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How do abiotic and biotic processes affect the spatial morphology of a landscape and what drives the distribution of species and communities?

Answers to these questions vary across ecosystems and with scale. Selecting an appropriate scale of analysis is fundamental to investigating and understanding the ecological processes that drive landscape morphology, assembly patterns of primary producers, and the spatial distribution of habitats used by consumers of higher trophic levels.

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Coastal Wetland Dynamics

Coastal wetlands and their surrounding seascapes are composed of diverse mosaics of ecosystems that offer unique laboratories to study ecological processes that interrelate the marine ecosystems of coral reefs and seagrass beds to coastal mangrove forests and vast terrestrial, graminoid-dominated marshes and prairies, tree islands, and cypress and pine forests.

Our main focus are the coastal ecosystems of South Florida. We aim to better understand ecosystem and plant community shifts in the Everglades landscape mosaic that are driven by changing environmental conditions including interactions of sea-level rise, freshwater management practices and restoration, fire regimes, and passing tropical storm events.

The different processes that operate and interact at different scales across the landscape often require cross-scale and multi-scale modeling of ecological processes and patterns. To understand ecosystem processes and their effects on vegetation transitions across spatial scales, we use very high spatial resolution remote sensing data and scaling algorithms that allow for larger-scale inferences, and prediction at different scales.

Crucial for system-wide scaling are methods that allow for estimation and reduction of information loss. The effects of categorical data scales and scaling of multi-scale quantitative classification systems are the focus of our research.

Research Interests:

(1) Categorical Data Scaling

(2) Plant Community Transitions:

(a) Glycophytic - Halophytic Community Dynamics in Response to Sea-Level Rise

(b) Effects of Hydroperiod Length and Fire on Spatio-Temporal Dynamics of Freshwater Wetland Communities

(3) Woody and Graminoid Species Co-Existence Patterns in Wetland Ecosystems

Wildlife Habitat Assessment and Conservation

Mobile species moving across the landscape to forage, find mates and reproduce and to avoid predators respond to the the structure of the landscapes across scales. The specific needs of a species determine optimal and suitable habitat. The abundance and spatiotemporal distribution of resources drive decisions of individual at the organism level.

Project 1: Habitat Selection of the St Vincent Parrot (Amazona guildingii)

We are working with the St Vincent department of Forestry to determine optimal habitat for the St Vincent Parrot producing and analyzing landcover maps at various spatal scales using airborne and terrestrial LiDAR technology and associating parrot presence and occupancy times across different landcover and landuse times using passive acounstic monitoring (SWIFT ONE, Cornell Lab).  

 

Projects

Title: Evaluating the effects of hydrological restoration and sea-level rise on vegetation patterns within Everglades National Park (2014 - 2028)

Objectives: We are assessing effects of hydrological restoration, and sea-level rise on vegetation patterns and transition dynamics across the ENP landscape. All project components use very high-resolution remote sensing data and methods to detect and model spatially explicit and exhaustive changes in vegetation/plant communities. Spatially explicit modeling of vegetation change in relation to environmental conditions is conducted in a landscape ecological framework at multiple spatial scales. Subregions of interest are (1) NESRS and TS responses to hydrological restoration; (2) Mangrove encroachment patterns in the coastal regions of Eveglades National Park; (3) Vegetation dynmaics in Shark-Harney River Network oin response to coastal creek expansion; (4) Woody vegetation distribution patterns and their environmetnal and spatial drivers.

Funded by: Everglades National Park

Lead PIs: Dr. Daniel Gann, Dr. Jennifer Richards

Title: Evaluating the effects of fire history on coastal marsh peat collapse features in the northwest coastal Everglades, Everglades National Park (2023 - 2028)

Objective: We are assessing what effect, if any, fire has on coastal marsh peat collapse and in the number and size of collapse features within the landscape. The project uses remote sensing techniques to determine if peat collapse features within the coastal Everglades are increasing in number and size following fires.

Funded by: Everglades National Park

Lead PIs: Dr. Daniel Gann

Title: Modeling and Correcting Vegetation-Induced Bias for LiDAR-Derived Digital Terrain Models in Water Conservation Areas (2021 - 2027)

Objective: Improve developed filtering and interpolation algorithms to estimate and correct vegetation class-specific biases and produce accurate DTMs from raw LiDAR point clouds from newly acquired LiDAR data and to model elevation bias of DTMs introduced by vegetation. The objective is to model the elevation bias introduced by 12 morphologically different woody and herbaceous vegetation classes: (1) Woody classes: hardwood hammock trees, bayhead trees, cypress trees, bayhead shrubs, and dwarf cypress; (2) herbaceous classes: tall and dense graminoid marsh species (including Cladium, Typha and other tall grasses and sedges), and short graminoid marsh, prairie communities, open marsh with sparse floating and emergent vegetation, and floating vegetation. All classes are mapped from spectral reflectance patterns of the WV-2 or -3 and/or PlanetScope multispectral satellite data to inform the bias estimation and adjustment models.

Funded by: South Florida Water Management District

Lead PIs:Dr. Daniel Gann, Dr. Jed Redwine

Title: Monitoring, Modeling and Assessment of the Everglades Ecosystem: R-EMAP V (2023 - 2026)

The overarching objectives of REMAP are to measure the condition of ecological resources throughout the Everglades and to document ecosystem responses as CERP restoration efforts change the quality, quantity, timing, and distribution of water, while Florida also implements control strategies for pollutants such as phosphorus and mercury. REMAP is unique to the Everglades in consistently combining several aspects of scientific study:  a probability-based sampling design which results in quantitative statements about the condition of the Everglades across space, multi-media biogeochemical sampling (water, soil, biota), and extensive spatial coverage of the freshwater Everglades.

Funded by: Everglades National Park & Environmental Protetion Agency

Lead PIs:Dr. Daniel Gann, Dr. Yong Cai, Dr. Yan Ding, Dr. Guiangliang Liu, Dr. Paulo Olivas 

Title: Tree Island Ground Topography in Relation to Changes in Marsh Hydrology - Water Conservation Area 3 Tree Island Surveys of High-Accuracy Elevation, Soil and Vegetation (2025 - 2028)

This project has three specific objectives:
(1) Estimate the relative elevation and spatial distribution of woody vegetation components of each tree island > 0.01 ha in WCA3A and 3B (Figure 1).
(2) Quantify past distributions of hydrological conditions among plant communities of interest across all sampled tree islands and non-sampled islands and compare tree islands within and among regions (Fig. 2).
(3) Quantify the spatial dependence of plant community distributions of tree islands as a function of biophysical parameters such as, island location distance to control structures, community cover along relative elevation distributions, and soil type and depth. The rationale for this objective is that the relationship between physical environmental variables and woody vegetation distributions are expected to vary spatially (e.g., due to different nutrient availability, biological processes, and succession legacies of community assembly).

Funded by: South Florida Water Management District

Lead PIs:Dr. Daniel Gann, Dr. Jed Redwine

Title: Vegetation Distribution in Biscayne Bay Coastal Wetlands - Remote Sensing Methods Development (2025)

Funded by: South Florida Water Management District

Lead PIs: Dr. Brittany Harris & Dr. Daniel Gann

Title: Florida Coastal Everglades Long-Term Ecological Research (FCE-LTER) (2025 - 2030)

Objective: The central focus of the Florida Coastal Everglades (FCE) Long Term Ecological
Research program is to understand the mechanisms and consequences of resilience in socialecological systems to shifting climate and hydrologic disturbance regimes.

Funded by: National Science Foundation

Lead PIs: Dr. John Kominoski, Dr. Daniel Gann, Dr. Jennifer Rehage, Dr. Rolando Santos, Dr. Tiffany Troxler

Title: Assessment of Upland Resources within Miami Dade County (2025 - 2026)

The purpose of the project is to assist Miami Dade County’s Division of Environmental Resources Management (DERM) in assessing upland resources within the county. The project will assess 250 tree plots and integrate the plots in a LiDAR driven tree canopy model and provide evaluations of potential environmentally sensitive footprints.

Funded by: Miami-Dade County

Lead PIs: Dr. Daniel Gann, Dr. Dishane Hewavithana, Dr. Brittany Harris, Dr. Tiffany Troxler

Title: Tree Island Dynamics in Everglades National Park (2024 - 2029)

Objectives: The specific objectives of the proposed work are to (1) monitor the condition of plant community structure and composition of tree islands; (2) to assess temporal changes in the plant community structure and composition; (3) to determine the relationships among the hydrologic regimes of adjacent marshes, other stress variables, and dynamics of vegetation communities on tree islands; and (4) to investigate the correlation of spatially explicit long-term vegetation changes in response to hydrological regime changes.

Funded by: U.S Army Corps of Engineers

Lead PIs: Dr. Jay Sah, Dr. Daniel Gann, Dr. Michael Ross

Title: Tree island response to hydrologic and fire regime changes in Northeast
Shark River Slough (NESRS), Everglades National Park (2024 - 2028)

Objective:  The major objectives are to determine the hydrologic optima of tree island woody species and assess the impacts of hydrologic restoration on them in NESRS and to assess how tree islands physiography in NESRS has changed between 1940 and present
in response to hydrologic management, fire regime, and invasive species.

Funded by: Everglades National Park

Lead PIs: Dr. Jay Sah & Dr. Daniel Gann

Title: Exploring Human-Wildlife Interconnectivity in the Caribbean – A Hands-On Approach to Research, Conservation and Professional Development (2024 - 2027)

Objective: This international training program, spearheaded by the Institute of Environment (IoE) at Florida International University in collaboration with St. Vincent and the Grenadines' Departments of Forestry and Fisheries, Science Initiative for Environmental Conservation and Education (SCIENCE, partner NGO), and the Barrouallie Whalers Project (partner NGO), aims to offer exceptional research and professional development opportunities in Wildlife Conservation and Ecology to U.S. undergraduate and graduate students. Each year, we recruit six students (2 two graduates and four undergraduates) for a comprehensive year-long research program investigating human-wildlife interactions involving terrestrial and marine flagship species. The program features a pivotal four-week fieldwork experience in St. Vincent and the Grenadines (SVG), in the eastern Caribbean. During field activities, students will receive hands-on mentorship from SVG's Forestry and Fisheries Department, along with research and capacity-building training from the project’s PIs.

Funded by: National Science Foundation

Lead PIs: Dr. Jeremy Kiszka & Dr. Daniel Gann

Title: MRI: Development of an instrument for student and faculty research on Multimodal
Environmental Observations (2020 - 2026)

Funded by: National Science Foundation

Lead PIs: Dr. Naphtalie Rishe, Dr. Daniel Gann, Dr. Shahin Vasigh, Dr. Sitharama Iyengar, Dr. Todd Crowl

 

Publications & Datasets

To view all publications, please visit Dr. Daniel Gann's profile on FIU Digital Commons.

  • Publications & Reports

    Journal Articles

    Gann, D. & Richards, J.H. (2023). Scaling of classification systems-effects of class precision on detection accuracy from medium-resolution multispectral data. Landscape Ecology, 38, 659–687 (2023). https://doi.org/10.1007/s10980-022-01546-1 

    Lamb, L. M., Gann, D., Velazquez, J. T., & Troxler, T. G. (2022). Detecting Vegetation to Open Water Transitions in a Subtropical Wetland Landscape from Historical Panchromatic Aerial Photography and Multispectral Satellite Imagery. Remote Sensing, 14, 3976. https://doi.org/10.3390/rs14163976

    Biswas, H., Zhang, K., Ross, M. S., & Gann, D. (2020). Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs. Remote Sensing, 12(13), 2086. https://doi.org/10.3390/rs12132086

    Gann, D. (2019). Quantitative spatial upscaling of categorical information: The multi‐dimensional grid‐point scaling algorithm. Methods in Ecology and Evolution / British Ecological Society, 10(12), 2090–2104. https://doi.org/10.1111/2041-210X.13301

    Zhang, K., Gann, D., Ross, M., Biswas, H., Li, Y., & Rhome, J. (2019). Comparison of TanDEM-X DEM with LiDAR Data for Accuracy Assessment in a Coastal Urban Area. Remote Sensing 11(7), 876. https://doi.org/10.3390/rs11070876

    Zhang, K., Gann, D., Ross, M., Robertson, Q., Sarmiento, J., Santana, S., Rhome, J., & Fritz, C. (2019). Accuracy assessment of ASTER, SRTM, ALOS, and TDX DEMs for Hispaniola and implications for mapping vulnerability to coastal flooding. Remote Sensing of Environment, 225, 290–306. https://doi.org/10.1016/j.rse.2019.02.028

    Wendelberger, K. S., Gann, D., & Richards, J. H. (2018). Using Bi-seasonal worldview-2 multi-spectral data and supervised random forest classification to map coastal plant communities in everglades national park. Sensors , 18(3). https://doi.org/10.3390/s18030829

    Zhang, K., Thapa, B., Ross, M., & Gann, D. (2016). Remote sensing of seasonal changes and disturbances in mangrove forest: A case study from South Florida. Ecosphere , 7(6). https://doi.org/10.1002/ecs2.1366

    Gann, D., & Richards, J. (2015). Quantitative Comparison of Plant Community Hydrology Using Large-Extent, Long-Term Data. Wetlands, 35(1), 81–93. https://doi.org/10.1007/s13157-014-0594-2 

    Book Chapters

    Gann, D., Richards, J., Lee, S., & Gaiser, E. (2015). Detecting Calcareous Periphyton Mats in the Greater Everglades Using Passive Remote Sensing Methods. In J. A. Entry, A. D. Gottlieb, K. Jayachandran, & A. Ogram (Eds.), Microbiology of the Everglades Ecosystem (pp. 350–372). CRC Press. https://doi.org/10.1201/b18253-17

    Reports

    Gann, D., Richards, J. H., & Harris, B. (2019). Vegetation Change along Everglades National Park Boundary Areas of Northeast Shark River Slough, Between 2010/13 and 2016/17. Everglades National Park.

    Richards, J., Gann, D., & Sadle, J. (2015). Vegetation Trends in Indicator Regions of Everglades National Park (p. 171). Everglades National Park. http://digitalcommons.fiu.edu/gis/29

    Gann, D. (2014). Remote Sensing Supported Vegetation Detection in the Hole-in-the-Donut Restoration Areas (p. 31). Everglades National Park. http://digitalcommons.fiu.edu/gis/24

    Gann, D., Richards, J. H., & Biswas, H. (2012). Determine the effectiveness of vegetation classification using WorldView 2 satellite data for the Greater Everglades (p. 62 pp). Division/RECOVER, Everglades. http://digitalcommons.fiu.edu/gis/25

  • Datasets

    In order to access datasets related to FIU, please visit the FIU Research Data Portal.