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USGS2024

2023-2024 Coastal sage scrub and chaparral community monitoring for western San Diego County

Western San Diego County is dominated by shrublands supporting biologically diverse native plant and animal communities. Widespread urbanization has led to regional habitat loss and fragmentation, and many species in these shrubland communities are rare, threatened, or endangered. Large-scale, multiple-species conservation planning has resulted in a regional preserve system that focuses on these shrubland communities. Several large-scale threats are leading to type conversion from shrub-dominated to non-native invasive annual grass-dominated vegetation. To understand the changes that are occurring to native shrublands, we have developed a vegetation monitoring program with several components at multiple spatial scales, focused on quantifying coastal sage scrub (CSS) and chaparral vegetation community characteristics. Several drivers of change associated with type conversion of native shrubland to non-native annual grassland have been identified by previous research including increasing fire frequency, nitrogen deposition from air pollution, and prolonged and intense drought associated with changing climate. Loss of ecological integrity indices have been proposed as useful measures of the threat of degradation and type conversion of shrublands in San Diego County. For this study, ecological integrity is defined as a system’s ability to maintain species’ relationships and functions comparable to natural habitat in the region. Previous studies have identified the percent cover of invasive non-native annual grasses as a proxy for overall ecological degradation (loss of integrity) that is consistent across native taxonomic groups. Increased cover of non-native grass is associated with lower integrity of the shrubland vegetation community as shrub-associated plant and animal species are replaced by species preferring grassy and disturbed habitats. The objectives of this CSS and chaparral vegetation community monitoring plan are to: 1) Determine the distribution, composition, structure, and integrity of CSS and chaparral vegetation communities on conserved lands in western San Diego County, 2) Identify whether these attributes of the vegetation communities are changing over time, and 3) Evaluate relationships of known drivers of change (threats) and environmental factors in association with changes in vegetation community attributes. The CSS and chaparral vegetation community monitoring program is divided into four components: 1) vegetation mapping, 2) GIS/remote sensing office analysis of landscape-scale data, 3) permanent field plots using Unmanned Aerial Systems (UAS) and field data collections, and 4) animal and target species surveys and rapid assessment protocols. The first component, which is not detailed in this vegetation monitoring plan, aims to map vegetation communities every 10-15 years based on a classification developed for western San Diego County. High resolution aerial imagery will be used to update the 2012 vegetation map and expand it across the entire study area. The second component uses remote sensing models to annually track ecological integrity of shrublands across the study area and will include a map of areas of change and areas of stability over several decades. These landscape-scale integrity classifications will be used to analyze ecological processes, threats, and abiotic factors relative to changes to shrubland ecological integrity over time and space. The third component includes field surveys of 100 permanent plots across areas historically mapped as shrublands. Surveys in the 1930s mapped vegetation types using plot data. By using this historical classification map, we included areas that have already type-converted from shrubland to non-native annual grassland. The plots were split between CSS (55 plots) and chaparral (45 plots) and stratified into four geographical eco-subregions to guarantee coverage over small patches of habitat along the heavily developed coast. Surveys will include the collection of UAS imagery at a very high resolution. Species-level identifications will be made from the imagery based on a plant list compiled of all species detected in the plot during a thorough field survey by botanists, combined with geo-referenced samples of plant species locations. In addition, herbaceous cover will be estimated in the field using nine 1-m diameter circles (one per subplot) to obtain ocular estimates of cover for each plant species within the circle frame. Soil samples will be collected and analyzed for important element compositions. These data will be analyzed to evaluate plot-level ecological integrity based on species composition and cover. Repeated monitoring will allow evaluation of changes in vegetation attributes over time with known drivers or threats and other environmental factors. In addition, analyses will focus on indicator species and various measures of biological diversity for the vegetation communities. Finally, animal species and rare plants will be assessed using either taxa-based rapid assessment protocols or specialized species-specific protocols for rarer species. The purpose of these assessments is to document the status, habitat, and threat covariates of specific species and confirm the species composition and diversity of animal taxonomic groups (e.g., pollinators). Diversity and abundance of animal species at vegetation plots will be used to refine measures and thresholds of ecological integrity. Rapid assessment protocols for animal taxonomic groups can include multiple detection methods such as, camera traps, cover boards, and bird point counts. Pollinators will be monitored at plots using a protocol currently being developed in conjunction with but separately from this plan. Target rare plant species will be monitored using the regional Inspect and Manage (IMG) protocol that measures the status of rare plant occurrences and habitat and threat covariates over time. Species-specific animal survey methods will be refined as these species are prioritized for future monitoring. The goal of this monitoring program is to classify CSS and chaparral vegetation community integrity, identify areas of degradation across western San Diego County, and characterize drivers, and environmental factors associated with loss of ecological integrity. A combination of vegetation mapping, landscape-scale remote sensing, and field plots will be used to address all the aspects of our research questions. Data compiled and collected will be available to conservation partners to help inform future management decisions.

California↗

USGS2019

Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets

Diatom data have been collected in large-scale biological assessments in the United States, such as the U.S. Environmental Protection Agency’s National Rivers and Streams Assessment (NRSA). However, the effectiveness of diatoms as indicators may suffer if inconsistent taxon identifications across different analysts obscure the relationships between assemblage composition and environmental variables. To reduce these inconsistencies, we harmonized the 2008–2009 NRSA data from nine analysts by updating names to current synonyms and by statistically identifying taxa with high analyst signal (taxa with more variation in relative abundance explained by the analyst factor, relative to environmental variables). We then screened a subset of samples with QA/QC data and combined taxa with mismatching identifications by the primary and secondary analysts. When these combined “slash groups” did not reduce analyst signal, we elevated taxa to the genus level or omitted taxa in difficult species complexes. We examined the variation explained by analyst in the original and revised datasets. Further, we examined how revising the datasets to reduce analyst signal can reduce inconsistency, thereby uncovering the variation in assemblage composition explained by total phosphorus (TP), an environmental variable of high priority for water managers. To produce a revised dataset with the greatest taxonomic consistency, we ultimately made 124 slash groups, omitted 7 taxa in the small naviculoid (e.g., Sellaphora atomoides ) species complex, and elevated Nitzschia , Diploneis , and Tryblionella taxa to the genus level. Relative to the original dataset, the revised dataset had more overlap among samples grouped by analyst in ordination space, less variation explained by the analyst factor, and more than double the variation in assemblage composition explained by TP. Elevating all taxa to the genus level did not eliminate analyst signal completely, and analyst remained the most important predictor for the genera Sellaphora , Mayamaea , and Psammodictyon , indicating that these taxa present the greatest obstacle to consistent identification in this dataset. Although our process did not completely remove analyst signal, this work provides a method to minimize analyst signal and improve detection of diatom association with TP in large datasets involving multiple analysts. Examination of variation in assemblage data explained by analyst and taxonomic harmonization may be necessary steps for improving data quality and the utility of diatoms as indicators of environmental variables.

Ecological Indicators↗

USGS2020

Trait‐based variation in host contribution to pathogen transmission across species and resource supplies

Two key knowledge gaps currently limit the development of more predictive and general models of pathogen transmission: (1) the physiological basis of heterogeneity in host contribution to pathogen transmission (reservoir potential) remains poorly understood, and (2) a general means of integrating the ecological dynamics of host communities has yet to emerge. If the traits responsible for differences in reservoir potential also modulate host community dynamics, these traits could be used to predict pathogen transmission as host communities change. In two greenhouse experiments, across 23 host species and two levels of resource supply, the reservoir potential of plant hosts increased significantly along the Leaf Economic Spectrum, a global axis of plant physiological trait covariation that features prominently in models of plant community ecology. This indicates that the traits of the Leaf Economic Spectrum underlie broad differences in reservoir potential across host species and resource supplies. Therefore, host traits could be used to integrate epidemiological models of pathogen transmission with ecological models of host community change.

Ecology↗

USGS2001

Role of environmental variability in evaluating stressor effects

In this chapter, we discuss how environmental variability affects the exposure of organisms and ecological systems to stressors, and give guidance on how to understand influences of stressors. We consider the characteristics of environmental variability and issues relating to the measurement of environmental variation. We discuss how to select the optimal indicators of ecological response in a variable natural environment. Finally, we suggest some approaches to incorporate environmental variability into resource management. In all cases we employ examples and case studies throughout to illustrate principles.

Book chapter↗

USGS2026

Identifying algal indicators for streamflow duration assessment methods in forested headwater streams

Streamflow duration assessment methods (SDAMs) are rapid tools for reach-scale streamflow duration classification. SDAMs use single-visit indicator data as surrogates because direct measurement of long-term flow duration is resource intensive. Algae (diatoms and soft-bodied algae) are potentially strong indicators of streamflow-duration class (SDC) because of geographical ubiquity and biodiversity across moisture gradients. Algal cover and algal assemblage data (presence/absence, density, and biovolume) at species- and genus-levels were analyzed from 508 samples across 22 ephemeral, 37 intermittent, and 51 perennial reaches distributed along 31 forested headwater streams within 4 ecoregions in the contiguous United States. Random forest models using species- and genus-level datasets to predict SDCs had classification accuracy ranging from 69.5% – 88.4%, with accuracy being highest for density, intermediate for presence/absence, lowest for biovolume data. Species-level models had 0.6% – 5.9% higher accuracy for density and presence/absence datasets than genus-level models. Based on their median ranks of minimum node depth among random forest models, season (wet vs dry) was a more important factor than habitat sampled (erosional vs depositional) when distinguishing ephemeral, intermittent and perennial but habitat was more important when distinguishing ephemeral from non-ephemeral reaches. Algal cover index (categorical visual-tactile assessment) was the most important indicator of SDC. Except for the red alga, Audouinella , the identified indicator taxa were diatoms. Our findings support epilithic algal cover as an SDAM indicator for forested headwater streams. Until taxonomic tools are available for field identifications, algal cover index and abundance of soft-bodied algae and live diatoms may be candidate indicators for regional SDAMs.

Illinois, Indiana, Kentucky, Ohio, New Hampshire, ↗

USGS2015

A Candidate Vegetation Index of Biological Integrity Based on Species Dominance and Habitat Fidelity

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas of the USA and are used in some states to make critical management decisions. An underlying concept of all VIBIs is that they respond negatively to disturbance. The Ohio VIBI (OVIBI) is calculated from 10 metrics, which are different for each wetland vegetation class. We present a candidate vegetation index of biotic integrity based on floristic quality (VIBI-FQ) that requires only two metrics to calculate an overall score regardless of vegetation class. These metrics focus equally on the critical ecosystem elements of diversity and dominance as related to a species’ degree of fidelity to habitat requirements. The indices were highly correlated but varied among vegetation classes. Both indices responded negatively with a published index of wetland disturbance in 261 Ohio wetlands. Unlike VIBI-FQ, however, errors in classifying wetland vegetation may lead to errors in calculating OVIBI scores. This is especially critical when assessing the ecological condition of rapidly developing ecosystems typically associated with wetland restoration and creation projects. Compared to OVIBI, the VIBI-FQ requires less field work, is much simpler to calculate and interpret, and can potentially be applied to all habitat types. This candidate index, which has been “standardized” across habitats, would make it easier to prioritize funding because it would score the “best” and “worst” of all habitats appropriately and allow for objective comparison across different vegetation classes.

Ecological Indicators↗

USGS2019

Multi-element fingerprinting of waters to evaluate connectivity among depressional wetlands

Establishing the connectivity among depressional wetlands is important for their proper management, conservation and restoration. In this study, the concentrations of 38 elements in surface water and porewater of depressional wetlands were investigated to determine chemical and hydrological connectivity of three hydrological types: recharge, flow-through, and discharge, in the Prairie Pothole Region of North America. Most element concentrations of porewater varied significantly by wetland hydrologic type ( p < 0.05), and increased along a recharge to discharge hydrologic gradient. Significant spatial variation of element concentrations in surface water was observed in discharge wetlands. Generally, higher element concentrations occurred in natural wetlands compared to wetlands with known disturbances (previous drainage and grazing). Electrical conductivity explained 42.3% and 30.5% of the variation of all element concentrations in porewater and surface water. Non-metric multidimensional scaling analysis showed that the similarity decreased from recharge to flow-through to discharge wetland in each sampling site. Cluster analysis confirmed that element compositions in porewater of interconnected wetlands were more similar to each other than to those of wetlands located farther away. Porewater and surface water in a restored wetland showed similar multi-element characteristics to natural wetlands. In contrast, depressional wetlands connected by seeps along a deactivated drain-tile path and a grazed wetland showed distinctly different multi-element characteristics compared to other wetlands sampled. Our findings confirm that the multi-element fingerprinting method can be useful for assessing hydro-chemical connectivity across the landscape, and indicate that element concentrations are not only affected by land use, but also by hydrological characteristics.

North Dakota↗

USGS2016

Fluctuating water depths affect American alligator ( Alligator mississippiensis ) body condition in the Everglades, Florida, USA

Successful restoration of wetland ecosystems requires knowledge of wetland hydrologic patterns and an understanding of how those patterns affect wetland plant and animal populations.Within the Everglades, Florida, USA restoration, an applied science strategy including conceptual ecological models linking drivers to indicators is being used to organize current scientific understanding to support restoration efforts. A key driver of the ecosystem affecting the distribution and abundance of organisms is the timing, distribution, and volume of water flows that result in water depth patterns across the landscape. American alligators (Alligator mississippiensis) are one of the ecological indicators being used to assess Everglades restoration because they are a keystone species and integrate biological impacts of hydrological operations through all life stages. Alligator body condition (the relative fatness of an animal) is one of the metrics being used and targets have been set to allow us to track progress. We examined trends in alligator body condition using Fulton’s K over a 15 year period (2000–2014) at seven different wetland areas within the Everglades ecosystem, assessed patterns and trends relative to restoration targets, and related those trends to hydrologic variables. We developed a series of 17 a priori hypotheses that we tested with an information theoretic approach to identify which hydrologic factors affect alligator body condition. Alligator body condition was highest throughout the Everglades during the early 2000s and is approximately 5–10% lower now (2014). Values have varied by year, area, and hydrology. Body condition was positively correlated with range in water depth and fall water depth. Our top model was the “Current” model and included variables that describe current year hydrology (spring depth, fall depth, hydroperiod, range, interaction of range and fall depth, interaction of range and hydroperiod). Across all models, interaction between range and fall water depth was the most important variable (relative weight of 1.0) followed by spring and fall water depths (0.99), range (0.96), hydroperiod (0.95) and interaction between range and hydroperiod (0.95). Our work provides additional evidence that restoring a greater range in annual water depths is important for improvement of alligator body condition and ecosystem function. This information can be incorporated into both planning and operations to assist in reaching Everglades restoration goals.

Florida↗

USGS2005

Leaf fluctuating asymmetry, soil disturbance and plant stress: A multiple year comparison using two herbs, Ipomoea pandurata and Cnidoscolus stimulosus

We studied Cnidoscolus stimulosus and Ipomoea pandurata, two common herbs of the Fall Line Sandhills to assess their potential as ecosystem level stress indicators. We focused on plants because they are among the most persistent organisms in terrestrial ecosystems. We used developmental instability as an indicator of plant population stress. Developmental instability is usually measured as deviations from symmetry, in traits that normally develop symmetrically. Thus, symmetry represents an idealized a priori phenotype. Stress presumably causes perturbations during development that may exceed the capacity of the organism to buffer or correct, resulting in developmental instability, and hence deviations from this ideal. Soil disturbance imposed by different land use patterns at Fort Benning, Georgia provided a gradient of soil disturbance. In 2000-2002 we collected plants from nine different sites representing three levels of disturbance. In addition, in 2002 we collected microhabitat data in 1 m quadrats surrounding each plant whose developmental stability we also assessed. The developmental instability of both species was influenced by land use patterns, whether or not the sites had been previously burned, and microhabitat variables. Developmental instability increased with soil disturbance, burning in the prior year, and as the percentage of bare ground increased around the target individual. To some extent, favorable microhabitat conditions reduced developmental instability in sites with medium and high soil disturbance, whereas unfavorable conditions at low soil disturbance sites increased developmental instability. As an indicator of community level stress, developmental instability is best used in conjunction with other indices of environmental quality. ?? Published by Elsevier Ltd.

Ecological Indicators↗

USGS2010

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.

Ecological Indicators↗

USGS2009

Impacts of acidification on macroinvertebrate communities in streams of the western Adirondack Mountains, New York, USA

Limited stream chemistry and macroinvertebrate data indicate that acidic deposition has adversely affected benthic macroinvertebrate assemblages in numerous headwater streams of the western Adirondack Mountains of New York. No studies, however, have quantified the effects that acidic deposition and acidification may have had on resident fish and macroinvertebrate communities in streams of the region. As part of the Western Adirondack Stream Survey, water chemistry from 200 streams was sampled five times and macroinvertebrate communities were surveyed once from a subset of 36 streams in the Oswegatchie and Black River Basins during 2003-2005 and evaluated to: (a) document the effects that chronic and episodic acidification have on macroinvertebrate communities across the region, (b) define the relations between acidification and the health of affected species assemblages, and (c) assess indicators and thresholds of biological effects. Concentrations of inorganic Al in 66% of the 200 streams periodically reached concentrations toxic to acid-tolerant biota. A new acid biological assessment profile (acidBAP) index for macroinvertebrates, derived from percent mayfly richness and percent acid-tolerant taxa, was strongly correlated (R2 values range from 0.58 to 0.76) with concentrations of inorganic Al, pH, ANC, and base cation surplus (BCS). The BCS and acidBAP index helped remove confounding influences of natural organic acidity and to redefine acidification-effect thresholds and biological-impact categories. AcidBAP scores indicated that macroinvertebrate communities were moderately or severely impacted by acidification in 44-56% of 36 study streams, however, additional data from randomly selected streams is needed to accurately estimate the true percentage of streams in which macroinvertebrate communities are adversely affected in this, or other, regions. As biologically relevant measures of impacts caused by acidification, both BCS and acidBAP may be useful indicators of ecosystem effects and potential recovery at the local and regional scale.

Ecological Indicators↗

USGS2010

The Index of Biological Integrity and the bootstrap revisited: an example from Minnesota streams

Multimetric indices, such as the Index of Biological Integrity (IBI), are increasingly used by management agencies to determine whether surface water quality is impaired. However, important questions about the variability of these indices have not been thoroughly addressed in the scientific literature. In this study, we used a bootstrap approach to quantify variability associated with fish IBIs developed for streams in two Minnesota river basins. We further placed this variability into a management context by comparing it to impairment thresholds currently used in water quality determinations for Minnesota streams. We found that 95% confidence intervals ranged as high as 40 points for IBIs scored on a 0–100 point scale. However, on average, 90% of IBI scores calculated from bootstrap replicate samples for a given stream site yielded the same impairment status as the original IBI score. We suggest that sampling variability in IBI scores is related to both the number of fish and the number of rare taxa in a field collection. A comparison of the effects of different scoring methods on IBI variability indicates that a continuous scoring method may reduce the amount of bias in IBI scores.

Minnesota↗

USGS2019

The power, potential, and pitfalls of open access biodiversity data in range size assessments: Lessons from the fishes

Geographic rarity is a driver of a species’ intrinsic risk of extinction. It encompasses multiple key components including range size, which is one of the most commonly measured estimates of geographic rarity. Range size estimates are often used to prioritize conservation efforts when there are multiple candidate species, because data for other components of rarity such as population size are sparse, or do not exist for species of interest. Range size estimates can provide rankings of species vulnerability to changing environments or threats, identifying rare species for future study or conservation initiatives. However, range sizes can be estimated by several different metrics, and the degree of overlap in the identification of the rarest or most common species across methodologies is not well understood. This knowledge gap compromises our ability to prioritize correctly rare species, and presents a particularly difficult challenge for stream-dwelling organisms with distributions constrained to river networks. We evaluated the relationship of multiple range size estimates of a subset of freshwater fishes native to the United States to determine the degree of overlap in rarity rankings using different data sources and grain sizes. We used publicly available, open access data from the Global Biodiversity Information Facility (GBIF) to calculate extent of occurrence (minimum convex polygons) and area of occupancy (total area occupied, measured across various grain sizes). We compared range sizes estimated using GBIF data with the best available estimates of current distributions described by publicly available digital maps (NatureServe) to evaluate the efficacy of GBIF data in assessments of range size. We found strong correlations between range size estimates across analytical approaches and data sources with no detectable bias of taxonomy. We found that variation among rarity rankings was highest for species with intermediate range sizes indicating that the approaches considered here generally converge when used to identify the rarest or the most common species. Importantly, our results show that the rarest, and perhaps the most vulnerable, species are consistently identified across common methodological approaches. More broadly, our results support the use of open access biodiversity data that include opportunistically collated and collected point occurrence records as a complement to coarse-grain (e.g., whole range map) approaches, as we observed no systematic bias or deviation across data sources in our analyses. This indicates databases such as the GBIF may help fill important fundamental and applied knowledge gaps for many poorly understood species, particularly in a broad-scale, multispecies framework.

Ecological Indicators↗

USGS2019

Temporal variability in stream fish assemblage metrics and implications for long-term monitoring

High natural variability in the condition of fish communities in headwater streams complicates detection of long-term responses to changes in water quality. As a result, little is known about the impacts and recovery of fishes from acid deposition in streams of New York. Twenty-one fish metrics from annual electrofishing surveys at 13 streams sites in the Catskill and Adirondack mountains were assessed to quantify temporal variability and identify effective monitoring strategies for detecting change in headwater stream fish assemblages. Metrics included the density and biomass of Brook Trout populations and entire fish communities using length-, area-, and effort-based standardization techniques. Linear mixed models were used to estimate changes in coefficients of variation (CV) for different classes of metrics and standardization techniques, and a simulation-based power analysis was conducted to assess differences in statistical power for each metric with various sampling designs. Metric CV varied significantly as a result of standardization technique and whether metrics were calculated for the entire community or Brook Trout only. The sampling effort necessary to detect a 30% change with power of 0.80 was strongly correlated with CV (R 2 = 0.77). The number of sampling events at the 13 sites needed to detect this change ranged from 1 to >60, suggesting metric selection can strongly affect statistical power and the resources necessary to detect change. Thus, metric selection is a complex decision that must consider study objectives and biological relevance, in addition to natural variability and statistical power. However, adequate statistical power was achieved at relatively small sample sizes using certain metrics, indicating that fish communities in headwater streams can be a valuable component of long-term assessments of acidification impacts and recovery.

New York↗

USGS2022

Evaluating acid-aluminum stress in streams of the Northeastern U.S. at watershed, fish community and physiological scales

In spite of overall improvements in air and water quality, biological stress from low pH and high concentrations of inorganic aluminum continue to impact fish and fish habitat in northeastern North America, with independent and interactive effects on individuals, populations and communities. Integrative indicators can therefore be useful in monitoring both impact and recovery across multiple scales. Using coupled water chemistry (pH, conductivity, and base cation and inorganic aluminum concentration), geographic (site elevation and watershed area) and biological (fish diversity, fish abundance, gill aluminum concentration and gill physiology) data, we developed an integrated indicator of acid aluminum stress across the White and Green mountains in central New England, USA. As has been established in a number of previous studies, preliminary analysis clearly indicated that across all sites, inorganic aluminum concentration was consistently greatest during the spring season. Structural Equation modelling (SEM) revealed that toxic conditions (concurrent low pH and high concentrations of inorganic aluminum) were well summarized with an integrated toxicity score, related to both base cation concentrations and elevation, with sites at higher elevations more likely to experience toxic conditions as well as low base cation concentrations. As hypothesized, fish diversity and abundance were negatively related to toxicity score. In spite of considerable variation among individuals, gill aluminum was positively related to toxicity score for both Atlantic salmon and brook trout. Observed elevated gill aluminum levels associated with reduced gill metabolic activity in Atlantic salmon smolts from impacted systems likely result in impaired osmoregulatory function and seawater tolerance. Overall, our results suggest that the integrated toxicity score metric is strongly associated with a syndrome of physiological stress, reduced abundance, and low species diversity for stream fishes in New England and can likely serve as a reliable indicator of continued impairment or recovery of acid-aluminum vulnerable systems in this ecoregion.

New Hampshire, Vermont↗

USGS2017

Trace element contamination in feather and tissue samples from Anna’s hummingbirds

Trace element contamination (17 elements; Be, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Ba, Hg, Tl, and Pb) of live (feather samples only) and deceased (feather and tissue samples) Anna's hummingbirds ( Calypte anna ) was evaluated. Samples were analyzed using inductively coupled plasma-mass spectrometry (ICP-MS; 17 elements) and atomic absorption spectrophotometry (Hg only). Mean plus one standard deviation (SD) was considered the benchmark, and concentrations above the mean + 1 SD were considered elevated above normal. Contour feathers were sampled from live birds of varying age, sex, and California locations. In order to reduce thermal impacts, minimal feathers were taken from live birds, therefore a novel method was developed for preparation of low mass feather samples for ICP-MS analysis. The study found that the novel feather preparation method enabled small mass feather samples to be analyzed for trace elements using ICP-MS. For feather samples from live birds, all trace elements, with the exception of beryllium, had concentrations above the mean + 1 SD. Important risk factors for elevated trace element concentrations in feathers of live birds were age for iron, zinc, and arsenic, and location for iron, manganese, zinc, and selenium. For samples from deceased birds, ICP-MS results from body and tail feathers were correlated for Fe, Zn, and Pb, and feather concentrations were correlated with renal (Fe, Zn, Pb) or hepatic (Hg) tissue concentrations. Results for AA spectrophotometry analyzed samples from deceased birds further supported the ICP-MS findings where a strong correlation between mercury concentrations in feather and tissue (pectoral muscle) samples was found. These study results support that sampling feathers from live free-ranging hummingbirds might be a useful, non-lethal sampling method for evaluating trace element exposure and provides a sampling alternative since their small body size limits traditional sampling of blood and tissues. The results from this study provide a benchmark for the distribution of trace element concentrations in feather and tissue samples from hummingbirds and suggests a reference mark for exceeding normal. Lastly, pollinating avian species are minimally represented in the literature as bioindicators for environmental trace element contamination. Given that trace elements can move through food chains by a variety of routes, our study indicates that hummingbirds are possible bioindicators of environmental trace element contamination.

Ecological Indicators↗

USGS2008

Changes in stream chemistry and biology in response to reduced levels of acid deposition during 1987-2003 in the Neversink River Basin, Catskill Mountains

Atmospheric acid deposition has decreased in the northeastern United States since the 1970s, resulting in modest increases in pH, acid-neutralizing capacity (ANC), and decreases in inorganic monomeric aluminum (AlIM) concentrations since stream chemistry monitoring began in the 1980s in the acid-sensitive upper Neversink River basin in the Catskill Mountains of New York. Stream pH has increased by 0.01 units/year during 1987-2003 at three sites in the Neversink basin as determined by Seasonal Kendall trend analysis. In light of this observed decrease in stream acidity, we sampled 12 stream sites within the Neversink River watershed for water chemistry, macroinvertebrates, fish, and periphytic diatoms in 2003 to compare with a similar data set collected in 1987. Metrics and indices that reflect sensitivity to stream acidity were developed with these biological data to determine whether changes in stream biota over the intervening 16 years parallel those of stream chemistry. Statistical comparisons of data on stream chemistry and an acid biological assessment profile (Acid BAP) derived from invertebrate data showed no significant differences between the two years. For pH and ANC, however, values in 2003 were generally lower than those in 1987; this difference likely resulted from higher streamflow in summer 2003. Despite these likely flow-induced changes in summer 2003, an ordination and cluster analysis of macroinvertebrate taxa based on the Acid BAP indicated that the most acidic sites in the upstream half of the East Branch Neversink River form a statistically significant separate cluster consistent with less acidic stream conditions. This analysis is consistent with limited recovery of invertebrate species in the most acidic reaches of the river, but will require additional improvement in stream chemistry before a stronger conclusion can be drawn. Data on the fish and periphytic diatom communities in 2003 indicate that slimy sculpin had not extended their habitat to upstream reaches that previously were devoid of this acid-intolerant species in 1987; a diatom acid-tolerance index indicates continued high-acid impact throughout most of the East Branch and headwaters of the West Branch Neversink River. ?? 2007 Elsevier Ltd. All rights reserved.

Ecological Indicators↗

USGS2024

Counting the chorus: A bioacoustic indicator of population density

Passive acoustic monitoring has grown in utility for tracking wildlife populations, although challenges remain when using acoustic detections to monitor population size and density. Distance sampling is considered the ‘gold standard’ for estimating animal densities but has several important limitations, especially for rare, cryptic, and high-density species. Here, we test the performance of a simple, quickly derived bioacoustic indicator for monitoring population density: call density—the proportion of recording samples containing vocalizations. Over three years, we collected synchronized bioacoustic and point-transect distance sampling data for eight forest bird species native to the Island of Hawai‘i, including four endangered species, across diverse ecosystems ranging from subalpine dry woodland to montane rainforest. The species studied exhibit varied population structures, from gregarious flocks to small, territorial family groups. Our results revealed significant, strong correlations between call density and distance sampling-based animal density estimates for all species, demonstrating that call density is a reliable indicator of animal density that can be used independently or in combination with traditional monitoring methods. Our analysis uses a fixed amount of manual validation of machine learning classifier output examples, without requiring prohibitively high classifier performance, and is robust to variation in vocal activity rates across time and space, making it both adaptable and scalable. This approach could enhance passive acoustic monitoring by providing a more sensitive population health indicator than commonly used detection/nondetection methods, facilitating prompt conservation and management decisions, particularly for species that are difficult to monitor with distance sampling.

Hawaii↗