Applying climate change refugia to forest management and old-growth restoration.

Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of late-successional forests have prompted efforts to restore old-growth forest structure. One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old-growth structure may reduce the extent and number of CCR. We used remotely sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old-growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old-growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches.

Relationships between climate and phylogenetic community structure of fossil pollen assemblages are not constant during the last deglaciation.

Disentangling the influence of environmental drivers on community assembly is important to understand how multiple processes influence biodiversity patterns and can inform understanding of ecological responses to climate change. Phylogenetic Community Structure (PCS) is increasingly used in community assembly studies to incorporate evolutionary perspectives and as a proxy for trait (dis)similarity within communities. Studies often assume a stationary relationship between PCS and climate, though few studies have tested this assumption over long time periods with concurrent community data. We estimated two PCS metrics-Nearest Taxon Index (NTI) and Net Relatedness index (NRI)-of fossil pollen assemblages of Angiosperms in eastern North America over the last 21 ka BP at 1 ka intervals. We analyzed spatiotemporal relationships between PCS and seven climate variables, evaluated the potential impact of deglaciation on PCS, and tested for the stability of climate-PCS relationships through time. The broad scale geographic patterns of PCS remained largely stable across time, with overdispersion tending to be most prominent in the central and southern portion of the study area and clustering dominating at the longitudinal extremes. Most importantly, we found that significant relationships between climate variables and PCS (slope) were not constant as climate changed during the last deglaciation and new ice-free regions were colonized. We also found weak, but significant relationships between both PCS metrics (i.e., NTI and NRI) and climate and time-since-deglaciation that also varied through time. Overall, our results suggest that (1) PCS of fossil Angiosperm assemblages during the last 21ka BP have had largely constant spatial patterns, but (2) temporal variability in the relationships between PCS and climate brings into question their usefulness in predictive modeling of community assembly.