Ecoregions of the United States

Nonnative M. vimineum has been expanding rapidly in the eastern United States, where it can negatively affect plant communities. Locally, the species is assumed to spread from roadsides into nearby forests, where it can form dense populations after disturbances, especially in light gaps. Using microsatellite markers, we quantified patterns of genetic variation and structure among populations at nine sites in West Virginia. We then examined patterns of local dispersal within each population, focusing on subpopulations along the roadside, those coalescing nearby along the forest edge, and subpopulations in the interior forest. We found that levels of genetic variation of M. vimineum were relatively low overall across populations but with genetic structure present among populations (Fst = 0.60). Within populations, subpopulations along the roadside were genetically variable, containing 4 to 22 unique, multilocus genotypes. Many of these genotypes were also identified in the adjacent forest, consistent with local, diffusive spread from the roadway. However, several genotypes in the interior forest were unique to the population, indicating that dispersal from other sites may also occur. Overall, it appears that genetic diversity and structure in M. vimineum reflects a variety of processes, including localized dispersal and long-distance migration.

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“…You should choose a biogeographic system(s) that is suitably scaled for your region. For example, Bailey's (1995) or…”

Section: Tailoring the Protocol For Specific Regions Of Interestmentioning

confidence: 99%

“…For example, Bailey's (1995) ecological regions would be appropriate for use for the contiguous United States, but not for the state of Delaware.…”

Section: Proportion Of Region's Biogeographic Units Invadedmentioning

confidence: 99%

Regional and Local Genetic Variation in Japanese Stiltgrass (Microstegium vimineum)

Culley

Huebner

Novy

2016

Invasive plant sci. manag.

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“…There is therefore a tradeoff between the ability to incorporate more climatic variability inherent in the longer state-based dataset and the ability to assess climate-fire relationships by vegetation type in the shorter agency-unit-based dataset. We chose to develop regional models for the period 1916-2006 to assess the role of climatic variability on fire area burned in the PNW, and to develop finer models for 1980-2006 at the level of Bailey's ecosections (Bailey, 1995) for the Pacific Northwest ecosystems in Washington: Coast Ranges / Olympic Mountains, Puget Trough / Willamette Valley, Western Cascades, Eastern Cascades, Okanogan Highlands, Palouse Prairie, Blue Mountains, and Columbia Basin.…”

Section: Climate and Area Burned By Firementioning

confidence: 99%

Forest ecosystems, disturbance, and climatic change in Washington State, USA

et al. 2010

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C limatic change is likely to affect Pacific Northwest (PNW) forests in several important ways. In this paper, we address the role of climate in four forest ecosystem processes and project the effects of future climatic change on these processes. First, we analyze how climate affects Douglas-fir growth across the region to understand potential changes in future growth. In areas where Douglas-fir is not water-limited, future growth will continue to vary with interannual climate variability, but in places where Douglas-fir is water-limited, growth is likely to decline due to projected increase in summer potential evapotranspiration. Second, we use existing analyses of climatic controls on future potential tree species ranges to highlight areas where species turnover may be greatest. By the mid 21 st century, some areas of the interior Columbia Basin and eastern Cascades are likely to have climates poorly suited to pine species that are susceptible to mountain pine beetle, and if these pines are climatically stressed, they may be more vulnerable to pine beetle attack. Climatic suitability for Douglas-fir is also likely to change, with substantial decreases in climatically suitable area in the Puget Trough and the Okanogan Highlands. Third, using regression approaches, we examine the relationships between climate and the area burned by fire in the PNW and in eight Washington ecosystems and project future area burned in response to changing climate. Area burned is significantly related to both temperature and precipitation in summer, but more physiologically relevant variables, such as water balance deficit, perform as well or better in models. Regional area burned is likely to double or even triple by the end of the 2040s, although Washington ecosystems have different sensitivities to climate and thus different responses to climatic change. Fourth, we evaluate the influence of climatic change on mountain pine beetle (MPB) outbreaks by quantifying both host-tree vulnerability and pine beetle adaptive seasonality. Host-tree vulnerability is closely related to vapor pressure deficit (VPD), and future projections support the hypothesis that summer VPD will increase over a significant portion of the range of host tree species. Due to the increased host 255vulnerability, MPB populations are expected to become more viable at higher elevations leading to increased incidence of MPB outbreaks. The increased rates of disturbance by fire and mountain pine beetle are likely to be more significant agents of changes in forest structure and composition in the 21st century than species turnover or declines in productivity. This suggests that understanding future disturbance regimes is critical for successful adaptation to climate change.

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“…Consequently, there are multiple ways to define ecoregions, reflecting differences in the parameters considered and their relative weights. Moreover, the fact that different levels of discrimination are possible leads to classifications that are commonly hierarchical, with smaller spatial units grouped into larger ones by increasing the range of variability used to define a class (Nowacki and others, 2001;Omernik, 1987;Bailey, 1995). Notwithstanding the complexity and ambiguity of ecoregional boundaries, an ecoregional classification is a useful tool for organizing monitoring and putting local results into a larger context.…”

Section: Ecoregional Structurementioning

confidence: 99%