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Kathryn M. Irvine

Publications and source records attributed to Kathryn M. Irvine.

At least 37 records · Page 2Linked to original sources
USGS2017

Assessment of imperfect detection of blister rust in whitebark pine within the Greater Yellowstone Ecosystem

We examined data on white pine blister rust (blister rust) collected during the monitoring of whitebark pine trees in the Greater Yellowstone Ecosystem (from 2004-2015). Summaries of repeat observations performed by multiple independent observers are reviewed and discussed. These summaries show variability among observers and the potential for errors being made in blister rust status. Based on this assessment, we utilized occupancy models to analyze blister rust prevalence while explicitly accounting for imperfect detection. Available covariates were used to model both the probability of a tree being infected with blister rust and the probability of an observer detecting the infection. The fitted model provided strong evidence that the probability of blister rust infection increases as tree diameter increases and decreases as site elevation increases. Most importantly, we found evidence of heterogeneity in detection probabilities related to tree size and average slope of a transect. These results suggested that detecting the presence of blister rust was more difficult in larger trees. Also, there was evidence that blister rust was easier to detect on transects located on steeper slopes. Our model accounted for potential impacts of observer experience on blister rust detection probabilities and also showed moderate variability among the different observers in their ability to detect blister rust. Based on these model results, we suggest that multiple observer sampling continue in future field seasons in order to allow blister rust prevalence estimates to be corrected for imperfect detection. We suggest that the multiple observer effort be spread out across many transects (instead of concentrated at a few each field season) while retaining the overall proportion of trees with multiple observers around 5-20%. Estimates of prevalence are confounded with detection unless it is explicitly accounted for in an analysis and we demonstrate how an occupancy model can be used to do account for this source of observation error.

idaho, Montana, Utah, Wyoming↗
USGS2016

Whitebark pine mortality related to white pine blister rust, mountain pine beetle outbreak, and water availability

Whitebark pine ( Pinus albicaulis ) forests in the western United States have been adversely affected by an exotic pathogen ( Cronartium ribicola , causal agent of white pine blister rust), insect outbreaks ( Dendroctonus ponderosae , mountain pine beetle), and drought. We monitored individual trees from 2004 to 2013 and characterized stand-level biophysical conditions through a mountain pine beetle epidemic in the Greater Yellowstone Ecosystem. Specifically, we investigated associations between tree-level variables (duration and location of white pine blister rust infection, presence of mountain pine beetle, tree size, and potential interactions) with observations of individual whitebark pine tree mortality. Climate summaries indicated that cumulative growing degree days in years 2006–2008 likely contributed to a regionwide outbreak of mountain pine beetle prior to the observed peak in whitebark mortality in 2009. We show that larger whitebark pine trees were preferentially attacked and killed by mountain pine beetle and resulted in a regionwide shift to smaller size class trees. In addition, we found evidence that smaller size class trees with white pine blister rust infection experienced higher mortality than larger trees. This latter finding suggests that in the coming decades white pine blister rust may become the most probable cause of whitebark pine mortality. Our findings offered no evidence of an interactive effect of mountain pine beetle and white pine blister rust infection on whitebark pine mortality in the Greater Yellowstone Ecosystem. Interestingly, the probability of mortality was lower for larger trees attacked by mountain pine beetle in stands with higher evapotranspiration. Because evapotranspiration varies with climate and topoedaphic conditions across the region, we discuss the potential to use this improved understanding of biophysical influences on mortality to identify microrefugia that might contribute to successful whitebark pine conservation efforts. Using tree-level observations, the National Park Service-led Greater Yellowstone Interagency Whitebark Pine Long-term Monitoring Program provided important ecological insight on the size-dependent effects of white pine blister rust, mountain pine beetle, and water availability on whitebark pine mortality. This ongoing monitoring campaign will continue to offer observations that advance conservation in the Greater Yellowstone Ecosystem.

Ecosphere↗
USGS2016

Extending ordinal regression with a latent zero-augmented beta distribution

Ecological abundance data are often recorded on an ordinal scale in which the lowest category represents species absence. One common example is when plant species cover is visually assessedwithin bounded quadrats and then assigned to pre-defined cover class categories.We present an ordinal beta hurdle model that directly models ordinal category probabilitieswith a biologically realistic beta-distributed latent variable.Ahurdle-at-zero model allows ecologists to explore distribution (absence) and abundance processes in an integrated framework. This provides an alternative to cumulative link models when data are inconsistent with the assumption that the odds ofmoving into a higher category are the same for all categories (proportional odds). Graphical tools and a deviance information criterion were developed to assess whether a hurdle-at-zero model should be used for inferences rather than standard ordinal methods. Hurdle-at-zero and non-hurdle ordinal models fit to vegetation cover class data produced substantially different conclusions.The ordinal beta hurdle model yielded more precise parameter estimates than cumulative logit models, although out-of-sample predictions were similar. The ordinal beta hurdle model provides inferences directly on the latent biological variable of interest, percent cover, and supports exploration of more realistic ecological patterns and processes through the hurdle-at-zero or two-part specification.We provide JAGS code as an on-line supplement. Supplementary materials accompanying this paper appear on-line.

Journal of Agricultural, Biological, and Environme↗
USGS2016

A goodness-of-fit test for occupancy models with correlated within-season revisits

Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and specifically evaluates occupancy model lack of fit related to correlation among detections within a sample unit. Our diagnostic tool is available for practitioners that serially deploy survey equipment as a way to achieve cost savings.

Ecology and Evolution↗
USGS2016

Semi-arid vegetation response to antecedent climate and water balance windows

Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.

Applied Vegetation Science↗
USGS2015

Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline

Aim Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making. Location Oregon and Washington, USA. Methods We developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km 2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines. Results Forest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis ( Myotis thysanodes ), canyon bat ( Parastrellus hesperus ) and pallid bat ( Antrozous pallidus ) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience. Main conclusions Landscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.

Oregon, Washington↗
USGS2015

Estimating the phenology of elk brucellosis transmission with hierarchical models of cause-specific and baseline hazards

Understanding the seasonal timing of disease transmission can lead to more effective control strategies, but the seasonality of transmission is often unknown for pathogens transmitted directly. We inserted vaginal implant transmitters (VITs) in 575 elk ( Cervus elaphus canadensis ) from 2006 to 2014 to assess when reproductive failures (i.e., abortions or still births) occur, which is the primary transmission route of Brucella abortus , the causative agent of brucellosis in the Greater Yellowstone Ecosystem. Using a survival analysis framework, we developed a Bayesian hierarchical model that simultaneously estimated the total baseline hazard of a reproductive event as well as its 2 mutually exclusive parts (abortions or live births). Approximately, 16% (95% CI = 0.10, 0.23) of the pregnant seropositive elk had reproductive failures, whereas 2% (95% CI = 0.01, 0.04) of the seronegative elk had probable abortions. Reproductive failures could have occurred as early as 13 February and as late as 10 July, peaking from March through May. Model results suggest that less than 5% of likely abortions occurred after 6 June each year and abortions were approximately 5 times more likely in March, April, or May compared to February or June. In western Wyoming, supplemental feeding of elk begins in December and ends during the peak of elk abortions and brucellosis transmission (i.e., Mar and Apr). Years with more snow may enhance elk-to-elk transmission on supplemental feeding areas because elk are artificially aggregated for the majority of the transmission season. Elk-to-cattle transmission will depend on the transmission period relative to the end of the supplemental feeding season, elk seroprevalence, population size, and the amount of commingling. Our statistical approach allowed us to estimate the probability density function of different event types over time, which may be applicable to other cause-specific survival analyses. It is often challenging to assess the cause of death, or in this case whether the reproductive event was an abortion or live birth. Accounting for uncertainty in the event type is an important future addition to our methodological approach.

Wyoming↗
USGS2015

Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers

Deep slab avalanches are particularly challenging to forecast. These avalanches are difficult to trigger, yet when they release they tend to propagate far and can result in large and destructive avalanches. We utilized a 44-year record of avalanche control and meteorological data from Bridger Bowl ski area in southwest Montana to test the usefulness of meteorological variables for predicting seasons and days with deep slab avalanches. We defined deep slab avalanches as those that failed on persistent weak layers deeper than 0.9 m, and that occurred after February 1st. Previous studies often used meteorological variables from days prior to avalanches, but we also considered meteorological variables over the early months of the season. We used classification trees and random forests for our analyses. Our results showed seasons with either dry or wet deep slabs on persistent weak layers typically had less precipitation from November through January than seasons without deep slabs on persistent weak layers. Days with deep slab avalanches on persistent weak layers often had warmer minimum 24-hour air temperatures, and more precipitation over the prior seven days, than days without deep slabs on persistent weak layers. Days with deep wet slab avalanches on persistent weak layers were typically preceded by three days of above freezing air temperatures. Seasonal and daily meteorological variables were found useful to aid forecasting dry and wet deep slab avalanches on persistent weak layers, and should be used in combination with continuous observation of the snowpack and avalanche activity.

Montana↗
USGS2015

Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling

Conceptual models are an integral facet of long-term monitoring programs. Proposed linkages between drivers, stressors, and ecological indicators are identified within the conceptual model of most mandated programs. We empirically evaluate a conceptual model developed for a regional aquatic and riparian monitoring program using causal models (i.e., Bayesian path analysis). We assess whether data gathered for regional status and trend estimation can also provide insights on why a stream may deviate from reference conditions. We target the hypothesized causal pathways for how anthropogenic drivers of road density, percent grazing, and percent forest within a catchment affect instream biological condition. We found instream temperature and fine sediments in arid sites and only fine sediments in mesic sites accounted for a significant portion of the maximum possible variation explainable in biological condition among managed sites. However, the biological significance of the direct effects of anthropogenic drivers on instream temperature and fine sediments were minimal or not detected. Consequently, there was weak to no biological support for causal pathways related to anthropogenic drivers’ impact on biological condition. With weak biological and statistical effect sizes, ignoring environmental contextual variables and covariates that explain natural heterogeneity would have resulted in no evidence of human impacts on biological integrity in some instances. For programs targeting the effects of anthropogenic activities, it is imperative to identify both land use practices and mechanisms that have led to degraded conditions (i.e., moving beyond simple status and trend estimation). Our empirical evaluation of the conceptual model underpinning the long-term monitoring program provided an opportunity for learning and, consequently, we discuss survey design elements that require modification to achieve question driven monitoring, a necessary step in the practice of adaptive monitoring. We suspect our situation is not unique and many programs may suffer from the same inferential disconnect. Commonly, the survey design is optimized for robust estimates of regional status and trend detection and not necessarily to provide statistical inferences on the causal mechanisms outlined in the conceptual model, even though these relationships are typically used to justify and promote the long-term monitoring of a chosen ecological indicator. Our application demonstrates a process for empirical evaluation of conceptual models and exemplifies the need for such interim assessments in order for programs to evolve and persist.

California, Colorado, Idaho, Montana, Nevada, Oreg↗
USGS2015

A plan for the North American Bat Monitoring Program (NABat)

The purpose of the North American Bat Monitoring Program (NABat) is to create a continent-wide program to monitor bats at local to rangewide scales that will provide reliable data to promote effective conservation decisionmaking and the long-term viability of bat populations across the continent. This is an international, multiagency program. Four approaches will be used to gather monitoring data to assess changes in bat distributions and abundances: winter hibernaculum counts, maternity colony counts, mobile acoustic surveys along road transects, and acoustic surveys at stationary points. These monitoring approaches are described along with methods for identifying species recorded by acoustic detectors. Other chapters describe the sampling design, the database management system (Bat Population Database), and statistical approaches that can be used to analyze data collected through this program.

Report↗
USGS2015

Evaluating physical habitat and water chemistry data from statewide stream monitoring programs to establish least-impacted conditions in Washington State

Various GIS-generated land-use predictor variables, physical habitat metrics, and water chemistry variables from 75 reference streams and 351 randomly sampled sites throughout Washington State were evaluated for effectiveness at discriminating reference from random sites within level III ecoregions. A combination of multivariate clustering and ordination techniques were used. We describe average observed conditions for a subset of predictor variables as well as proposing statistical criteria for establishing reference conditions for stream habitat in Washington. Using these criteria, we determined whether any of the random sites met expectations for reference condition and whether any of the established reference sites failed to meet expectations for reference condition. Establishing these criteria will set a benchmark from which future data will be compared.

Washington↗
USGS2014

Predicting foundation bunchgrass species abundances: Model-assisted decision-making in protected-area sagebrush steppe

Foundation species are structurally dominant members of ecological communities that can stabilize ecological processes and influence resilience to disturbance and resistance to invasion. Being common, they are often overlooked for conservation but are increasingly threatened from land use change, biological invasions, and over-exploitation. The pattern of foundation species abundances over space and time may be used to guide decision-making, particularly in protected areas for which they are iconic. We used ordinal logistic regression to identify the important environmental influences on the abundance patterns of bluebunch wheatgrass ( Pseudoroegneria spicata ), Thurber's needlegrass ( Achnatherum thurberianum ), and Sandberg bluegrass ( Poa secunda ) in protected-area sagebrush steppe. We then predicted bunchgrass abundances along gradients of topography, disturbance, and invasive annual grass abundance. We used model predictions to prioritize the landscape for implementation of a management and restoration decision-support tool. Models were fit to categorical estimates of grass cover obtained from an extensive ground-based monitoring dataset. We found that remnant stands of abundant wheatgrass and bluegrass were associated with steep north-facing slopes in higher and more remote portions of the landscape outside of recently burned areas where invasive annual grasses were less abundant. These areas represented only 25% of the landscape and were prioritized for protection efforts. Needlegrass was associated with south-facing slopes, but in low abundance and in association with invasive cheatgrass ( Bromus tectorum ). Abundances of all three species were strongly negatively correlated with occurrence of another invasive annual grass, medusahead ( Taeniatherum caput-medusae ). The rarity of priority bunchgrass stands underscored the extent of degradation and the need for prioritization. We found no evidence that insularity reduced invasibility; annual grass invasion represents a serious threat to protected-area bunchgrass communities. Our study area was entirely within the Wyoming big sagebrush ecological zone, understood to have inherently low resilience to disturbance and resistance to weed invasion. However, our study revealed important variation in abundance of the foundation species associated with resilience and resistance along the topographic-soil moisture gradient within this zone, providing an important foothold for conservation decision-making in these steppe ecosystems. We found the foundation species focus a parsimonious strategy linking monitoring to decision-making via biogeographic modeling.

Ecosphere↗
USGS2014

Evaluation of a combined macrophyte–epiphyte bioassay for assessing nutrient enrichment in the Portneuf River, Idaho, USA

We describe and evaluate a laboratory bioassay that uses Lemna minor L. and attached epiphytes to characterize the status of ambient and nutrient-enriched water from the Portneuf River, Idaho. Specifically, we measured morphological (number of fronds, longest surface axis, and root length) and population-level (number of plants and dry mass) responses of L. minor and community-level (ash-free dry mass [AFDM] and chlorophyll a [Chl a ]) responses of epiphytes to nutrient enrichment. Overall, measures of macrophyte biomass and abundance increased with increasing concentrations of dissolved phosphorus (P) and responded more predictably to nutrient enrichment than morphological measures. Epiphyte AFDM and Chl a were also greatest in P-enriched water; enrichments of N alone produced no measurable epiphytic response. The epiphyte biomass response did not directly mirror macrophyte biomass responses, illustrating the value of a combined macrophyte–epiphyte assay to more fully evaluate nutrient management strategies. Finally, the most P-enriched waters not only supported greater standing stocks of macrophyte and epiphytes but also had significantly higher water column dissolved oxygen and dissolved organic carbon concentrations and a lower pH. Advantages of this macrophyte–epiphyte bioassay over more traditional single-species assays include the use of a more realistic level of biological organization, a relatively short assay schedule (~10 days), and the inclusion of multiple biological response and water-quality measures.

Idaho↗
USGS2014

Demographic monitoring and population viability analysis of two rare beardtongues from the Uinta Basin

Energy development, in combination with other environmental stressors, poses a persistent threat to rare species endemic to energy-producing regions of the western United States. Demographic analyses of monitored populations can provide key information on the natural dynamics of threatened plant and animal populations and how these dynamics might be affected by present and future development. In the Uinta Basin in Utah and Colorado, Graham's beardtongue ( Penstemon grahamii ) and White River beardtongue ( Penstemon scariosus var. albifluvis ) are 2 rare endemic wildflowers that persist on oil shale habitats that are heavily impacted by current energy exploration and development and are slated for expanded traditional drilling and oil shale development. We described demographic characteristics and population viability for 2 populations of each species that have been monitored since 2004. First, we measured population size, survival rates, transitions between life stages, and recruitment by using individually marked plants at the 4 study areas. We then used matrix population models to determine stochastic population growth rates (λ) and the probability that each population would persist 50 years into the future, given current conditions. The 2 P. grahamii study plots had small populations, averaging 70 adult plants, and relatively constant and high survival in both vegetative and flowering plants. The 2 P. scariosus var. albifluvis study plots had populations that averaged 120 adult plants, with high and stable survival in flowering plants and variable survival in vegetative plants. Recruitment of new seedlings into all populations was low and variable, with most recruitment occurring in one or 2 years. Both P. grahamii populations had λ near 1.0 (stable). One P. scariosus var. albifluvis population appeared to be declining (λ = 0.97), whereas the other was increasing (λ = 1.16). Our analyses reveal populations that appear relatively stable, but that are susceptible to declines now and into the future. Increases in environmental variability, deterministic changes in habitat conditions or stressors, or a single catastrophic event could all have immediately deleterious impacts on the long-term growth trajectory of these populations.

Utah↗
USGS2014

Statistical assessment on a combined analysis of GRYN-ROMN-UCBN upland vegetation vital signs

As of 2013, Rocky Mountain and Upper Columbia Basin Inventory and Monitoring Networks have multiple years of vegetation data and Greater Yellowstone Network has three years of vegetation data and monitoring is ongoing in all three networks. Our primary objective is to assess whether a combined analysis of these data aimed at exploring correlations with climate and weather data is feasible. We summarize the core survey design elements across protocols and point out the major statistical challenges for a combined analysis at present. The dissimilarity in response designs between ROMN and UCBN-GRYN network protocols presents a statistical challenge that has not been resolved yet. However, the UCBN and GRYN data are compatible as they implement a similar response design; therefore, a combined analysis is feasible and will be pursued in future. When data collected by different networks are combined, the survey design describing the merged dataset is (likely) a complex survey design. A complex survey design is the result of combining datasets from different sampling designs. A complex survey design is characterized by unequal probability sampling, varying stratification, and clustering (see Lohr 2010 Chapter 7 for general overview). Statistical analysis of complex survey data requires modifications to standard methods, one of which is to include survey design weights within a statistical model. We focus on this issue for a combined analysis of upland vegetation from these networks, leaving other topics for future research. We conduct a simulation study on the possible effects of equal versus unequal probability selection of points on parameter estimates of temporal trend using available packages within the R statistical computing package. We find that, as written, using lmer or lm for trend detection in a continuous response and clm and clmm for visually estimated cover classes with “raw” GRTS design weights specified for the weight argument leads to substantially different results and/or computational instability. However, when only fixed effects are of interest, the survey package (svyglm and svyolr) may be suitable for a model-assisted analysis for trend. We provide possible directions for future research into combined analysis for ordinal and continuous vital sign indictors.

Natural Resource Report↗
USGS2014

Status of whitebarkpine in the Greater Yellowstone Ecosystem: A step-trend analysis comparing 2004-2007 to 2008-2011

Whitebark pine (Pinus albicaulis) is a foundation and keystone species in upper subalpine environments of the northern Rocky Mountains that strongly influences the biodiversity and productivity of high-elevation ecosystems (Tomback et al. 2001, Ellison et al. 2005). Throughout its historic range, whitebark pine has decreased significantly as a major component of high-elevation forests. As a result, it is critical to understand the challenges to whitebark pine—not only at the tree and stand level, but also as these factors influence the distribution of whitebark pine across the Greater Yellowstone Ecosystem (GYE). In 2003, the National Park Service (NPS) Greater Yellowstone Inventory & Monitoring Network identified whitebark pine as one of twelve significant natural resource indicators or vital signs to monitor (Jean et al. 2005, Fancy et al. 2009) and initiated a long-term, collaborative monitoring program. Partners in this effort include the U.S. Geological Survey, U.S. Forest Service, and Montana State University with representatives from each comprising the Greater Yellowstone Whitebark Pine Monitoring Working Group. The objectives of the monitoring program are to assess trends in (1) the proportion of live, whitebark pine trees (>1.4-m tall) infected with white pine blister rust (blister rust); (2) to document blister rust infection severity by the occurrence and location of persisting and new infections; (3) to determine mortality of whitebark pine trees and describe potential factors contributing to the death of trees; and (4) to assess the multiple components of the recruitment of understory whitebark pine into the reproductive population. In this report we summarize the past eight years (2004-2011) of whitebark pine status and trend monitoring in the GYE. Our study area encompasses six national forests (NF), two national parks (NP), as well as state and private lands in portions of Wyoming, Montana, and Idaho; this area is collectively described as the GYE here and in other studies. The sampling design is a probabilistic, twostage cluster design with stands of whitebark pine as the primary units and 10x50 m belt transects as the secondary units. Primary sampling units (stands) were selected randomly from a sample frame of approximately 10,770 mapped pure and mixed whitebark pine stands ≥2.0 hectares in the GYE (Dixon 1997, Landenburger 2012). From 2004 through 2007 (monitoring transect establishment or initial time-step), we established 176 permanent belt transects (secondary sampling units=176) in 150 whitebark pine stands and permanently marked approximately 4,740 individual trees >1.4 m tall to monitor long-term changes in blister rust infection and survival rates. Between 2008 and 2011 (revisit time-step), these same 176 transects were surveyed and again all previously tagged trees were observed for changes in blister rust infection and survival status. Objective 1. Using a combined ratio estimator, we estimated the proportion of live trees infected in the GYE in the initial time-step (2004-2007) to be 0.22 (0.031 SE). Following the completion of all surveys in the revisit time-step (2008-2011), we estimated the proportion of live trees infected with white pine blister rust as 0.23 (0.028 SE; Table 2). We detected no significant change in the proportion of trees infected in the GYE between the two time-steps. Objective 2. We documented blister rust canker locations as occurring in the canopy or bole. We compared changes in canker position between the initial time-step (2004-2007) and the revisit time-step (2008-2011) in order to assess changes in infection severity. This analysis included the 3,795 trees tagged during the initial time-step that were located and documented as alive at the end of the revisit time-step. At the end of the revisit time-step, we found 1,217 trees infected with blister rust. This includes the 287 newly tagged trees in the revisit time step of which 14 had documented infections. Of these 1,217 trees, 780 trees were infected with blister rust in both time steps. Trees with only canopy cankers made up approximately 43% (519 trees) of the total number of trees infected with blister rust at the end of the revisit time-step, while trees with only bole cankers comprised 20% (252 trees), and those with both canopy and bole cankers included 37% (446 trees) of the infected sample. A bole infection is considered to be more consequential than a canopy canker, as it compromises not only the overall longevity of the tree, but its functional capacity for reproductive output as well (Kendall and Arno 1990, Campbell and Antos 2000, McDonald and Hoff 2001, Schwandt and Kegley 2004). In addition to infection location, we also documented infection transition between the canopy and bole. Of the 780 live trees that were infected with blister rust in both time-steps, approximately 31% (242) maintained canopy cankers and 36% (281) retained bole infections at the end of the revisit time-step. Infection transition from canopy to bole occurred in 30% (234) of the revisit time-step trees while 3% (23) transitioned from bole to canopy infections during this period. Objective 3. To determine whitebark pine mortality, we resurveyed all belt transects to reassess the life status of permanently tagged trees >1.4 m tall. We compared the total number of live tagged trees recorded during monitoring transect establishment to the total number of resurveyed dead tagged trees recorded during the revisit time-step and identified all potential mortality-influencing conditions (blister rust, mountain pine beetle, fire and other). By the end of the revisit time-step, we observed a total of 975 dead tagged whitebark pine trees; using a ratio estimator, this represents a loss of approximately 20% (SE=4.35%) of the original live tagged tree population (GYWPMWG 2012). Objective 4. To investigate the proportion of live, reproducing tagged trees, we divided the total number of positively identified cone-bearing trees by the total number of live trees in the tagged tree sample at the end of the revisit time-step. To approximate the average density of recruitment trees per stand, trees ≤1.4 m tall were summed by stand (within the 500 m² transect area) and divided by the total number of stands. Reproducing trees made up approximately 24% (996 trees) of the total live tagged population at the end of the revisit time-step. Differentiating between whitebark pine and limber pine seedlings or saplings is problematic given the absence of cones or cone scars. Therefore, understory summaries as presented in this report may include individuals of both species when they are sympatric in a stand. The average density of small trees ≤1.4 m tall was 53 understory trees per 500 m². Raw counts of these understory individuals ranged from 0-635 small trees per belt transect. In addition, a total of 287 trees were added to the tagged tree population by the end of 2011. These newly tagged trees were individuals that upon subsequent revisits had reached a height of >1.4 m tall and subsequently added to the sample. Throughout the past decade in the GYE, monitoring has helped document shifts in whitebark pine forests; whitebark pine stands have been impacted by insect, pathogen, wildland fire, and other disturbance events. Blister rust infection is ubiquitous throughout the ecosystem and infection proportions are variable across the region. And while we have documented mortality of whitebark pine, we have also recorded considerable recruitment. We provide this first step-trend report as a quantifiable baseline for understanding the state of whitebark pine in the GYE. Many aspects of whitebark pine health are highly variable across the range of its distribution in the GYE. Through sustained implementation of the monitoring program, we will continue efforts to document and quantify whitebark pine forest dynamics as they arise under periodic upsurges in insect, pathogen, fire episodes, and climatic events in the GYE. Since its inception, this monitoring program perseveres as one of the only sustained longterm efforts conducted in the GYE with a singular purpose to track the health and status of this prominent keystone species.

Natural Resource Technical Report↗