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Naithani Research Group
  • Home
  • People
  • Projects
    • Borneo
    • Rice
    • Monarch
    • Shale Hills
    • ChEAS
    • Codling moth
    • Sagebrush
    • NEON
    • EcoREU
    • Yaqunia Estuary
    • Beaver Lake
    • ERC
  • Publications
    • Ecosystem and Landscape Ecology
    • Biodiversity Conservation
    • Food Security
  • Teaching
  • Join the Group
  • More
    • Home
    • People
    • Projects
      • Borneo
      • Rice
      • Monarch
      • Shale Hills
      • ChEAS
      • Codling moth
      • Sagebrush
      • NEON
      • EcoREU
      • Yaqunia Estuary
      • Beaver Lake
      • ERC
    • Publications
      • Ecosystem and Landscape Ecology
      • Biodiversity Conservation
      • Food Security
    • Teaching
    • Join the Group

Publications

Food Security

Biodiversity Conservation

Combined landscape complexity is a better indicator of ecosystem functions in forested ecosystems than physical or biological complexity alone.  

  St. Rose A., Xiao J., and Naithani K. (in review) Combined landscape complexity is a better indicator of ecosystem functions in forested ecosystems than physical or biological complexity alone. 

This research introduces novel tools for evaluating and conserving multi-trophic biodiversity in forested ecosystems at the landscape scale.  

  St. Rose A., and Naithani K. (2025) Unraveling the Influence of Structural Complexity, Environmental, and Geographic Factors on Multi-Trophic Biodiversity in Forested Landscapes. Ecology and Evolution, Vol: 15(2) e70907. doi: 10.1002/ece3.70907

Sheep grazing reduces insect diversity. 

Acharya R. S., Leslie T., Burke J., Naithani K., Fitting E., Loftin K., and Joshi N. K. (2024) Sheep grazing influences the abundance, diversity, and community composition of wild bees and other insects in livestock pastures. Ecological Indicators. Vol: 162, 111839. doi: 10.1016/j.ecolind.2024.111839

Identifying the influence of a landmark on an outcome of interest using a distance variable, such as the effect of distance to shopping on home price.  

Syed M., Farmer M.C., Naithani K., and Lacombe D. J. (2024) A problem with distance variables and alternatives for their use. Journal of Real Estate Research. doi: 10.1080/08965803.2024.2325244.

A network of networks approach to macrosystems biology research. 


SanClements M., Record S., Rose K., Donnelly A., Chong S., Duffy K., Hallmark A., Heffernan J., Mitchell J., Moore D., Naithani K., O’Reilly C., Sokol E., Weintraub S., Stack Whitney K., and Yang D. (2022) People, infrastructure, and data: A pathway to an inclusive and diverse ecological Network of Networks. Ecosphere, e4262.  doi: 10.1002/ecs2.4262

Global food and beverage industry lacks transparency on climate goals and targets, and needs a clear path for monitoring, reporting, and verification of GHG emissions.

 Reavis M. L., Ahlen J., Rudek J., and Naithani K. (2022) Evaluating greenhouse gas emissions and climate mitigation goals of the global food and beverage sector. Frontiers of Sustainable Food Systems, 5:789499. doi: 10.3389/fsufs.2021.789499

Logging and forest conversion significantly affect soil microbial diversity and can have lasting effects on carbon cycling in tropical montane forests. 


Sniegocki R., Moon J. B., Rutrough A., Gireneus J., Seelan J. S. S., Weindorf D. C., Farmer M. C., and Naithani K. (2022) Recovery of soil microbial diversity and functions along a tropical montane forest disturbance gradient, Frontiers in Environmental Science, 10:853686. doi: 10.3389/fenvs.2022.853686 

NEON data for next generation ecology research and education. 


Nagy R. C. et al. (90 authors including Naithani K.) (2021) Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community. Ecosphere, 12 (12): e03833. doi:10.1002/ecs2.3833

neonMicrobe: R package for analyzing NEON marker gene sequence data.  

GitHub Repo

Qin C., Bartelme R., Chung A., Fairbanks D., Lin Y., Liptzin D., Muscarella C., Naithani K., Peay K., Pellitier P., St. Rose A., Stanish L., Werbin Z., and Zhu K. (2021) From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package. Ecosphere, 12 (11): e03842. doi: 10.1002/ecs2.3842.

First decadal (2006 – 2015) field-based estimate of sediment deficit for coastal Louisiana. 

Sanks K. M., Shaw J. B. Naithani K. (2020) Field-based estimate of the sediment deficit in coastal Louisiana. JGR–Earth Surface.  125 (8) e2019JF005389.

       doi: 10.1029/2019JF005389

Promising multivariate soil indices as indicators of wetland condition. 


Moon J. B., Wardrop D. H., Smithwick E. A. H.  & Naithani K. J. (2019) Fine-scale spatial homogenization of microbial habitats: a multivariate index of headwater wetland complex condition. Ecological Applications. 29(1), e0181.

Dryad, Dataset

Coupled human and natural systems approach is needed to resolve human-elephant conflicts


Shaffer L. J., Khadka K. K., Van Den Hoek J. & Naithani K. J. (2019) Human-elephant conflict: A review of current management strategies and future directions. Frontiers in Ecology and Evolution 6:235.


Semiarid ecosystems can alter their canopy leaf area to control atmosphere-canopy decoupling, potentially moderating impacts of climate change.


Reed D. E., Ewers B. E., Pendall E., Naithani K. J., Kwon H. & Kelly R. D. (2018) Biophysical factors and canopy coupling control ecosystem water and carbon fluxes of semi-arid sagebrush ecosystems. Rangeland Ecology and Management. 71(3): 309 – 317.


Uncertainty in predicting carbon and water fluxes increased with increasing temporal resolution. 

Mitra B., Mackay D. S., Cleary M. B., Pendall E. G., Ewers B. E., Kwon H., Cleary M. B. & Naithani K. J. (2018) Model – Data fusion approach to quantify evapotranspiration and net ecosystem exchange across the sagebrush ecosystem at different temporal resolutions, Ecohydrology. ECO1957.

A new catchment-scale stratification scheme showed that integrating soil and terrain attributes improves delineation of similar soil hydrologic units.

Baldwin D., Naithani K. J. & Lin H. (2017) Combined soil-terrain stratification for characterizing catchment-scale soil moisture variation. Geoderma, 285: 260–269.

Development of consistent and transparent practices for model selection are needed for successful model transfer. 

Moon J. B., DeWitt T. H., Errend M. N., Bruins R. J. F., Kentula M. E., Chamberlain S. J., Fennessy M. S., and Naithani K. J. (2017) Model application niche analysis: Assessing the transferability and generalizability of ecological models. Ecosphere 8(10): e01974.

Landscape metrics can be utilized to predict wetland microbial communities.

Moon J. B., Wardrop D. H., Bruns M. A. V., Miller R. M., and Naithani K. J. (2016) Land-use and land-cover effects on soil microbial community abundance and composition in headwater riparian wetlands. Soil Biology and Biochemistry, 97: 215 – 233. 

Interpretation of nutrient limitation in grasslands is dependent on the grain used to measure grass response and that herbivory had a secondary effect.

Smithwick E. A. H., Baldwin D. & Naithani K. J. (2016) Grassland productivity in response to nutrient additions and herbivory is scale-dependent. PeerJ 4:e2745.

Plant phenology drove seasonal fluxes more predictably than abiotic measurements.

Cleary M.B., Naithani K.J., Ewers B.E. & Pendall E. (2015) Upscaling CO2 fluxes using leaf, soil and chamber measurements across successional growth stages in a sagebrush steppe ecosystem. Journal of Arid Environments, 121:43-51. 

Common microhabitat preference and limited dispersal are the main drivers for rockcress spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

Naithani K.J., Ewers B.E., Adelman J.D. & Siemens D.H. (2014) Abiotic and biotic controls on local spatial distribution and performance of a Boechera stricta population. Frontiers in Plant Science, 5:348.

Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. 

Naithani K.J., Baldwin D.C., Gaines K.P., Lin H. & Eissenstat D.M. (2013) Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape. PLoS ONE, 8:e58704.

A combination of atmospheric and surface soil drought control leaf transpiration, whereas stomatal conductance is mainly driven by atmospheric drought. 

Naithani K.J., Ewers B.E. & Pendall E. (2012) Sap flux-scaled transpiration and stomatal conductance response to soil and atmospheric drought in a semi-arid sagebrush ecosystem. Journal of Hydrology, 464-465: 176-185. 

We observed congruent spatial structures (i.e., patchiness) of microbial, cover, and N mineralization variables, suggestive of strong linkages between pattern (microbial abundance, aboveground cover) and process (N mineralization) in burned plots. 

Smithwick E.A.H., Naithani K.J., Balser T.C., Romme W.H. & Turner M.G. (2012) Post-fire spatial patterns of soil nitrogen mineralization and microbial abundance. PLoS ONE, 7:e50597. 

Under water limitation, soil drought was the main driving factor of growing season NEE regardless of weather conditions while atmospheric drought was the main driver of NEE when the ecosystem was not limited by soil moisture. 

Kwon H., Pendall E., Ewers B. E., Cleary M. & Naithani K. (2008) Spring drought regulates summer net ecosystem CO2 exchange in a sagebrush steppe ecosystem. Agricultural & Forest Meteorology, 91(5): 24-30., 148: 381-391.

These materials are not endorsed, approved, sponsored, or provided by or on behalf of the University of Arkansas, Fayetteville.

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