Explore the vast range of titles available.

Aim Foliar fungi – pathogens, endophytes, epiphytes – form taxonomically diverse communities that affect plant health and productivity. The composition of foliar fungal communities is variable at spatial scales both small (e.g. individual plants) and large (e.g. continents), yet few studies have attempted to tease apart spatial from climatic factors influencing these communities. Moreover, few studies have sampled in more than 1 year to gauge interannual variation in community structure. Location The Pacific Northwest of western North America. Taxon Foliar fungi associated with the deciduous tree Populus trichocarpa. Methods In two consecutive years, we used DNA metabarcoding to characterize foliar fungal communities of Populus trichocarpa across its geographic range, which encompasses a sharp climatic transition as it crosses the Cascade Mountain Range. We used multivariate analyses to (a) test for and differentiate spatial and environmental factors affecting community composition and (b) test for temporal variation in community composition across spatial and environmental gradients. Results In both study years, we found that foliar fungal community composition varied among sites and between regions (east vs. west of the Cascades). We found that climate explained more variation in community composition than geographic distance, although the majority of variation explained by each was shared. We also found that interannual variation in community composition depended on environmental context: communities located in the dry, eastern portion of the tree's geographic range varied more between study years than those located in the wet, western portion of the tree's range. Main conclusions Our results suggest that the environment plays a greater role in structuring foliar fungal communities than dispersal limitation.

Patterns of genetic structure and diversity are largely mediated by a species’ ecological niche and sensitivity to climate variation. Some species with narrow ecological niches have been found to exhibit increased population differentiation, limited gene flow across populations, and reduced population genetic diversity. In this study, we examine patterns of population genetic structure and diversity of four bumble bee species that are broadly sympatric, but do not necessarily inhabit the same ecological niche in the Pacific Northwest of the United States. Testing for the effect of isolation by geographic distance (IBD) with linearized F st and D est found that Bombus sylvicola and B. mixtus exhibited significant IBD across populations. In contrast, both B. melanopygus and B. flavifrons , two species that are distributed across a broad elevation gradient, exhibited no IBD, a result further corroborated by Bayesian a priori population assignment tests. Furthermore, we discovered that B. sylvicola populations distributed on the Olympic Peninsula have significantly less average allelic diversity than populations distributed in the Cascade Mountains. Our results suggest that populations distributed in the Olympic Mountains represent a distinct genetic cluster relative to the Cascade Mountains, with B. sylvicola and B. mixtus likely experiencing the greatest degree of population genetic differentiation relative to B. flavifrons and B. melanopygus . While bumble bees are known to co-exist across a diversity of habitats, our results demonstrate that underlying population genetic structure and diversity may not necessarily be similar across species, and are largely governed by their respective niches.

Dendroecological studies of historical tree recruitment patterns suggest mixed‐severity fire effects are common in Douglas‐fir/western hemlock forests of the Pacific Northwest (PNW), USA, but empirical studies linking observed fire severity to tree regeneration response are needed to expand our understanding into the functional role of fire in this forest type. Recent increases in mixed‐severity fires offered this opportunity, so we quantified the abundance, spatial distribution, species richness, and community composition of regenerating trees across a mixed‐severity fire gradient (unburned–high‐severity fire) 10 and 22 yr post‐fire, and use our results to inform a discussion of fire's functional role in western Oregon Cascades Douglas‐fir forests. Regeneration abundance was unimodal across the fire severity gradient such that the greatest mean abundance followed moderate‐severity fire (25–75% basal area mortality). Similarly, the greatest number of species was present within the most 25‐m2 regeneration quadrants (most extensive distribution) following moderate‐severity fire, relative to any other fire severity class. On average, species richness also exhibited a unimodal distribution across the severity gradient, increasing by 100% in stands that experienced moderate‐severity fire relative to unburned forests or following high‐severity fire, as predicted by the Intermediate Disturbance Hypothesis. Several distinct regeneration communities emerged across the fire severity gradient, including early seral tree communities indicative of those observed in initial and relay floristics successional models for this forest type. Most significantly, moderate‐severity fire alters successional trajectories and facilitates the establishment of a more diverse tree regeneration community than observed following low‐ or high‐severity fire. These communities are reflective of the diverse overstory communities commonly encountered throughout this forest type. The emergence of these diverse forests is unlikely to develop or persist in the absence of moderate‐severity fire effects, and may be perpetuated longer by recurring moderate‐severity fire relative to experiencing stand replacing fire. Therefore, moderate‐severity fire may be the most functionally important fire effect in Douglas‐fir forests and should be better represented in successional models and more prominent in ecologically based fire and forest management.

Spatial patterns of pathogen prevalence are determined by ecological processes acting across multiple spatial scales. Host-pathogen interactions are influenced by community composition, landscape structure, and environmental factors. Explaining prevalence patterns requires an understanding of how local determinants of infection, such as community composition, are mediated by landscape characteristics and regional-scale environmental drivers. Here we investigate the role of local community interactions and the effects of landscape structure on the dynamics of barley and cereal yellow dwarf viruses (B/CYDV) in the open meadows of the Cascade Mountains of Oregon. B/CYDV is an aphid-transmitted, generalist pathogen of over 100 wild and cultivated grass species. We used variance components analysis and model selection techniques to partition the sources of variation in B/CYDV prevalence and to determine which abiotic and biotic factors influence host-pathogen interactions in a Cascades meadow system. B/CYDV prevalence in Cascades meadows varied by host species identity, with a significantly higher proportion of infected Festuca idahoensis individuals than Elymus glaucus or Bromus carinatus . Although there was significant variation in prevalence among host species and among meadows in the same meadow complex, there was no evidence of any significant variation in prevalence among different meadow complexes at a larger spatial scale. Variation in prevalence among meadows was primarily associated with the local community context (host identity, the relative abundance of different host species, and host species richness) and the physical landscape attributes of the meadow. These results highlight the importance of local host community composition, mediated by landscape characteristics such as meadow aspect, as a determinant of the spatial pattern of infection of a multi-host pathogen.

Spring snowmelt serves as the major hydrological contribution to many watersheds of the US West. Since the 1970s the conterminous western USA has seen an earlier arrival of spring snowmelt. The extremely low snowpack and early melt of 2015 in the Cascade Mountains may be a harbinger of winters to come, underscoring the interest in advancements in spring snowmelt monitoring. Target-of-opportunity and point measurements of snowmelt using meteorological stations or stream gauges are common sources of these data, however, there have been few attempts to identify snowmelt timing using remote sensing. In this study, we describe the creation of snowmelt timing maps (STMs) which identify the day of year that each pixel of a remotely sensed image transitions from \"snow-covered\" to \"no snow\" during the spring melt season, controlling for cloud coverage and ephemeral spring snow storms. Derived from the 500 m MODerate-resolution Imaging Spectroradiometer (MODIS) standard snow map, MOD10A2, this new dataset provides annual maps of snowmelt timing, with corresponding maps of cloud interference and interannual variability in snow coverage from 2001-2015. We first show that the STMs agree strongly with in-situ snow telemetry (SNOTEL) meteorological station measurements in terms of snowmelt timing. We then use the STMs to investigate the early snowmelt event of 2015 in the Cascade Mountains, USA, highlighting the protected areas of Mt. Rainier, Crater Lake, and Lassen Volcanic National Parks. In 2015 the Cascade Mountains experienced snowmelt 41 days earlier than the 2001-2015 average, with 25% of its land area melting>65 days earlier than average. The upper elevations of the Cascade Mountains experienced the greatest snowmelt anomaly. Our results are relevant to land managers and biologists as they plan adaptation strategies for mitigating the effects of climate change throughout temperate mountains.

Whitebark pine (Pinus albicaulis Engelm.) is a foundation species of high elevation forest ecosystems in the Cascade Mountain Range of Oregon, Washington, and British Columbia. We examined fire evidence on 55 fire history sites located in the Cascade Range. To estimate dates of historic fires we analyzed 57 partial cross-sections from fire-scarred trees plus 700 increment cores. The resulting 101 fire events indicate fire has been a widespread component of Cascadian whitebark pine stands. Results are site specific and vary considerably. Whitebark pine stands appear to burn in a variety of severities and frequencies. Sites where fire intervals were detected ranged from 9 to 314 years, with a median of 49 years, and averaging 67 years. Fire intervals shortened significantly with higher latitudes. In assessing the most recent fire event at each site, overall, 56 percent burned as stand replacing events. In the 20th century, the number of fires diminished significantly. Due to conservation imperatives, re-introducing fire should be undertaken with extreme care to avoid substantial mortality of this endangered species.

Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the Cascade Mountains, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras of logging trends that align with prevailing regulations and economic conditions. We used multiple logistic regression to determine the biophysical and anthropogenic factors that influence fine-scale selection of harvest stands in each time period. Results show that private lands forest cover became significantly reduced and more fragmented from 1985 to 2014. Variables linked to parameters of site conditions, location, climate, and vegetation greenness consistently distinguished harvest selection for each distinct era. This study demonstrates the utility of annual LULC data for investigating the underlying factors that influence land cover change.

Burn severity in forests is commonly assessed in the field with visual ordinal estimates such as the Composite Burn Index (CBI). However, how CBI (a composite of several individual field measures) relates to independent quantitative measures of burn severity (e.g. fire-caused tree mortality, surface charring) has not been widely tested. Here, we use field data from 315 plots in 14 fires in the north-western USA to ask: (1) how CBI relates to eight independent field measures of burn severity; and (2) how these relationships vary across gradients of pre-fire forest structure. Overall, CBI corresponded well with most independent field measures, but some measures of extreme burn severity (e.g. deep charring on trees and snags) were not captured by CBI. Additionally, some measures of canopy burn severity corresponded to lower CBI values in forests with larger average tree size (diameter and height) – potentially from decoupling of surface and canopy fire effects in stands with larger, fire-resistant trees. Our findings suggest continued broad utility of CBI, while highlighting how the correspondence of aggregate plot-level CBI to different measures of burn severity can vary with forest conditions. We also suggest considerations for broadening CBI to account for more extreme levels of burn severity.

Warmer and drier climate over the past few decades has brought larger fire sizes and increased annual area burned in forested ecosystems of western North America, and continued increases in annual area burned are expected due to climate change. As warming continues, fires may also increase in severity and produce larger contiguous patches of severely burned areas. We used remotely sensed burn-severity data from 125 fires in the northern Cascade Range of Washington, USA, to explore relationships between fire size, severity, and the spatial pattern of severity. We examined relationships between climate and the annual area burned and the size of wildfires over a 25-year period. We tested the hypothesis that increased fire size is commensurate with increased burn severity and increased spatial aggregation of severely burned areas. We also asked how local ecological controls might modulate these relationships by comparing results over the whole study area (the northern Cascade Range) to those from four ecological subsections within it. We found significant positive relationships between climate and fire size, and between fire size and the proportion of high severity and spatial-pattern metrics that quantify the spatial aggregation of high-severity areas within fires, but the strength and significance of these relationships varied among the four subsections. In areas with more contiguous subalpine forests and less complex topography, the proportion and spatial aggregation of severely burned areas were more strongly correlated with fire size. If fire sizes increase in a warming climate, changes in the extent, severity, and spatial pattern of fire regimes are likely to be more pronounced in higher-severity fire regimes with less complex topography and more continuous fuels.

Climate change could significantly influence seasonal streamflow and water availability in the snowpack-fed watersheds of Washington, USA. Descriptions of snowpack decline often use linear ordinary least squares (OLS) models to quantify this change. However, the region’s precipitation is known to be related to climate cycles. If snowpack decline is more closely related to these cycles, an OLS model cannot account for this effect, and thus both descriptions of trends and estimates of decline could be inaccurate. We used intervention analysis to determine whether snow water equivalent (SWE) in 25 long-term snow courses within the Olympic and Cascade Mountains are more accurately described by OLS (to represent gradual change), stationary (to represent no change), or step-stationary (to represent climate cycling) models. We used Bayesian information-theoretic methods to determine these models’ relative likelihood, and we found 90 models that could plausibly describe the statistical structure of the 25 snow courses’ time series. Posterior model probabilities of the 29 “most plausible” models ranged from 0.33 to 0.91 (mean = 0.58, s  = 0.15). The majority of these time series (55 %) were best represented as step-stationary models with a single breakpoint at 1976/77, coinciding with a major shift in the Pacific Decadal Oscillation. However, estimates of SWE decline differed by as much as 35 % between statistically plausible models of a single time series. This ambiguity is a critical problem for water management policy. Approaches such as intervention analysis should become part of the basic analytical toolkit for snowpack or other climatic time series data.