Is subarctic forest advance able to keep pace with climate change?

Recent climate warming and scenarios for further warming have led to expectations of rapid movement of ecological boundaries. Here we focus on the circumarctic forest-tundra ecotone (FTE), which represents an important bioclimatic zone with feedbacks from forest advance and corresponding tundra disappearance (up to 50% loss predicted this century) driving widespread ecological and climatic changes. We address FTE advance and climate history relations over the 20th century, using FTE response data from 151 sites across the circumarctic area and site-specific climate data. Specifically, we investigate spatial uniformity of FTE advance, statistical associations with 20th century climate trends, and whether advance rates match climate change velocities (CCVs). Study sites diverged into four regions (Eastern Canada; Central and Western Canada and Alaska; Siberia; and Western Eurasia) based on their climate history, although all were characterized by similar qualitative patterns of behaviour (with about half of the sites showing advancing behaviour). The main associations between climate trend variables and behaviour indicate the importance of precipitation rather than temperature for both qualitative and quantitative behaviours, and the importance of non-growing season as well as growing season months. Poleward latitudinal advance rates differed significantly among regions, being smallest in Eastern Canada (~10 m/year) and largest in Western Eurasia (~100 m/year). These rates were 1-2 orders of magnitude smaller than expected if vegetation distribution remained in equilibrium with climate. The many biotic and abiotic factors influencing FTE behaviour make poleward advance rates matching predicted 21st century CCVs (~103 -104  m/year) unlikely. The lack of empirical evidence for swift forest relocation and the discrepancy between CCV and FTE response contradict equilibrium model-based assumptions and warrant caution when assessing global-change-related biotic and abiotic implications, including land-atmosphere feedbacks and carbon sequestration.

Landscape genomic insights into the historic migration of mountain hemlock in response to Holocene climate change.

PREMISE OF THE STUDY: Untangling alternative historic dispersal pathways in long-lived tree species is critical to better understand how temperate tree species may respond to climatic change. However, disentangling these alternative pathways is often difficult. Emerging genomic technologies and landscape genetics techniques improve our ability to assess these pathways in natural systems. We address the question to what degree have microrefugial patches and long-distance dispersal been responsible for the colonization of mountain hemlock (Tsuga mertensiana) on the Alaskan Kenai Peninsula. METHODS: We used double-digest restriction-associated DNA sequencing (ddRADseq) to identify genetic variants across eight mountain hemlock sample sites on the Kenai Peninsula, Alaska. We assessed genetic diversity and linkage disequilibrium using landscape and population genetics approaches. Alternative historic dispersal pathways were assessed using discriminant analysis of principle components and electrical circuit theory. KEY RESULTS: A combination of decreasing diversity, high gene flow, and landscape connectivity indicates that mountain hemlock colonization on the Kenai Peninsula is the result of long-distance dispersal. We found that contemporary climate best explained gene flow patterns and that isolation by resistance was a better model explaining genetic variation than isolation by distance. CONCLUSIONS: Our findings support the conclusion that mountain hemlock colonization is the result of several long-distance dispersal events following Pleistocene glaciation. The high dispersal capability suggests that mountain hemlock may be able to respond to future climate change and expand its range as new habitat opens along its northern distribution.

Patterns of shrub expansion in Alaskan arctic river corridors suggest phase transition.

Recent increases in deciduous shrub cover are a primary focus of terrestrial Arctic research. This study examined the historic spatial patterns of shrub expansion on the North Slope of Alaska to determine the potential for a phase transition from tundra to shrubland. We examined the historic variability of landscape-scale tall shrub expansion patterns on nine sites within river valleys in the Brooks Range and North Slope uplands (BRNS) between the 1950s and circa 2010 by calculating percent cover (PCTCOV), patch density (PADENS), patch size variability (CVSIZE), mean nearest neighbor distance (MEDIST) and the multi-scale information fractal dimension (d I ) to assess spatial homogeneity for shrub cover. We also devised conceptual models for trends in these metrics before, during, and after a phase transition, and compared these to our results. By developing a regression equation between PCTCOV and d I and using universal critical d I values, we derived the PCTCOV required for a phase transition to occur. All nine sites exhibited increases in PCTCOV. Five of the nine sites exhibited an increase in PADENS, seven exhibited an increase in CVSIZE, and five exhibited a decrease in MEDIST. The d I values for each site exceeded the requirements necessary for a phase transition. Although fine-scale heterogeneity is still present, landscape-scale patterns suggest our study areas are either currently in a state of phase transition from tundra to shrubland or are progressing towards spatial homogeneity for shrubland. Our results indicate that the shrub tundra in the river valleys of the north slope of Alaska has reached a tipping point. If climate trends observed in recent decades continue, the shrub tundra will continue towards homogeneity with regard to the cover of tall shrubs.

Stage-structured matrix models for organisms with non-geometric development times.

Matrix models have been used to model population growth of organisms for many decades. They are popular because of both their conceptual simplicity and their computational efficiency. For some types of organisms they are relatively accurate in predicting population growth; however, for others the matrix approach does not adequately model growth rate. One of the reasons for the lack of accuracy is that most matrix-based models implicitly assume a specific degree of variability in development times for the organism. Because the variability is implicit, the implied variances are often not verified with experimental data. In this paper, we shall present extensions to the stage-classified matrix models so that organisms with arbitrary means and standard deviations of development times can be modeled.