@article{raigosa-garcia_rathbun_cook_baker_corrao_sumnall_2024, title={Rethinking Productivity Evaluation in Precision Forestry through Dominant Height and Site Index Measurements Using Aerial Laser Scanning LiDAR Data}, volume={15}, ISSN={["1999-4907"]}, DOI={10.3390/f15061002}, abstractNote={Optimizing forest plantation management has become imperative due to increasing forest product demand, higher fertilization and management costs, declining land availability, increased competition for land use, and the growing demands for carbon sequestration. Precision forestry refers to the ability to use data acquired with technology to support the forest management decision-making process. LiDAR can be used to assess forest metrics such as tree height, topographical position, soil surface attributes, and their combined effects on individual tree growth. LiDAR opens the door to precision silviculture applied at the tree level and can inform precise treatments such as fertilization, thinning, and herbicide application for individual trees. This study uses ALS LiDAR and other ancillary data to assess the effect of scale (i.e., stand, soil type, and microtopography) on dominant height and site index measures within loblolly pine plantations across the southeastern United States. This study shows differences in dominant height and site index across soil types, with even greater differences observed when the interactions of microtopography were considered. These results highlight how precision forestry may provide a unique opportunity for assessing soil and microtopographic information to optimize resource allocation and forest management at an individual tree scale in a scarce higher-priced fertilizer scenario.}, number={6}, journal={FORESTS}, author={Raigosa-Garcia, Ivan and Rathbun, Leah C. and Cook, Rachel L. and Baker, Justin S. and Corrao, Mark V. and Sumnall, Matthew J.}, year={2024}, month={Jun} }
 @article{tajudeen_omotayo_ogundele_rathbun_2022, title={The Effect of Climate Change on Food Crop Production in Lagos State}, volume={11}, ISSN={["2304-8158"]}, DOI={10.3390/foods11243987}, abstractNote={Climate change is set to be particularly disruptive in poor agricultural communities. This study examines the effects of, and farmer’s perceptions of, climate change on farming practices for cassava and maize in Lagos, Nigeria. Analysis of weather data from 1998 to 2018 (the most recent available) reveals little impact on cassava yield but a significant impact on maize yield. Furthermore, survey results indicate that farmers in this area are currently implementing techniques to adapt to changes in climate based on the type of crop grown. Agriculture in Lagos, Nigeria, is largely rain-fed and climate change negatively impacts crop productivity by decreasing crop yield and soil fertility, limiting the availability of soil water, increasing soil erosion, and contributing to the spread of pests. A decline in crop production due to climate change may be further exasperated by a lack of access to farming technology that reduces over-reliance on the rain-fed farming system and subsistence agriculture. This study indicates that there is a need for initiatives to motivate young and older farmers through access to credits, irrigation facilities, and innovative climate change adaptive strategies.}, number={24}, journal={FOODS}, author={Tajudeen, Tawakalitu Titilayo and Omotayo, Ayo and Ogundele, Fatai Olakunle and Rathbun, Leah. C. C.}, year={2022}, month={Dec} }
 @article{kralicek_sánchez meador_rathbun_2018, title={Development and assessment of regeneration imputation models for National Forests of Oregon and Washington}, volume={409}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85037540120&partnerID=MN8TOARS}, DOI={10.1016/j.foreco.2017.12.004}, abstractNote={Imputation models were developed to predict seedling regeneration density and composition on National Forest System (NFS) lands in Oregon and Washington. The models were based on Forest Inventory and Analysis and Pacific Northwest Regional NFS Monitoring data. Individual models were developed based on broad forest plant association groups (FPAGs) with all model development and analysis conducted in R using a most similar neighbor-like imputation approach. Model performance was evaluated based on bias, mean absolute deviation, root mean-squared error (RMSE), and error rate in correctly predicting the total presence or absence of any regenerating species regardless of species (Total ER). Low to moderate RMSE (≤7400 regeneration stems ha−1) and low to moderate Total ER (≤50%) were observed for 25 out of 58 FPAG-specific models. The regeneration imputation models produced in this study represent a large first step towards developing flexible, expandable, and adaptable regeneration models that can be easily incorporated into existing growth models like the Forest Vegetation Simulator.}, journal={Forest Ecology and Management}, author={Kralicek, K. and Sánchez Meador, A.J. and Rathbun, L.C.}, year={2018}, pages={667–682} }
 @article{greenberg_keyser_rathbun_rose_fearer_mcnab_2014, title={Forecasting long-term acorn production with and without oak decline using forest inventory data}, volume={60}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84897516484&partnerID=MN8TOARS}, DOI={10.5849/forsci.12-106}, abstractNote={Acorns are important as wildlife food and for oak regeneration, but production is highly variable, posing a challenge to forest managers targeting acorn production levels. Forest managers need tools to predict acorn production capability tailored to individual landscapes and forest management scenarios, adjusting for oak mortality and stand development over time. We implemented published predictive models of average annual acorn production by five oak species common to the eastern United States in the Forest Vegetation Simulator (FVS) and used forest inventory data to estimate long-term acorn production on the Bent Creek Experimental Forest watershed, with and without oak decline. Under a no-management scenario, simulations forecasted a 58% increase in average annual acorn production by 2062 without oak decline but a 17% decrease with oak decline. Forecasts were influenced by the initial abundance and basal area of different oak species on the landscape and stand dynamics over time. Simulations indicated that heavy oak mortality with regeneration failure could substantially affect acorn production over the long term by reducing the proportion of mature canopy oaks and relative abundance of oak species. FVS ACORN provides a powerful tool for long-term acorn production planning that can be tailored to individual landscapes and forest management scenarios to predict average annual number and mass of acorns.}, number={2}, journal={Forest Science}, author={Greenberg, C.H. and Keyser, C.E. and Rathbun, L.C. and Rose, A.K. and Fearer, T.M. and McNab, W.H.}, year={2014}, pages={222–230} }
 @article{rathbun_lemay_smith_2011, title={Diameter growth models for mixed-species stands of Coastal British Columbia including thinning and fertilization effects}, volume={222}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79959332421&partnerID=MN8TOARS}, DOI={10.1016/j.ecolmodel.2011.04.004}, abstractNote={In this study, diameter growth models for three species growing in mixed-stands of Coastal British Columbia (BC), Canada, under a variety of silvicultural treatments were developed. The three species were: Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco), western hemlock (Tsuga heterophylla (Raf.) Sarg.), and western redcedar (Thuja plicata Donn). A Box and Lucas model (1959) was initially fitted to the diameter growth series for each tree, as this model is very flexible and was based on processes reflective of the metabolic processes governing tree growth. Next, a random coefficients modelling approach (i.e., parameter prediction approach) was used to modify the estimated parameters for each species using functions of tree size and stage of development, site productivity, and inter-tree competition variables, while accounting for temporal correlation within trees. Impacts of fertilization on diameter growth were estimated by including the time since fertilization as an additional variable. Since state variables that are changed as a result of thinning were already in the model, accurate results post-thinning were obtained with no changes to the model. For the combined effects of thinning and fertilization, a two-step additive approach was used, where the state variables were changed following thinning and the diameter increment was modified for fertilization using the time since fertilization variable. Results indicated that multiple treatments sustain a change in growth for a longer time period following treatment than thinning or fertilization alone.}, number={14}, journal={Ecological Modelling}, author={Rathbun, L.C. and LeMay, V. and Smith, N.}, year={2011}, pages={2234–2248} }
 @article{rathbun_lemay_smith_2010, title={Modeling mortality in mixed-species stands of coastal British Columbia}, volume={40}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-77958041008&partnerID=MN8TOARS}, DOI={10.1139/X10-089}, abstractNote={ Individual-tree distance-independent models were developed to estimate regular mortality for western hemlock ( Tsuga heterophylla (Raf.) Sarg.), Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. menziesii), and western redcedar ( Thuja plicata Donn ex D. Don) in the coastal temperate rain forests of British Columbia, Canada. Permanent plots remeasured at intervals ranging from 1 to 17 years were used. Because of the irregular remeasurement intervals, survival was estimated using a generalized logistic model and mortality was calculated by subtraction. Basal area of trees larger than the subject tree provided reasonably accurate mortality estimates for larger trees. However, poor results were obtained for trees less than 7.5 cm in diameter at breast height, which had higher mortality rates than the larger trees. Since the implementation of a survival (or mortality) model within a growth and yield model environment can largely affect estimation accuracy, three methods of implementing the model were also evaluated. A probability multiplier approach where the stems per hectare surviving to the next period is estimated by multiplying the probability of survival by the stems per hectare at the beginning of the time period is recommended. This is equivalent to a stochastic approach averaged over many repetitions but with much less processing time. }, number={8}, journal={Canadian Journal of Forest Research}, author={Rathbun, L.C. and LeMay, V. and Smith, N.}, year={2010}, pages={1517–1528} }