A review of open top chamber (OTC) performance across the ITEX Network

Open top chambers (OTCs) were adopted as the recommended warming mechanism by the International Tundra Experiment (ITEX) network in the early 1990’s. Since then, OTCs have been deployed across the globe. Hundreds of papers have reported the impacts of OTCs on the abiotic environment and the biota. Here we review the impacts of the OTC on the physical environment, with comments on the appropriateness of using OTCs to characterize the response of biota to warming. The purpose of this review is to guide readers to previously published work and to provide recommendations for continued use of OTCs to understand the implications of warming on low stature ecosystems. In short, the OTC is a useful tool to experimentally manipulate temperature, however the characteristics and magnitude of warming varies greatly in different environments, therefore it is important to document chamber performance to maximize the interpretation of biotic response. When coupled with long-term monitoring, warming experiments are a valuable means to understand the impacts of climate change on natural ecosystems

Modeling macronuclear DNA regulation in two ciliates : Paramecium tetraurelia and Tetrahymena thermophila

A revision to existing models for regulating the macronuclear DNA content of the ciliates Paramecium tetraurelia and Tetrahymena thermophila explains previously unresolved observations. Using an independent parameter to regulate ciliate macronuclear DNA content allows the mass of P. tetraurelia to be linked with DNA regulation. A similar parameterization of the T. thermophila model accounts for observed generation-dependent variations. Introducing controlled selection rules on macronuclear DNA content in modeled populations of T. thermophila results in evolving periodic distributions. The amount of unequal macronuclear division in the population is then directly proportional to the frequency of the resulting oscillation. Unequal division acts to restore the distribution opposing the selection displacement. Another parameter related to the replication’s independence from macronucleus DNA content shows a critical value of the √2–1 such that higher values result in periodic variations while lower values do not.Science, Faculty ofUnreviewedUndergraduat

Mutation Load in Sunflower Inversions Is Negatively Correlated with Inversion Heterozygosity.

Recombination is critical both for accelerating adaptation and purging deleterious mutations. Chromosomal inversions can act as recombination modifiers that suppress local recombination in heterozygotes and thus, under some conditions, are predicted to accumulate such mutations. In this study, we investigated patterns of recombination, transposable element abundance, and coding sequence evolution across the genomes of 1,445 individuals from three sunflower species, as well as within nine inversions segregating within species. We also analyzed the effects of inversion genotypes on 87 phenotypic traits to test for overdominance. We found significant negative correlations of long terminal repeat retrotransposon abundance and deleterious mutations with recombination rates across the genome in all three species. However, we failed to detect an increase in these features in the inversions, except for a modest increase in the proportion of stop codon mutations in several very large or rare inversions. Consistent with this finding, there was little evidence of overdominance of inversions in phenotypes that may relate to fitness. On the other hand, significantly greater load was observed for inversions in populations polymorphic for a given inversion compared to populations monomorphic for one of the arrangements, suggesting that the local state of inversion polymorphism affects deleterious load. These seemingly contradictory results can be explained by the low frequency of inversion heterozygotes in wild sunflower populations, apparently due to divergent selection and associated geographic structure. Inversions contributing to local adaptation represent ideal recombination modifiers, acting to facilitate adaptive divergence with gene flow, while largely escaping the accumulation of deleterious mutations

Winters are changing: snow effects on Arctic and alpine tundra ecosystems

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes and biogeochemical cycling. We also compare studies of natural snow gradients with snow manipulation studies, altering snow depth and duration, to assess time scale difference of these approaches. The number of studies on snow in tundra ecosystems has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. In specific, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by manipulative studies (average 7.9 days advance, 5.5 days delay) were substantially lower than those observed over spatial gradients (mean range of 56 days) or due to interannual variation (mean range of 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates

Winters are changing: snow effects on Arctic and alpine tundra ecosystems

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes and biogeochemical cycling. We also compare studies of natural snow gradients with snow manipulation studies, altering snow depth and duration, to assess time scale difference of these approaches. The number of studies on snow in tundra ecosystems has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. In specific, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by manipulative studies (average 7.9 days advance, 5.5 days delay) were substantially lower than those observed over spatial gradients (mean range of 56 days) or due to interannual variation (mean range of 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates

Winters are changing: snow effects on Arctic and alpine tundra ecosystems

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates

Winters are changing:snow effects on Arctic and alpine tundra ecosystems

Abstract Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates