Cynthia S. Loftin

PIT tags increase effectiveness of freshwater mussel recaptures

Abstract Translocations are used increasingly to conserve populations of rare freshwater mussels. Recovery of translocated mussels is essential to accurate assessment of translocation success. We designed an experiment to evaluate the use of passive integrated transponder (PIT) tags to mark and track individual freshwater mussels. We used eastern lampmussels (Lampsilis radiata radiata) as a surrogate for 2 rare mussel species. We assessed internal and external PIT-tag retention in the laboratory and field. Internal tag retention was high (75–100%), and tag rejection occurred primarily during the first 3 wk after tagging. A thin layer of nacre coated internal tags 3 to 4 mo after insertion, suggesting that long-term retention is likely. We released mussels with external PIT tags at 3 field study sites and recaptured them with a PIT pack (mobile interrogation unit) 8 to 10 mo and 21 to 23 mo after release. Numbers of recaptured mussels differed among study sites; however, we found more tagged mussels with the PIT-pack searches with visual confirmation (72–80%) than with visual searches alone (30–47%) at all sites. PIT tags offer improved recapture of translocated mussels and increased accuracy of posttranslocation monitoring.

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

Abstract.  Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models.

Landsat imagery reveals declining clarity of Maine's lakes during 1995–2010

Abstract.  Water clarity is a strong indicator of regional water quality. Unlike other common water-quality metrics, such as chlorophyll a, total P, or trophic status, clarity can be accurately and efficiently estimated remotely on a regional scale. Satellite-based remote sensing is useful in regions with many lakes where traditional field-sampling techniques may be prohibitively expensive. Repeated sampling of easily accessed lakes can lead to spatially irregular, nonrandom samples of a region. Remote sensing remedies this problem. We applied a remote monitoring protocol we had previously developed for Maine lakes >8 ha based on Landsat satellite data recorded during 1995–2010 to identify spatial and temporal patterns in Maine lake clarity. We focused on the overlapping region of Landsat paths 11 and 12 to increase availability of cloud-free images in August and early September, a period of relative lake stability and seasonal poor-clarity conditions well suited for annual monitoring. We divided Maine into 3 regions (northeastern, south-central, western) based on morphometric and chemical lake features. We found a general decrease in average statewide lake clarity from 4.94 to 4.38 m during 1995–2010. Water clarity ranged from 4 to 6 m during 1995–2010, but it decreased consistently during 2005–2010. Clarity in both the northeastern and western lake regions has decreased from 5.22 m in 1995 to 4.36 and 4.21 m, respectively, in 2010, whereas lake clarity in the south-central lake region (4.50 m) has not changed since 1995. Climate change, timber harvesting, or watershed morphometry may be responsible for regional water-clarity decline. Remote sensing of regional water clarity provides a more complete spatial perspective of lake water quality than existing, interest-based sampling. However, field sampling done under existing monitoring programs can be used to calibrate accurate models designed to estimate water clarity remotely.

An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers

Abstract.  State water-quality professionals developing new biological assessment methods often have difficulty relating assessment results to narrative criteria in water-quality standards. An alternative to selecting index thresholds arbitrarily is to include the Biological Condition Gradient (BCG) in the development of the assessment method. The BCG describes tiers of biological community condition to help identify and communicate the position of a water body along a gradient of water quality ranging from natural to degraded. Although originally developed for fish and macroinvertebrate communities of streams and rivers, the BCG is easily adapted to other habitats and taxonomic groups. We developed a discriminant analysis model with stream algal data to predict attainment of tiered aquatic-life uses in Maines water-quality standards. We modified the BCG framework for Maine stream algae, related the BCG tiers to Maines tiered aquatic-life uses, and identified appropriate algal metrics for describing BCG tiers. Using a modified Delphi method, 5 aquatic biologists independently evaluated algal community metrics for 230 samples from streams and rivers across the state and assigned a BCG tier (1–6) and Maine water quality class (AA/A, B, C, nonattainment of any class) to each sample. We used minimally disturbed reference sites to approximate natural conditions (Tier 1). Biologist class assignments were unanimous for 53% of samples, and 42% of samples differed by 1 class. The biologists debated and developed consensus class assignments. A linear discriminant model built to replicate a priori class assignments correctly classified 95% of 150 samples in the model training set and 91% of 80 samples in the model validation set. Locally derived metrics based on BCG taxon tolerance groupings (e.g., sensitive, intermediate, tolerant) were more effective than were metrics developed in other regions. Adding the algal discriminant model to Maines existing macroinvertebrate discriminant model will broaden detection of biological impairment and further diagnose sources of impairment. The algal discriminant model is specific to Maine, but our approach of explicitly tying an assessment tool to tiered aquatic-life goals is widely transferrable to other regions, taxonomic groups, and waterbody types.

A MULTIVARIATE ASSESSMENT OF CHANGES IN WETLAND HABITAT FOR WATERBIRDS AT MOOSEHORN NATIONAL WILDLIFE REFUGE, MAINE, USA

We assessed changes in vegetative structure of 49 impoundments at Moosehorn National Wildlife Refuge (MNWR), Maine, USA, between the periods 1984–1985 to 2002 with a multivariate, adaptive approach that may be useful in a variety of wetland and other habitat management situations. We used Mahalanobis Distance (MD) analysis to classify the refuge’s wetlands as poor or good waterbird habitat based on five variables: percent emergent vegetation, percent shrub, percent open water, relative richness of vegetative types, and an interspersion juxtaposition index that measures adjacency of vegetation patches. Mahalanobis Distance is a multivariate statistic that examines whether a particular data point is an outlier or a member of a data cluster while accounting for correlations among inputs. For each wetland, we used MD analysis to quantify a distance from a reference condition defined a priori by habitat conditions measured in MNWR wetlands used by waterbirds. Twenty-five wetlands declined in quality between the two periods, whereas 23 wetlands improved. We identified specific wetland characteristics that may be modified to improve habitat conditions for waterbirds. The MD analysis seems ideal for instituting an adaptive wetland management approach because metrics can be easily added or removed, ranges of target habitat conditions can be defined by field-collected data, and the analysis can identify priorities for single or multiple management objectives.

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters.

Mercury Bioaccumulation in Wood Frogs Developing in Seasonal Pools

Abstract Seasonal woodland pools contribute significant biomass to terrestrial ecosystems through production of pool-breeding amphibians. The movement of amphibian metamorphs potentially transports toxins bioaccumulated during larval development in the natal pool into the surrounding terrestrial environment. We documented total mercury (THg) in seasonal woodland pool water, sediment, litter, and Lithobates sylvaticus LeConte (Wood Frog) in Acadia National Park, ME. THg concentrations in pool water varied over the study season, increasing during April—June and remaining high in 2 of 4 pools upon October refill. Water in pools surrounded by softwoods had lower pH, greater dissolved organic carbon, and greater THg concentrations than pools surrounded by hardwoods, with seasonal patterns in sediment THg but not litter THg. THg increased rapidly from near or below detection in 1–2 week old embryos (<0.2 ng; 0–0.49 ppb wet weight) to 17.1–54.2 ppb in tadpoles within 6 weeks; 7.2–42.0% of THg was methyl Hg in tadpoles near metamorphosis. Metamorphs emigrating from seasonal pools may transfer mercury into terrestrial food webs.

Hibernal Habitat Selection by Wood Frogs (Lithobates sylvaticus) in a Northern New England Montane Landscape

Abstract Poikilothermic species, such as amphibians, endure harsh winter conditions via freeze-tolerance or freeze-avoidance strategies. Freeze-tolerance requires a suite of complex, physiological mechanisms (e.g., cryoprotectant synthesis); however, behavioral strategies (e.g., hibernal habitat selection) may be used to regulate hibernaculum temperatures and promote overwintering survival. We investigated the hibernal ecology of the freeze-tolerant Wood Frog (Lithobates sylvaticus) in north-central Maine. Our objectives were to characterize the species hibernaculum microclimate (temperature, relative humidity), evaluate hibernal habitat selection, and describe the spatial arrangement of breeding, post-breeding, and hibernal habitats. We monitored 15 frogs during two winters (2011/12: N = 10; 2012/13: N = 5), measured hibernal habitat features at micro (2 m) and macro (10 m) spatial scales, and recorded microclimate hourly in three strata (hibernaculum, leaf litter, ambient air). We compared these data to that of 57 random locations with logistic regression models, Akaike Information Criterion, and Kolmogorov–Smirnov tests. Hibernaculum microclimate was significantly different and less variable than leaf litter, ambient air, and random location microclimate. Model averaging indicated that canopy cover (−), leaf litter depth (+), and number of logs and stumps (+; microhabitat only) were important predictors of Wood Frog hibernal habitat. These habitat features likely act to insulate hibernating frogs from extreme and variable air temperatures. For example, decreased canopy cover facilitates increased snowpack depth and earlier snowpack accumulation and melt. Altered winter temperature and precipitation patterns attributable to climate change may reduce snowpack insulation, facilitate greater temperature variation in the underlying hibernacula, and potentially compromise Wood Frog winter survival.

Influence of Observers and Stream Flow on Northern Two-Lined Salamander (Eurycea bislineata bislineata) Relative Abundance Estimates in Acadia and Shenandoah National Parks, USA

Abstract We investigated effects of observers and stream flow on Northern Two-Lined Salamander (Eurycea bislineata bislineata) counts in streams in Acadia (ANP) and Shenandoah National Parks (SNP). We counted salamanders in 22 ANP streams during high flow (May to June 2002) and during low flow (July 2002). We also counted salamanders in SNP in nine streams during high flow (summer 2003) and 11 streams during low flow (summers 2001–02, 2004). In 2002, we used a modified cover-controlled active search method with a first and second observer. In succession, observers turned over 100 rocks along five 1-m belt transects across the streambed. The difference between observers in total salamander counts was not significant. We counted fewer E. b. bislineata during high flow conditions, confirming that detection of this species is reduced during high flow periods and that assessment of stream salamander relative abundance is likely more reliable during low or base flow conditions.

Lakes without Landsat? An alternative approach to remote lake monitoring with MODIS 250 m imagery

Abstract We evaluated use of MODIS 250 m imagery for remote lake monitoring in Maine. Despite limited spectral resolution (visible red and near infrared bands), the twice daily image capture has a potential advantage over conventionally used, often cloudy Landsat imagery (16 day interval) when short time windows are of interest. We analyzed 364 eligible (≥100 ha) Maine lakes during late summer (Aug–early Sep) 2000–2011. The red band was strongly correlated with natural log-transformed Secchi depth (SD), and the addition of ancillary lake and watershed variables explained some variability in ln(SD) (R2 = 0.68–0.85; 9 models). Weak spectral resolution and variable lake conditions limited accurate lake monitoring to relatively productive periods in late summer, as indicated by inconsistent, sometimes weak regressions during June and July when lakes were clearer and less stable (R2 = 0.19–0.74; 8 models). Additionally, SD estimates derived from 2 sets of concurrent MODIS and Landsat imagery generally did not agree unless Landsat imagery (30 m) was resampled to 250 m, likely owing to various factors related to scale. Average MODIS estimates exceeded those of Landsat by 0.35 and 0.49 m on the 2 dates. Overall, MODIS 250 m imagery are potentially useful for remote lake monitoring during productive periods when Landsat data are unavailable; however, analyses must occur when algal communities are stable and well-developed, are biased toward large lakes, may overestimate SD, and accuracy may be unreliable without non-spectral lake predictors.