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Timothy A. Martin  - - - 
Top co-authors See all
Dennis D. Baldocchi

153 shared publications

Department of Environmental Sciences, Policy, and Management; University of California; Berkeley CA USA

Gil Bohrer

81 shared publications

Department of Civil, Environmental and Geodetic Engineering; The Ohio State University; Columbus OH USA

Walter C. Oechel

71 shared publications

San Diego State University, San Diego, CA. 92182, USA

Francisco J. Escobedo

56 shared publications

Facultad de Ciencias Naturales y Matemáticas, Programa de Biología, Universidad del Rosario, Bogotá D.C., Colombia

Wendell P. Cropper

47 shared publications

School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA

Publication Record
Distribution of Articles published per year 
(1995 - 2017)
Total number of journals
published in
Publications See all
Article 0 Reads 5 Citations Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the So... Mukhtar Ahmed Ajaz Ahmed, Amr Abd-Elrahman, Francisco J. Esc... Published: 01 September 2017
Journal of Environmental Management, doi: 10.1016/j.jenvman.2017.05.013
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale.
Article 0 Reads 2 Citations Loblolly Pine Productivity and Water Relations in Response to Throughfall Reduction and Fertilizer Application on a Poor... Maxwell Wightman, Timothy Martin, Carlos Gonzalez-Benecke, E... Published: 26 September 2016
Forests, doi: 10.3390/f7100214
DOI See at publisher website ABS Show/hide abstract
Loblolly pine (Pinus taeda L.) forests are of great ecological and economic value in the southeastern United States, where nutrient availability frequently limits productivity. The impact of fertilizer application on the growth and water relations of loblolly pine has been investigated by numerous studies; however, few field experiments have examined the effects of drought. Drought is of particular interest due to the potential for climate change to alter soil water availability. In this study, we investigated the impact of fertilizer application and a 30% reduction in throughfall on loblolly pine productivity, transpiration, hydraulic conductance, and stomatal conductance. The study was installed in a ten-year-old loblolly pine plantation on a somewhat poorly drained site in northern Florida. Throughfall reduction did not impact tree productivity or water relations of the trees. This lack of response was attributed to abundant rainfall and the ability of trees to access the shallow water table at this site. Fertilizer application increased basal area production by 20% and maximum leaf area index by 0.5 m2∙m−2, but it did not affect whole-tree hydraulic conductance or the sensitivity of stomatal conductance to vapor pressure deficit. During the spring, when leaf area and vapor pressure deficit were high, the fertilizer-only treatment increased monthly transpiration by 17% when compared to the control. This relationship, however, was not significant during the rest of the year.
Article 1 Read 5 Citations Regional validation and improved parameterization of the 3-PG model for Pinus taeda stands Carlos A. Gonzalez-Benecke, Robert O. Teskey, Timothy A. Mar... Published: 01 February 2016
Forest Ecology and Management, doi: 10.1016/j.foreco.2015.11.025
DOI See at publisher website ABS Show/hide abstract
Highlights•The 3-PG model is an extensively applied tool for estimating forest growth.•We developed a new set of parameters and functions for loblolly pine.•New functions: NPP allocation, biomass, canopy cover, survival and fertility.•We used the largest validation dataset ever used for 3-PG.•We found strong agreement between measurements and model predictions. AbstractThe forest simulation model, 3-PG, has the capability to estimate the effects of climate, site and management practices on many stand attributes using easily available data. The model, once calibrated, has been widely applied as a useful tool for estimating growth of forest species in many countries. Currently, there is an increasing interest in estimating biomass and assessing the potential impact of climate change on loblolly pine (Pinus taeda L.), the most important commercial tree species in the southeastern U.S. This paper reports a new set of 3-PG parameter estimates for loblolly pine, and describe new methodologies to determine important estimates. Using data from the literature and long-term productivity studies, we parameterized 3-PG for loblolly pine stands, and developed new functions for estimating NPP allocation dynamics, biomass pools at variable starting ages, canopy cover dynamics, effects of frost on production, density-independent and density-dependent tree mortality and the fertility rating. The model was tested against data from replicated experimental measurement plots covering a wide range of stand characteristics, distributed across the southeastern U.S. and also beyond the natural range of the species, using stands in Uruguay, South America. We used the largest validation dataset for 3-PG, and the most geographically extensive within and beyond a species’ native range. Comparison of modeled to measured data showed robust agreement across the natural range in the U.S., as well as in South America, where the species is grown as an exotic. Across all tested sites, estimations of survival, basal area, height, quadratic mean diameter, bole volume and above-ground biomass agreed well with measured values, with R2 values ranging between 0.71 for bole volume, and 0.95 for survival. The levels of bias were small and generally less than 13%. LAI estimations performed well, predicting monthly values within the range of observed LAI. The results provided strong evidence that 3-PG could be applied over a wide geographical range using one set of parameters for loblolly pine. The model can also be applied to estimate the impact of climate change on stands growing across a wide range of ages and stand characteristics.
Article 0 Reads 4 Citations Modeling the effects of forest management on in situ and ex situ longleaf pine forest carbon stocks C.A. Gonzalez-Benecke, L.J. Samuelson, T.A. Martin, W.P. Cro... Published: 01 November 2015
Forest Ecology and Management, doi: 10.1016/j.foreco.2015.02.029
DOI See at publisher website
Article 0 Reads 2 Citations Management intensification effects on autotrophic and heterotrophic soil respiration in subtropical grasslands Julius B. Adewopo, Maria L. Silveira, Sutie Xu, Stefan Gerbe... Published: 01 September 2015
Ecological Indicators, doi: 10.1016/j.ecolind.2015.03.025
DOI See at publisher website
Article 1 Read 12 Citations A Range-Wide Experiment to Investigate Nutrient and Soil Moisture Interactions in Loblolly Pine Plantations Rodney E. Will, Thomas Fox, Madison Akers, Jean-Christophe D... Published: 03 June 2015
Forests, doi: 10.3390/f6062014
DOI See at publisher website ABS Show/hide abstract
The future climate of the southeastern USA is predicted to be warmer, drier and more variable in rainfall, which may increase drought frequency and intensity. Loblolly pine (Pinus taeda) is the most important commercial tree species in the world and is planted on ~11 million ha within its native range in the southeastern USA. A regional study was installed to evaluate effects of decreased rainfall and nutrient additions on loblolly pine plantation productivity and physiology. Four locations were established to capture the range-wide variability of soil and climate. Treatments were initiated in 2012 and consisted of a factorial combination of throughfall reduction (approximate 30% reduction) and fertilization (complete suite of nutrients). Tree and stand growth were measured at each site. Results after two growing seasons indicate a positive but variable response of fertilization on stand volume increment at all four sites and a negative effect of throughfall reduction at two sites. Data will be used to produce robust process model parameterizations useful for simulating loblolly pine growth and function under future, novel climate and management scenarios. The resulting improved models will provide support for developing management strategies to increase pine plantation productivity and carbon sequestration under a changing climate.