Modeling effects of climate change on spruce-fir forest ecosystems and associated priority bird populations
Eastern spruce-fir forest ecosystems are among the most vulnerable to climate change within the continuous US. The goal of this project was to develop tools to identify refugia sites most likely to support spruce-fir forest and its associated high-priority obligate spruce-fir bird species over the long-term under projected climate change scenarios. Specific research objectives included: (1) producing high-resolution (temporal and spatial) projections of spruce-fir forests, including stand characteristics like structure and composition; (2) estimating future changes in the distribution, productivity and stand characteristics of the spruce-fir forest type due to potential changes in climate; (3) comparing the distribution and condition of spruce-fir forest for different climate change scenarios to identify areas with key physiographic settings likely to support refugia for this forest type; (4) modeling bird occurrence, distribution, nesting phenology and productivity as functions of climate and these modeled values for forest structure and composition; (5) linking these bird-habitat models to projected climatic and forest conditions to predict future bird occurrence, distribution and nesting phenology and productivity across the region; and (6) identifying areas with the greatest richness of priority bird species across climate scenarios.
These objectives were accomplished using long-term vegetation, bird, and remote sensing data from spruce-fir forests across the Northeast and Great Lakes regions to predict the future extent and condition of spruce-fir forests and associated avifauna. In particular, the project combined count datasets for 14 spruce-fir forest bird species as well as, 25 long-term vegetation datasets, and Landsat imagery to develop a series of species distribution models. Models were used for predicting climate impacts on future habitat suitability for spruce-fir species and for evaluating recent dynamics in the location of the montane spruce-fir ecotone. Finally, maps of contemporary forest conditions were developed by combining field observations and Landsat imagery and will be central to future work focused on modeling the distribution of spruce-fir ecosystems and associated bird species under different climate change and management scenarios.
- Foster, J.R., A.W. D'Amato, and J.B. Bradford, Simulation of insect impacts on forest dynamics: Landsat defoliation maps predict growth declines in tree ring data. International Association for Landscape Ecology World Congress, Portland, OR. July 9, 2015.
- Foster, J.R., Summary of the project at the UMN Silviculture and Applied Forest Ecology Lab Group Meeting in St. Paul, MN. February 20, 2014.
- Foster, J.R., A.W. D’Amato, and J.B. Bradford, Characterizing the differential sensitivity of tree species and forest types to past weather variability using dendrochronological techniques. Ecological Society of America Annual Meeting, Minneapolis, MN. August 5-9, 2013.
- Ralston J., DeLuca W.V., Feldma R.E., King D.I. 2016. Realized climate niche breadth varies with population trend and distribution in North American birds. Global Ecology and Biogeography 25: 1173 – 1180 DOI :10.1111/geb.12490
- Ralston J., DeLuca W.V., Feldman R.E., King D.I. 2016. Population trends influence species ability to track climate change. Global Change Biology.,23, (4) DOI: 10.1111/gcb.13478
- Andrews, C. 2015. Modeling and forecasting the influence of current and future climate on eastern North American spruce-fir (Picea-Abies) forests. Master's Thesis, University of Maine, Orono.
- Ralston, J., King, D.I., Deluca, W.V., Niemi, G.J., Glennon, M.J., Carl, J.C., and Lambert, D.J. 2015. Analysis of combined data sets yields trend estimates for vulnerable spruce-fir birds in northern United Stated. Biological Conservation, 07/2015, Volume 287, p. 270-278
- Foster, J.R., and A.W. D'Amato. 2015. Montane forest ecotone moved downslope in northeastern US in spite of warming between 1984 and 2011. Global Change Biology, 09/2015.