SEARCH · Search USGS

Results for “Ecology Indicators”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56Linked to original sources

USGS2008

Does urbanization influence the spatial ecology of Gila monsters in the Sonoran Desert?

To assess whether urbanization influences the spatial ecology of a rare and protected venomous reptilian predator, the Gila monster Heloderma suspectum , we compared home range (HR) size and movement parameters at three sites varying in degree of urbanization in the Sonoran Desert. We predicted that the urban population of H. suspectum would exhibit smaller HRs, avoid human structures and show less movement. Multivariate analysis indicated that males generally exhibited larger HRs and had higher movement rates and activity levels than females at all three sites. Contrary to our predictions, however, HR size and movement parameters did not vary across the sites in relation to the level of urbanization. At the urban site, individuals often crossed narrow roads and regularly used artificial structures as refuges for extended periods. Furthermore, the population sex ratio at the urban site was female-biased, consistent with the expectation that occupation of larger HRs and higher movement rates results in higher mortality for males in urbanized areas. Gila monsters did not appear to alter certain aspects of their spatial ecology in response to low levels of human activity but additional work will be required to assess population viability and possible effects in the long term and with higher levels of urbanization.

Arizona↗

USGS2022

Spatially integrating microbiology and geochemistry to reveal complex environmental health issues: Anthrax in the contiguous United States

Maxent models were run using the B. anthracis presence data and/or the animal outbreak presence data. Models run using the animal outbreak data alone utilized two scales: the Outbreak State scale which included only states reporting animal anthrax outbreaks from 2001 to 2013 and the National scale which included all states in the contiguous United States. Three iterations of the environmental data were used and included the Sample Location dataset which utilized the environmental variable data with assigned latitude and longitude locations from the USGS NASGLP project; the Normalized dataset which scaled the environmental variables so that the values fell between 0 and 1; and the Interpolated dataset which provided an interpolation of the environmental variables averaged for each county and assigned to a point for that county at the centroid (rather than using the NASGLP latitude and longitude location). Two metrics were used to measure model performance including the widely used area under the curve (AUC) and an alternative method, the True Skill Statistic (TSS). The AUC gives the probability that a randomly chosen presence location has been correctly ranked higher than the absence/background site. AUC values at 0.5 or lower mean the ranking is no better than random, while the AUC values nearer to 1 mean the model is a better predictor. The TSS provides a comparison of how well the background predictions made by the model match the model results at the test dataset (presence) locations. TSS values near +1 means the model approaches perfect agreement, while values near −1 indicate the model is no better than random. Maxent models to determine the influence of environmental factors on the B. anthracis distribution using the PCR data yielded a low TSS, which suggested the model might be underfitting the data. This was not surprising due to the difficulty in recovering B. anthracis in soil samples as well as the samples themselves being discrete in nature and only capturing a snapshot in time. Therefore, the distribution of B. anthracis and its niche in the contiguous United States could not be determined in this study. However, efforts to investigate environmental factors that would have a higher potential of supporting an anthrax outbreak in wildlife and livestock yielded better results. Results showed that most of the Maxent models in this study performed best when using the Outbreak State scale. When the models were scaled up to the National scale, model performance declined, except for the Normalized variable dataset. At the Outbreak State scale, a large proportion of the area was predicted to be of higher probability for wildlife/livestock anthrax outbreaks, and the statistical measures assumed the model was underfitting the data. The model with the highest AUC and TSS scores for this study was the Outbreak State scale using Sample Location dataset (AUC = 0.918 and TSS = 0.82). Some of the variables found to be closely related to the occurrence of B. anthracis in this study included pH, drainage potential, and concentration of elements including Na, Ca, Sr, and Mg, which have also been found to be related to animal outbreaks or to the occurrence of B. anthracis in previous studies. The models in the current study indicated possible regions that have not had recent wildlife/livestock anthrax outbreaks but contained environmental conditions that could potentially support an outbreak if one were to occur (Michigan and Maine). This work provides an extension to the use of ecological niche modeling to outbreak potential in livestock/wildlife in the United States because it utilizes additional soil geochemistry data and has shown that further validation techniques, such as the TSS, should be considered in addition to AUC. Results from this study could be used by animal and public health officials to identify areas with a higher potential for anthrax outbreak in wildlife and livestock due to naturally occurring soil and environmental conditions.

Book chapter↗

USGS2021

Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach

A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics , and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.

North Carolina, South Carolina, Virginia↗

USGS2002

A landscape ecology approach to assessing development impacts in the tropics: A geothermal energy example in Hawaii

Geographic information systems (GIS) are increasingly being used in environmental impact assessments (EIA) because GIS is useful for analysing spatial impacts of various development scenarios. Spatially representing these impacts provides another tool for landscape ecology in environmental and geographical investigations by facilitating analysis of the effects of landscape patterns on ecological processes and examining change over time. Landscape ecological principles are applied in this study to a hypothetical geothermal development project on the Island of Hawaii. Some common landscape pattern metrics were used to analyse dispersed versus condensed development scenarios and their effect on landscape pattern. Indices of fragmentation and patch shape did not appreciably change with additional development. The amount of forest to open edge, however, greatly increased with the dispersed development scenario. In addition, landscape metrics showed that a human disturbance had a greater simplifying effect on patch shape and also increased fragmentation than a natural disturbance. The use of these landscape pattern metrics can advance the methodology of applying GIS to EIA.

Singapore Journal of Tropical Geography↗

USGS2021

Multi‐constrained catchment scale optimization of groundwater abstraction using linear programming

Due to increasing water demands globally, freshwater ecosystems are under constant pressure. Groundwater resources, as the main source of accessible freshwater, are crucially important for irrigation worldwide. Over‐abstraction of groundwater leads to declines in groundwater levels; consequently, the groundwater inflow to streams decreases. The reduction in base flow and alteration of the stream flow regime can potentially have an adverse impact on groundwater‐dependent ecosystems. A spatially distributed, coupled groundwater‐surface water model can simulate the impacts of groundwater abstraction on aquatic ecosystems. A constrained optimization algorithm and a simulation model in combination can provide an objective tool for the water practitioner to evaluate the interplay between economic benefits of groundwater abstractions and requirements to environmental flow. In this study, a holistic catchment‐scale groundwater abstraction optimization framework has been developed that allows for a spatially explicit optimization of groundwater abstraction, while fulfilling a pre‐defined maximum allowed reduction of stream flow (base flow (Q95) or median flow (Q50)) as constraint criteria for 1484 stream locations across the catchment. A balanced K‐Means clustering method was implemented to reduce the computational burden of the optimization. The model parameters and observation uncertainties calculated based on Bayesian linear theory allow for a risk assessment on the optimized groundwater abstraction values. The results from different optimization scenarios indicated that using the linear programming optimization algorithm in conjunction with integrated models provides valuable information for guiding the water practitioners in designing an effective groundwater abstraction plan with the consideration of environmental flow criteria important for the ecological status of the entire system.

Groundwater↗

USGS2015

Linking dynamic habitat selection with wading bird foraging distributions across resource gradients

Species distribution models (SDM) link species occurrence with a suite of environmental predictors and provide an estimate of habitat quality when the variable set captures the biological requirements of the species. SDMs are inherently more complex when they include components of a species' ecology such as conspecific attraction and behavioral flexibility to exploit resources that vary across time and space. Wading birds are highly mobile, demonstrate flexible habitat selection, and respond quickly to changes in habitat quality; thus serving as important indicator species for wetland systems. We developed a spatio-temporal, multi-SDM framework using Great Egret ( Ardea alba ), White Ibis ( Eudocimus albus ), and Wood Stork ( Mycteria Americana ) distributions over a decadal gradient of environmental conditions to predict species-specific abundance across space and locations used on the landscape over time. In models of temporal dynamics, species demonstrated conditional preferences for resources based on resource levels linked to differing temporal scales. Wading bird abundance was highest when prey production from optimal periods of inundation was concentrated in shallow depths. Similar responses were observed in models predicting locations used over time, accounting for spatial autocorrelation. Species clustered in response to differing habitat conditions, indicating that social attraction can co-vary with foraging strategy, water-level changes, and habitat quality. This modeling framework can be applied to evaluate the multi-annual resource pulses occurring in real-time, climate change scenarios, or restorative hydrological regimes by tracking changing seasonal and annual distribution and abundance of high quality foraging patches.

PLoS ONE↗

USGS2007

Multiple stressors in amphibian communities: Effects of chemical contamination, bullfrogs, and fish

A leading hypothesis of amphibian population declines is that combinations of multiple stressors contribute to declines. We examined the role that chemical contamination, competition, and predation play singly and in combination in aquatic amphibian communities. We exposed larvae of American toads (Bufo americanus), southern leopard frogs (Rana sphenocephala), and spotted salamanders (Ambystoma maculatum) to overwintered bullfrog tadpoles (R. catesbeiana), bluegill sunfish (Lepomis macrochirus), the insecticide carbaryl, and ammonium nitrate fertilizer in 1000-L mesocosms. Most significantly, our study demonstrated that the presence of multiple factors reduced survival of B. americanus and A. maculatum and lengthened larval periods of R. sphenocephala. The presence of bluegill had the largest impact on the community; it eliminated B. americanus and A. maculatum and reduced the abundance of R. sphenocephala. Chemical contaminants had the second strongest effect on the community with the insecticide, reducing A. maculatum abundance by 50% and increasing the mass of anurans (frogs and toads) at metamorphosis; the fertilizer positively influenced time and mass at metamorphosis for both anurans and A. maculatum. Presence of overwintered bullfrogs reduced mass and increased time to metamorphosis of anurans. While both bluegill and overwintered bullfrog tadpoles had negative effects on the amphibian community, they performed better in the presence of one another and in contaminated habitats. Our results indicate that predicting deleterious combinations from single-factor effects may not be straightforward. Our research supports the hypothesis that combinations of factors can negatively impact some amphibian species and could contribute to population declines. ?? 2007 by the Ecological Society of America.

Ecological Applications↗

USGS2015

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup ( Aythya ) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.

Ecological Applications↗

USGS2016

The influence of food abundance, food dispersion and habitat structure on territory selection and size of an Afrotropical terrestrial insectivore

Most tropical insectivorous birds, unlike their temperate counterparts, hold and defend a feeding and breeding territory year-around. However, our understanding of ecological factors influencing territory selection and size in tropical insectivores is limited. Here we examine three prominent hypotheses relating food abundance, food dispersion (spatial arrangement of food items), and habitat structure to territoriality in the Usambara Thrush Turdus roehli . We first compared leaf-litter macro-invertebrate abundance and dispersion, and habitat structure between territories and random sites. We then examined the relation between these same ecological factors and territory size. Invertebrate abundance and dispersion were sparsely and evenly distributed across our study system and did not vary between territories and random sites. In contrast, habitat structure did vary between territories and random sites indicating the Usambara Thrush selects territories with open understorey and closed overstorey habitat. Invertebrate abundance and dispersion within territories of the Usambara Thrush were not associated with habitat structure. We believe the most likely explanation for the Usambara Thrush’s preference for open understorey and closed overstorey habitat relates to foraging behavior. Using information-theoretic model selection we found that invertebrate abundance was the highest-ranked predictor of territory size and was inversely related, consistent with food value theory of territoriality.

Ostrich↗

USGS2015

Fire patterns in the range of the greater sage-grouse, 1984-2013 - Implications for conservation and management

Fire ranks among the top three threats to the greater sage-grouse ( Centrocercus urophasianus ) throughout its range, and among the top two threats in the western part of its range. The national research strategy for this species and the recent U.S. Department of the Interior Secretarial Order 3336 call for science-based threats assessment of fire to inform conservation planning and fire management efforts. The cornerstone of such assessments is a clear understanding of where fires are occurring and what aspects of fire regimes may be shifting outside of their historical range of variation. This report fulfills this need by describing patterns of fire area, fire size, fire rotation, and fire season length and timing from 1984 to 2013 across the range of the greater sage-grouse. This information need is further addressed by evaluating the ecological and management implications of these fire patterns. Analyses are stratified by major vegetation types and the seven greater sage-grouse management zones, delineated regionally as four western and three eastern management zones. Soil temperature and moisture indicators of resilience to fire and resistance to cheatgrass invasion, and the potential for establishment of a grass/fire cycle, are used as unifying concepts in developing fire threat assessments for each analysis strata. The results indicate that fire threats are higher in the four western than in the three eastern management zones. Among the four western management zones, the Snake River Plain and the Columbia Basin ranked somewhat higher than the Southern Great Basin and Northern Great Basin in terms of fire effects on sage-grouse habitat. These results support the previous high ranking of fire as a threat to the greater sage-grouse in the western region. In contrast, considering the low rankings for fire threats in the eastern region, it may be useful to reconsider the relative importance of wildfire as a threat to greater sage-grouse in those three management zones.

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

USGS2021

Ensemble species distribution model identifies survey opportunities for at-risk bearded beaksedge (Rhynchospora crinipes) in the southeastern United States

Locating additional occurrences of at-risk species can inform assessments of their status and conservation needs (including potential legal protections). The perennial bearded beaksedge ( Rhynchospora crinipes ) ranges from Mississippi to North Carolina, but known occurrences are limited. Because of the species' apparent rarity, a model to identify areas with suitable habitat conditions for the species will allow conservationists to effectively prioritize and allocate scarce surveying resources. We used known occurrence records, a suite of environmental datasets, and four species distribution modeling techniques (generalized additive, GAM; maximum entropy, MaxEnt; generalized boosted, GBM; and weighted ensemble) to generate maps to inform surveys for R. crinipes . The ensemble approach improved predictive performance (AUC-PR = 0.95) compared to other techniques (individual model AUC-PR ranged from 0.7 to 0.8). We also obtained quantitative insights on the species' habitat relationships, including the likelihood of R. crinipes 's presence near Atlantic white cedar ( Chamaecyparis thyoides ) habitat and floodplains, which is consistent with prior field observations. The ensemble model indicated that 3.6% of the study area could be suitable habitat, but only 0.38% had high suitability. Small stream riparian habitats and Atlantic swamp forests in Alabama, Florida, and Georgia had the highest proportion of suitable areas. Prioritizing surveys in areas with model-indicated high habitat suitability is expected to reveal additional R. crinipes occurrences. We suggest surveying efforts for other at-risk species may benefit from using an ensemble modeling approach to identify and prioritize survey areas and improve ecological knowledge of these species.

Alabama, Florida, Georgia, Mississippi, North Caro↗

USGS2018

Behavioral differences following ingestion of large meals and consequences for management of a harmful invasive snake: A field experiment

Many snakes are uniquely adapted to ingest large prey at infrequent intervals. Digestion of large prey is metabolically and aerobically costly, and large prey boluses can impair snake locomotion, increasing vulnerability to predation. Cessation of foraging and use of refugia with microclimates facilitating digestion are expected to be strategies employed by free‐ranging snakes to cope with the demands of digestion while minimizing risk of predation. However, empirical observations of such submergent behavior from field experiments are limited. The brown treesnake (Serpentes: Colubridae: Boiga irregularis ) is a nocturnal, arboreal, colubrid snake that was accidentally introduced to the island of Guam, with ecologically and economically costly consequences. Because tools for brown treesnake damage prevention generally rely on snakes being visible or responding to lures or baits while foraging, cessation of foraging activities after feeding would complicate management. We sought to characterize differences in brown treesnake activity, movement, habitat use, and detectability following feeding of large meals (rodents 33% of the snake's unfed body mass) via radio telemetry, trapping, and visual surveys. Compared to unfed snakes, snakes in the feeding treatment group showed drastic decreases in hourly and nightly activity rates, differences in refuge height and microhabitat type, and a marked decrease in detectability by trapping and visual surveys. Depression of activity lasted approximately 5–7 days, a period that corresponds to previous studies of brown treesnake digestion and cycles of detectability. Our results indicate that management strategies for invasive brown treesnakes need to account for cycles of unavailability and underscore the importance of preventing spread of brown treesnakes to new environments where large prey are abundant and periods of cryptic behavior are likely to be frequent. Characterization of postfeeding behavior changes provides a richer understanding of snake ecology and foraging models for species that consume large prey.

Ecology and Evolution↗

USGS2006

Ecological values of shallow-water habitats: Implications for the restoration of disturbed ecosystems

A presumed value of shallow-habitat enhanced pelagic productivity derives from the principle that in nutrient-rich aquatic systems phytoplankton growth rate is controlled by light availability, which varies inversely with habitat depth. We measured a set of biological indicators across the gradient of habitat depth within the Sacramento–San Joaquin River Delta (California) to test the hypothesis that plankton biomass, production, and pelagic energy flow also vary systematically with habitat depth. Results showed that phytoplankton biomass and production were only weakly related to phytoplankton growth rates whereas other processes (transport, consumption) were important controls. Distribution of the invasive clam Corbicula fluminea was patchy, and heavily colonized habitats all supported low phytoplankton biomass and production and functioned as food sinks. Surplus primary production in shallow, uncolonized habitats provided potential subsidies to neighboring recipient habitats. Zooplankton in deeper habitats, where grazing exceeded phytoplankton production, were likely supported by significant fluxes of phytoplankton biomass from connected donor habitats. Our results provide three important lessons for ecosystem science: (a) in the absence of process measurements, derived indices provide valuable information to improve our mechanistic understanding of ecosystem function and to benefit adaptive management strategies; (b) the benefits of some ecosystem functions are displaced by water movements, so the value of individual habitat types can only be revealed through a regional perspective that includes connectedness among habitats; and (c) invasive species can act as overriding controls of habitat function, adding to the uncertainty of management outcomes.

Ecosystems↗

USGS2015

The Everglades Depth Estimation Network (EDEN) surface-water model, version 2

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that generate daily water-level and water-depth data, and applications that compute derived hydrologic data across the freshwater part of the greater Everglades landscape. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN in order for EDEN to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The EDEN surface-water model, version 2 (V2), interpolates water-level data from a network of 240 gages to generate gridded daily water-level surfaces for the freshwater domain of the Everglades. When these spatiotemporal continuous surfaces are combined with EDEN’s digital elevation model of ground surface, derived hydrologic data provide scientists and water managers working in the Everglades with data necessary to analyze ecological and biotic responses to hydrologic changes in the Everglades. Derived datasets include water depth, recession rates, days since last dry, water-surface slopes, and hydroperiod. The V2 model includes enhancements from the previous model (version 1; V1) to accommodate changes in the water-level gage network, adjustments to water-level data, improved understanding of the flow dynamics (particularly near canals), and installation of an elevation benchmark network. Enhancements to the V2 model included Expansion of the EDEN domain: The model domain was expanded to include a part of southern Big Cypress National Preserve and northwestern Everglades National Park upstream of the marsh mangrove wetlands, thus completing the coastal connection along the southwestern boundary of the model; and Development of subdomain models: To account for insufficient water-control structure gage data at some subbasin boundaries, subdomain models were developed for five subdomains, and the resulting water-level surfaces were merged to generate the final water-level surface. Model performance statistics show a general improvement in the V2 model as compared to the V1 model. Overall, the root mean squared error (RMSE) was reduced by 2.42 centimeters (cm) to 4.68 cm. In Water Conservation Area 3A North and Water Conservation Area 3B, the RMSE was reduced by 10.88 and 9.15 cm, respectively. In addition to evaluating model performance statistics, 2-cm water-level maps were generated and evaluated for irregular contours that would indicate a potential problem either with data input or water-level estimates. Three applications of the EDEN-modeled water surfaces and other EDEN datasets are presented in the report to show how scientists and resource managers are using EDEN datasets to analyze biological and ecological responses to hydrologic changes in the Everglades. The biological responses of two important Everglades species, alligators and wading birds, to changes in hydrology are described. The effects of hydrology on fire dynamics in the Everglades are also discussed.

Florida↗

USGS2021

Gut microbial ecology of the Critically Endangered Fijian crested iguana (Brachylophus vitiensis): Effects of captivity status and host reintroduction on endogenous microbiomes

Animals often exhibit distinct microbial communities when maintained in captivity as compared to when in the wild. Such differentiation may be significant in headstart and reintroduction programs where individuals spend some time in captivity before release into native habitats. Using 16S rRNA gene sequencing, we (i) assessed differences in gut microbial communities between captive and wild Fijian crested iguanas ( Brachylophus vitiensis ) and (ii) resampled gut microbiota in captive iguanas released onto a native island to monitor microbiome restructuring in the wild. We used both cloacal swabs and fecal samples to further increase our understanding of gut microbial ecology in this IUCN Critically Endangered species. We found significant differentiation in gut microbial community composition and structure between captive and wild iguanas in both sampling schemes. Approximately two months postrelease, microbial communities in cloacal samples from formerly captive iguanas closely resembled wild counterparts. Interestingly, microbial communities in fecal samples from these individuals remained significantly distinct from wild conspecifics. Our results indicate that captive upbringings can lead to differences in microbial assemblages in headstart iguanas as compared to wild individuals even after host reintroduction into native conditions. This investigation highlights the necessity of continuous monitoring of reintroduced animals in the wild to ensure successful acclimatization and release.

Ecology and Evolution↗

USGS2023

Occupancy and activity patterns of nine-banded armadillos (Dasypus novemcinctus) in a suburban environment

The geographic range of the nine-banded armadillo ( Dasypus novemcinctus ) has rapidly been expanding within the United States for the last 150 years. One of the factors contributing to this astounding range expansion is the species’ ability to survive in and colonize human-dominated areas. Despite the fact that armadillos live alongside humans in numerous towns and cities across the Southeastern, Southcentral, and now Midwestern United States, we know relatively little about the behavior and ecology of armadillos in human-developed areas. Here, we used motion-triggered game cameras in over 115 residential yards in the rapidly developing Northwest corner of Arkansas to survey armadillos in a largely suburban environment. Our objectives were to explore trends in armadillo occupancy and daily activity patterns in a suburban setting. We documented armadillos in approximately 84% of the yards surveyed indicating that the species was widespread throughout the environment. We found that the species was more likely to occupy yards surrounded by a high proportion of forest cover. We found no relationship between armadillo occupancy and other land cover or development covariates. Only 2% of nearly 2000 armadillo detections occurred during the day indicating that the species is almost exclusively nocturnal during the summer months when living near humans in the suburban environment, which we suggest is likely an adaptation to avoid contact with humans and their dogs. As the armadillo continues to expand its geographic range to areas where it has not previously occurred, understanding how human development supports and facilitates the spread of this species can elucidate areas where conflict between humans and armadillos might occur allowing for preemptive management or education to mitigate conflict.

Diversity↗

USGS2021

Improving the ability of a BACI design to detect impacts within a kelp‐forest community

Distinguishing between human impacts and natural variation in abundance remains difficult because most species exhibit complex patterns of variation in space and time. When ecological monitoring data are available, a before‐after‐control‐impact (BACI) analysis can control natural spatial and temporal variation to better identify an impact and estimate its magnitude. However, populations with limited distributions and confounding spatial‐temporal dynamics can violate core assumptions of BACI‐type designs. In this study, we assessed how such properties affect the potential to identify impacts. Specifically, we quantified the conditions under which BACI analyses correctly (or incorrectly) identified simulated anthropogenic impacts in a spatially and temporally replicated data set of fish, macroalgal, and invertebrate species found on nearshore subtidal reefs in southern California, USA. We found BACI failed to assess very localized impacts, and had low power but high precision when assessing region‐wide impacts. Power was highest for severe impacts of moderate spatial scale, and impacts were most easily detected in species with stable, widely distributed populations. Serial autocorrelation in the data greatly inflated false impact detection rates, and could be partly controlled for statistically, while spatial synchrony in dynamics had no consistent effect on power or false detection rates. Unfortunately, species that offer high power to detect real impacts were also more likely to detect impacts where none had occurred. However, considering power and false detection rates together can identify promising indicator species, and collectively analyzing data for similar species improved the net ability to assess impacts. These insights set expectations for the sizes and severities of impacts that BACI analyses can detect in real systems, point to the importance of serial autocorrelation (but not of spatial synchrony), and indicate how to choose the species, and groups of species, that can best identify impacts.

Ecological Applications↗

USGS2022

Using biological responses to monitor freshwater post-spill conditions over 3 years in Blacktail Creek, North Dakota, USA

A pipeline carrying unconventional oil and gas (OG) wastewater spilled approximately 11 million liters of wastewater into Blacktail Creek, North Dakota, USA. Flow of the mix of stream water and wastewater down the channel resulted in storage of contaminants in the hyporheic zone and along the banks, providing a long-term source of wastewater constituents to the stream. A multi-level investigation was used to assess the potential effects of oil and brine spills on aquatic life. In this study, we used a combination of experiments using a native fish species, Fathead Minnow ( Pimephales promelas ), field sampling of the microbial community structure, and measures of estrogenicity. The fish investigation included in situ experiments and experiments with collected site water. Estrogenicity was measured in collected site water samples, and microbial community analyses were conducted on collected sediments. During the initial post-spill investigation, February 2015, performing in situ fish bioassays was impossible because of ice conditions. However, microbial community (e.g., the presence of members of the Halomonadaceae, a family that is indicative of elevated salinity) and estrogenicity differences were compared to reference sites and point to early biological effects of the spill. We noted water column effects on in situ fish survival 6 months post-spill during June 2015. At that time, total dissolved ammonium (sum of ammonium and ammonia, TAN) was 4.41 mg NH 4 /L with an associated NH 3 of 1.09 mg/L, a concentration greater than the water quality criteria established to protect aquatic life. Biological measurements in the sediment defined early and long-lasting effects of the spill on aquatic resources. The microbial community structure was affected during all sampling events. Therefore, sediment may act as a sink for constituents spilled and as such provide an indication of continued and cumulative effects post-spill. However, lack of later water column effects may reflect pulse hyporheic flow of ammonia from shallow ground water. Combining fish toxicological, microbial community structure and estrogenicity information provides a complete ecological investigation that defines potential influences of contaminants at organismal, population, and community levels. In general, in situ bioassays have implications for the individual survival and changes at the population level, microbial community structure defines potential changes at the community level, and estrogenicity measurements define changes at the individual and molecular level. By understanding effects at these various levels of biological organization, natural resource managers can interpret how a course of action, especially for remediation/restoration, might affect a larger group of organisms in the system. The current work also reviews potential effects of additional constituents defined during chemistry investigations on aquatic resources.

North Dakota↗