Harvester ant seed removal in an invaded sagebrush ecosystem: Implications for restoration.

A better understanding of seed movement in plant community dynamics is needed, especially in light of disturbance-driven changes and investments into restoring degraded plant communities. A primary agent of change within the sagebrush-steppe is wildfire and invasion by non-native forbs and grasses, primarily cheatgrass (Bromus tectorum). Our objectives were to quantify seed removal and evaluate ecological factors influencing seed removal within degraded sagebrush-steppe by granivorous Owyhee harvester ants (Pogonomyrmex salinus Olsen). In 2014, we sampled 76 harvester ant nests across 11 plots spanning a gradient of cheatgrass invasion (40%-91% cover) in southwestern Idaho, United States. We presented seeds from four plant species commonly used in postfire restoration at 1.5 and 3.0 m from each nest to quantify seed removal. We evaluated seed selection for presented species, monthly removal, and whether biotic and abiotic factors (e.g., distance to nearest nest, temperature) influenced seed removal. Our top model indicated seed removal was positively correlated with nest height, an indicator of colony size. Distance to seeds and cheatgrass canopy cover reduced seed removal, likely due to increased search and handling time. Harvester ants were selective, removing Indian ricegrass (Achnatherum hymenoides) more than any other species presented. We suspect this was due to ease of seed handling and low weight variability. Nest density influenced monthly seed removal, as we estimated monthly removal of 1,890 seeds for 0.25 ha plots with 1 nest and 29,850 seeds for plots with 15 nests. Applying monthly seed removal to historical restoration treatments across the western United States showed harvester ants can greatly reduce seed availability at degraded sagebrush sites; for instance, fourwing saltbush (Atriplex canescens) seeds could be removed in <2 months. Collectively, these results shed light on seed removal by harvester ants and emphasize their potential influence on postfire restoration within invaded sagebrush communities.

Climate change, woodpeckers, and forests: Current trends and future modeling needs.

The structure and composition of forest ecosystems are expected to shift with climate-induced changes in precipitation, temperature, fire, carbon mitigation strategies, and biological disturbance. These factors are likely to have biodiversity implications. However, climate-driven forest ecosystem models used to predict changes to forest structure and composition are not coupled to models used to predict changes to biodiversity. We proposed integrating woodpecker response (biodiversity indicator) with forest ecosystem models. Woodpeckers are a good indicator species of forest ecosystem dynamics, because they are ecologically constrained by landscape-scale forest components, such as composition, structure, disturbance regimes, and management activities. In addition, they are correlated with forest avifauna community diversity. In this study, we explore integrating woodpecker and forest ecosystem climate models. We review climate-woodpecker models and compare the predicted responses to observed climate-induced changes. We identify inconsistencies between observed and predicted responses, explore the modeling causes, and identify the models pertinent to integration that address the inconsistencies. We found that predictions in the short term are not in agreement with observed trends for 7 of 15 evaluated species. Because niche constraints associated with woodpeckers are a result of complex interactions between climate, vegetation, and disturbance, we hypothesize that the lack of adequate representation of these processes in the current broad-scale climate-woodpecker models results in model-data mismatch. As a first step toward improvement, we suggest a conceptual model of climate-woodpecker-forest modeling for integration. The integration model provides climate-driven forest ecosystem modeling with a measure of biodiversity while retaining the feedback between climate and vegetation in woodpecker climate change modeling.

Thermal conditions within tree cavities in ponderosa pine (Pinus ponderosa) forests: potential implications for cavity users.

Tree cavities provide critical roosting and breeding sites for multiple species, and thermal environments in these cavities are important to understand. Our objectives were to (1) describe thermal characteristics in cavities between June 3 and August 9, 2014, and (2) investigate the environmental factors that influence cavity temperatures. We placed iButtons in 84 different cavities in ponderosa pine (Pinus ponderosa) forests in central Washington, and took hourly measurements for at least 8 days in each cavity. Temperatures above 40 °C are generally lethal to developing avian embryos, and ~ 18% of the cavities had internal temperatures of ≥ 40 °C for at least 1 h of each day. We modeled daily maximum cavity temperature, the amplitude of daily cavity temperatures, and the difference between the mean internal cavity and mean ambient temperatures as a function of several environmental variables. These variables included canopy cover, tree diameter at cavity height, cavity volume, entrance area, the hardness of the cavity body, the hardness of the cavity sill (which is the wood below the cavity entrance which forms the barrier between the cavity and the external environment), and sill width. Ambient temperature had the largest effect size for maximum cavity temperature and amplitude. Larger trees with harder sills may provide more thermally stable cavity environments, and decayed sills were positively associated with maximum cavity temperatures. Summer temperatures are projected to increase in this region, and additional research is needed to determine how the thermal environments of cavities will influence species occupancy, breeding, and survival.

The role of wood hardness in limiting nest site selection in avian cavity excavators.

Woodpeckers and other primary cavity excavators (PCEs) are important worldwide for excavating cavities in trees, and a large number of studies have examined their nesting preferences. However, quantitative measures of wood hardness have been omitted from most studies, and ecologists have focused on the effects of external tree- and habitat-level features on nesting. Moreover, information is lacking on the role of wood hardness in limiting nesting opportunities for this important guild. Here, we used an information theoretic approach to examine the role of wood hardness in multi-scale nest site selection and in limiting nesting opportunities for six species of North American PCEs. We found that interior wood hardness at nests (n = 259) differed from that at random sites, and all six species of PCE had nests with significantly softer interior wood than random trees (F1,517 = 106.15, P < 0.0001). Accordingly, interior wood hardness was the most influential factor in our models of nest site selection at both spatial scales that we examined: in the selection of trees within territories and in the selection of nest locations on trees. Moreover, regardless of hypothesized excavation abilities, all the species in our study appeared constrained by interior wood hardness, and only 4-14% of random sites were actually suitable for nesting. Our findings suggest that past studies that did not measure wood hardness counted many sites as available to PCEs when they were actually unsuitable, potentially biasing results. Moreover, by not accounting for nest site limitations in PCEs, managers may overestimate the amount of suitable habitat. We therefore urge ecologists to incorporate quantitative measures of wood hardness into PCE nest site selection studies, and to consider the limitations faced by avian cavity excavators in forest management decisions.

Occupancy of red-naped sapsuckers in a coniferous forest: using LiDAR to understand effects of vegetation structure and disturbance.

Red-naped sapsuckers (Sphyrapicus nuchalis) are functionally important because they create sapwells and cavities that other species use for food and nesting. Red-naped sapsucker ecology within aspen (Populus tremuloides) has been well studied, but relatively little is known about red-naped sapsuckers in conifer forests. We used light detection and ranging (LiDAR) data to examine occupancy patterns of red-naped sapsuckers in a conifer-dominated system. We surveyed for sapsuckers at 162 sites in northern Idaho, USA, during 2009 and 2010. We used occupancy models and an information-theoretic approach to model sapsucker occupancy as a function of four LiDAR-based metrics that characterized vegetation structure and tree harvest, and one non-LiDAR metric that characterized distance to major roads. We evaluated model support across a range of territory sizes using Akaike's information criterion. Top model support was highest at the 4-ha extent, which suggested that 4 ha was the most relevant scale describing sapsucker occupancy. Sapsuckers were positively associated with variation of canopy height and harvested area, and negatively associated with shrub and large tree density. These results suggest that harvest regimes and structural diversity of vegetation at moderate extents (e.g., 4 ha) largely influence occurrence of red-naped sapsuckers in conifer forests. Given the current and projected declines of aspen populations, it will be increasingly important to assess habitat relationships, as well as demographic characteristics, of aspen-associated species such as red-naped sapsuckers within conifer-dominated systems to meet future management and conservation goals.

Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale.

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.

Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models.

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species-energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during -50% of the surveys in occupied sample units. The overall naive estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to -0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (-0.04-0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America.

Estimating temporal trend in the presence of spatial complexity: a Bayesian hierarchical model for a wetland plant population undergoing restoration.

Monitoring programs that evaluate restoration and inform adaptive management are important for addressing environmental degradation. These efforts may be well served by spatially explicit hierarchical approaches to modeling because of unavoidable spatial structure inherited from past land use patterns and other factors. We developed bayesian hierarchical models to estimate trends from annual density counts observed in a spatially structured wetland forb (Camassia quamash [camas]) population following the cessation of grazing and mowing on the study area, and in a separate reference population of camas. The restoration site was bisected by roads and drainage ditches, resulting in distinct subpopulations ("zones") with different land use histories. We modeled this spatial structure by fitting zone-specific intercepts and slopes. We allowed spatial covariance parameters in the model to vary by zone, as in stratified kriging, accommodating anisotropy and improving computation and biological interpretation. Trend estimates provided evidence of a positive effect of passive restoration, and the strength of evidence was influenced by the amount of spatial structure in the model. Allowing trends to vary among zones and accounting for topographic heterogeneity increased precision of trend estimates. Accounting for spatial autocorrelation shifted parameter coefficients in ways that varied among zones depending on strength of statistical shrinkage, autocorrelation and topographic heterogeneity--a phenomenon not widely described. Spatially explicit estimates of trend from hierarchical models will generally be more useful to land managers than pooled regional estimates and provide more realistic assessments of uncertainty. The ability to grapple with historical contingency is an appealing benefit of this approach.

Experimental and ecological implications of evening bird surveys in stream-riparian ecosystems.

Stream-riparian ecosystems are dynamic and complex entities that can support high levels of bird assemblage abundance and diversity. The myriad patches (e.g., aquatic, floodplain, riparian) found in the riverscape habitat mosaic attract a unique mixture of aquatic, semiaquatic, riparian, and upland birds, each uniquely utilizing the river corridor. Whereas standard morning bird surveys are widely used across ecosystems, the variety of bird guilds and the temporal habitat partitioning that likely occur in stream-riparian ecosystems argue for the inclusion of evening surveys. At 41 stream reaches in Vermont and Idaho, USA, we surveyed bird assemblages using a combination of morning and evening fixed-width transect counts. Student's paired t-tests showed that while bird abundance was not significantly different between morning and evening surveys, bird assemblage diversity (as measured by species richness, Shannon-Weiner's index, and Simpson's index) was significantly higher in the morning than in the evening. NMS ordinations of bird species and time (i.e., morning, evening) indicated that the structure of morning bird assemblages was different from that of evening assemblages. NMS further showed that a set of species was only found in evening surveys. The inclusion of evening counts in surveying bird assemblages in stream-riparian ecosystems has important experimental and ecological implications. Experimentally, the sole use of morning bird surveys may significantly underestimate the diversity and misrepresent the community composition of bird assemblages in these ecosystems. Ecologically, many of the birds detected in evening surveys were water-associated species that occupy high trophic levels and aerial insectivores that represent unique aquatic-terrestrial energy transfers.