Climate change is expected to disproportionately impact high elevation ecosystems by disrupting current temperature and precipitation regimes. The future carbon balance of these systems is uncertain, given the interplay between longer growing season length and the potential for increased drought. Currently, the most robust inferences about ecosystem responses to changing climate come from the integration of experimental and observational methods. In this thesis, I utilize evidence from a warming experiment and an elevational gradient to gain insights into how aspects of ecosystem productivity and community functional composition change in response to the abiotic environment. First, I show that ecosystem productivity was similar in the heated and ambient treatment groups of the warming experiment. Net ecosystem productivity (NEP) was similar between treatments with only slightly increased NEP in the early season in the heated treatment. Important leaf functional traits (leaf mass per area, LMA; leaf dry matter content, LDMC) shifted with heating in directions associated with higher productivity, both at the community level and within species. While these results are counterintuitive, potential insight was provided by a soil cooling effect found in the heated plots in the early season. Second, I investigate ecosystem productivity across spatial and temporal gradients using phenology cameras. I show strong relationships between greenness indices generated from camera images and on-the-ground measurements of gross primary productivity (GPP). I also used changes in greenness indices early season to infer green-up rates, and found a strong pattern of increasing green-up rate with increasing elevation. Together, these studies highlight the importance of comparing experimental and gradient methods to assess how different spatial and temporal scales influence our conclusions about the effect of climate change on ecosystems.

Montane meadows comprise less than 5% of the landscape of the western Cascades of Oregon, but they provide habitat for diverse species of plants and pollinators. Little is known about plant-pollinator network structure at these sites. This study quantified plant-pollinator interactions over the summer of 2011, based on six observations of 10 permanent subplots in 15 meadows, stratified by size and isolation. The study examined (1) relationships between richness and abundance of flowers, pollinators, and interactions; (2) distribution of abundance and richness of flowers, pollinators, and interactions with regards to surrounding meadow habitat; (3) change in flower and pollinator abundance over the season; (4) factors associated with the presence of various guilds of pollinators; and (5) the structure of plant-pollinator networks. The study showed that (1) richness of pollinators increased 2x faster than richness of flowers with increased abundance; (2) density of flowers and interactions was positively correlated with meadow size and diversity of pollinators and interactions were both correlated with surrounding habitat at two spatial scales; (3) peak flower abundance coincided with or preceded peaks in pollinator populations; (4) abundance of three guilds of bees exhibited different patterns of association to surrounding habitat and meadow soil moisture corresponding to various dispersal potential and phenology of guild species; and (5) the number of network pairings for plants and pollinators increased with increasing species richness of potential interaction partners and all networks were found to be significantly nested. Results of this study indicate that plant-pollinator networks are complex assemblages of species, in which spatial and temporal patterns of habitat affect species composition and network structure. In particular, flower and pollinator abundance and richness are depressed in small and isolated meadows. Significant nestedness emerged as a pattern of network level organization across the study meadows. / Graduation date: 2013