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Dave Roberts

Publications and source records attributed to Dave Roberts.

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Assessing effects of nonnative crayfish on mosquito survival

Introductions of nonnative predators often reduce biodiversity and affect natural predator–prey relationships and may increase the abundance of potential disease vectors (e.g., mosquitoes) indirectly through competition or predation cascades. The Santa Monica Mountains (California, U.S.A.), situated in a global biodiversity hotspot, is an area of conservation concern due to climate change, urbanization, and the introduction of nonnative species. We examined the effect of nonnative crayfish (Procambarus clarkii) on an existing native predator, dragonfly nymphs (Aeshna sp.), and their mosquito larvae (Anopheles sp.) prey. We used laboratory experiments to compare the predation efficiency of both predators, separately and together, and field data on counts of dragonfly nymphs and mosquito larvae sampled from 13 local streams. We predicted a lower predation efficiency of crayfish compared with native dragonfly nymphs and a reduced predation efficiency of dragonfly nymphs in the presence of crayfish. Dragonfly nymphs were an order of magnitude more efficient predators than crayfish, and dragonfly nymph predation efficiency was reduced in the presence of crayfish. Field count data showed that populations of dragonfly nymphs and mosquito larvae were strongly correlated with crayfish presence in streams, such that sites with crayfish tended to have fewer dragonfly nymphs and more mosquito larvae. Under natural conditions, it is likely that crayfish reduce the abundance of dragonfly nymphs and their predation efficiency and thereby, directly and indirectly, lead to higher mosquito populations and a loss of ecosystem services related to disease vector control.

California

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

Riparian plant community structure in a managed hydrological regime

The hydrology of the Snake River in Grand Teton National Park is partly determined by releases from Jackson Lake Dam. The dam was first built in 1908 and became part of the National Park system when GTNP was expanded to include most of Jackson Hole. Completion of the present structure of Jackson Lake Dam occurred in 1917 and resulted in an increase above the natural level of Jackson Lake of 11.9 m. The Bureau of Reclamation (BOR) manages the dam and sets discharge schedules, primarily to meet agricultural needs, and to a lesser extent the needs of recreational river use. Major changes to the hydrological regime of the Snake River include lower than natural peak releases, decrease in frequency of extreme flood events , and unusually high flows from July to September. In addition , peak releases prior to 1957 were not synchronized with spring runoff but shifted to July or early August. Changes in inundation frequencies of floodplains , inundation duration and timing of peak flows have profound effects on the extent and composition of the riparian zone.

Wyoming