PIE LTER Publications
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2013. The importance of dissimilatory nitrate reduction to ammonium (DNRA) in the nitrogen cycle of coastal ecosystems.. Oceanography. 26:124-131.
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2003. Importance of metabolism in the development of salt marsh ponds.. Biological Bulletin. 205:248-249.
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2007. Improvements in the use of the ROC statistic for landscape ecology. Conference proceedings of the World Congress of the International Association for Landscape Ecology. :2.
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2022. Improving Channel Hydrological Connectivity in Coastal Hydrodynamic Models With Remotely Sensed Channel Networks. Journal of Geophysical Research: Earth Surface. 127:e2021JF006294.
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2000. Improving marine ecosystem models: Use of data assimilation and mesocosm experiments.. Journal of Marine Research. 58:117-164.
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2020. Improving predictions of salt marsh evolution through better integration of data and models.. Annual Review of Marine Science. 12:389-413.
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2015. Increased nitrogen export from eastern North America to the Atlantic Ocean due to climatic and anthropogenic changes during 1901–2008. Journal of Geophysical Research: Biogeosciences. 120:1046-1068.
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2009. Increased supply of ambient nitrogen has minimal effect on salt marsh bacterial production. Limnology and Oceanography . 54:713-722.
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2015. An index to characterize the spatial distribution of land use within watersheds and implications for river network nutrient removal and export. Geophysical Research Letters. 42
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1999. Influence of marsh flooding on the abundance and growth of Fundulus heteroclitus in salt marsh creeks. Biological Bulletin. 197:299-300.
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1998. Influence of the benthos on growth of planktonic estuarine bacteria . Aquatic Microbial Ecology. 16:109-118.
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2004. The influence of urbanization on runoff generation and stream chemistry in Massachusetts watersheds.. Ph.D.
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2022. Integrated Modeling of Dynamic Marsh Feedbacks and Evolution Under Sea-Level Rise in a Mesotidal Estuary (Plum Island, MA, USA). Water Resources Research. 58:e2022WR032225.
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2021. Integrating a Forward Feature Selection algorithm, Random Forest, and Cellular Automata to extrapolate urban growth in the Tehran-Karaj Region of Iran. Computers, Environment and Urban Systems. 87:101595.
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2005. Integrating LIDAR, multispectral imagery and neural network modeling techniques for marsh classification.. International Journal of Remote Sensing. 26:5221-5234.
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2018. Intense Storms Increase the Stability of Tidal Bays. Geophysical Research Letters. 45:5491–5500.
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2019. Intensity Analysis and the Figure of Merit’s components for assessment of a Cellular Automata – Markov simulation model. Ecological Indicators.
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2019. Intensity Analysis to communicate land change during three time intervals in two regions of Quanzhou City, China.. GIScience & Remote Sensing.
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2020. Intensity Analysis to communicate land change during three time intervals in two regions of Quanzhou City, China. GIScience & Remote Sensing. 57:21–36.
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2012. Intensity Analysis to Unify Measurements of Size and Stationarity of Land Changes by Interval, Category, and Transition.. Landscape and Urban Planning. 106:103-114.
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2000. Interaction between physical processes and ecosystem structure: A comparative approach.. Estuarine Science: A Synthetic Approach to Research and Practice. :177-206.
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2005. An inverse ecosystem model of year-to-year variations with first order approximation to the annual mean fluxes.. Ecological Modeling. 187:369-388.