 of 0.93 and a root mean square difference (RMSD) of 39.3%. Spatial uncertainty reflecting bootstrap-derived variance remained consistent, with relative standard errors around 90% across the years analyzed. The data are accessible through a web application, RapidFEM4D, enabling researchers and stakeholders to assess AGBD maps for areas of interest. These datasets support monitoring forest recovery, assessing carbon dynamics, and guiding post-hurricane management and restoration. The RapidFEM4D platform facilitates access and analysis of Hurricane Ian’s impact on Florida’s forests, empowering stakeholders with actionable insights and offering a model for similar efforts in other hurricane-prone regions.

  PublisherOA PDFDOI

• Family forest landowners’ decision-making about reforestation and timber salvaging post hurricane

  Trees Forests and People · 2025-02-21 · 1 citations

  articleOpen access

  • Providing financial assistance to forest landowners after hurricanes can help with reforestation. • Owning forestlands to harvest timber is a strong motivator for reforestation and grant application. • Large volumes of debris still left on family forest lands after hurricane. • Larger landowners are more likely to reforest their lands and apply for the grant. • Our study reveals lack of awareness and accessibility for forest landowners to apply for financial assistance. Reforestation is critical to maintaining ecosystem functions and socio-economic benefits, particularly after extreme disturbances such as hurricanes. This study assessed the management efforts of family forest landowners in the Panhandle, Florida following the devastating impacts of Hurricane Michael (2018). We mailed a survey to 1,000 randomly selected landowners impacted by Hurricane Michael to examine 1) their reforestation and timber salvaging plans, 2) their ownership and management plans and 3) the impacts of the novel Florida Timber Recovery Block Grant (TRBG) program on forest management including any significant differences between landowners who did and did not apply for the program. We found that family forest landowners who were members of environmental or woodland owners’ organizations, had written forest management plans, had larger forest lands, or owned their forest lands for timber products were more likely to engage in reforestation. Landowners who applied for the TRBG funding were more likely to have salvage harvested timber and indicated plans to reforest their lands in the future, in comparison to those who did not apply for the grant. Our study provides insights on policy that can support family forest landowners to reforest their lands, primarily highlighting that although financial assistance is invaluable, these support programs should be thoughtfully implemented to increase landowner accessibility.

  PublisherDOI

Frequent coauthors

• Eric J. Jokela

  43 shared

• Edward A. G. Schuur

  Northern Arizona University

  30 shared

• Timothy A. Martin

  Corteva (United States)

  30 shared

• Rosvel Bracho

  University of Florida

  21 shared

• Daniel Markewitz

  University of Georgia

  19 shared

• Rodney E. Will

  Oklahoma State University

  15 shared

• Cassandra Meek

  14 shared

• Jason B. West

  Texas A&M University

  13 shared