A Markov model for assessing ecological stability properties

Ecological systems are frequently modeled as dynamic systems. It is natural then to use the techniques of dynamic systems theory to analyze such models. However, the methods and results that are produced by dynamic systems theory do not always capture the aspects of ecological systems that are of greatest interest to managers and decision-makers. We identify some of the challenges of using dynamic systems theory to explore ecological systems and propose an alternative approach that emphasizes the understanding of transient effects in light of uncertainty and variability. We illustrate this method by an examination of a model for phosphorus levels in fresh water lakes.     

Inferring linear feature use in the presence of GPS measurement error

Global Positioning System (GPS) collars are increasingly used to study animal movement and habitat use. Measurement error is defined as the difference between the observed and true value being measured. In GPS data measurement error is referred to as location error and leads to misclassification of observed locations into habitat types. This is particularily true when studying habitats of small spatial extent with large amounts of edge, such as linear features (e.g. roads and seismic lines). However, no consistent framework exists to address the effect of measurement error on habitat classification of observed locations and resulting biological inference. We developed a mechanistic, empirically-based method for buffering linear features that minimizes the underestimation of animal use introduced by GPS measurement error. To do this we quantified the distribution of measurement error and derived an explicit formula for buffer radius which incorporated the error distribution, the width of the linear feature, and a predefined amount of acceptable type I error in location classification. In our empirical study we found the GPS measurement error of the Lotek GPS_3300 collar followed a bivariate Laplace distribution with parameter ρ = 0.1123. When we applied our method to a simulated landscape, type I error was reduced by 57%. This study highlights the need to address the effect of GPS measurement error in animal location classification, particularily for habitats of small spatial extent.     

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance-based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods.     

NEAR‐STREAM LANDUSE EFFECTS ON STREAMWATER NUTRIENT DISTRIBUTION IN AN URBANIZING WATERSHED1

ABSTRACT: We investigated spatial and temporal relationships among surface and subsurface watershed attributes and stream nutrient concentrations in urbanizing Johnson Creek watershed in northern Oregon. We sampled stream water at eight urban and five nonurban locations from March 1998 through December 1999. We sampled eight wells distributed over the two primary aquifers in the watershed. Using a Geographic Information System (GIS), percentages of landuse attributes within a radius of 30, 91, and 152 m from each sample site were quantified. We analyzed relationships between (1) nutrient concentrations and percentage cover of different landuse attributes, and (2) nutrient concentrations and underlying hydrologic units. We did not find a significant relationship between ground water chemistry and stream water chemistry. We found elevated levels of phosphorus (P) concentrations correlated with urban landuse, while higher nitrogen (N) concentrations were correlated with nonurban (primarily agricultural) landuse. We concluded that elevated levels of N in nonurban areas of Johnson Creek watershed were associated with agricultural practices. We further concluded that urban development factors such as increases in storm drains, dry wells, and impermeable surfaces may be responsible for higher input of P to the stream in urbanizing areas of the Johnson Creek watershed.     

NUTRIENT LOAD CHARACTERIZATION FROM INTEGRATED SOURCE DATA FOR THE LOWER MISSISSIPPI RWER1

ABSTRACT: Nutrient data from all available sources for the lower Mississippi River were examined for potential differences among sampling agencies and geographic locations for the period between 1960 and 1998. Monthly means grouped by parameter, sampling location and agency, were calculated and compared as paired sets, excluding those months where data were not available for both sets. Some significant differences were found between various agencies collecting nutrient data on the river, as well as between various stretches of river, especially in the case of phosphorus nutrient data. Results were used to synthesize data sets from which a history of nutrient loading in the Mississippi River was determined. General trends in nitrate+nitrite, total Kjeldahl nitrogen, orthophosphate, total phosphorus and silica loads, as well as changes in nutrient proportions and the specific limiting nutrient (by month) are reported. This study provides a useful summary of contemporary and historical nutrient data that may assist in the evaluation of Mississippi River water quality and its potential effect on the Gulf of Mexico.     

A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove

The spread of invasive species is a long studied subject that garners much interest in the ecological research community. Historically the phenomenon has been approached using a purely deterministic mathematical framework (usually involving differential equations of some form). These methods, while scientifically meaningful, are generally highly simplified and fail to account for uncertainty in the data and process, of which our knowledge could not possibly exist without error. We propose a hierarchical Bayesian model for population spread that accommodates data sources with errors, dependence structures between population dynamics parameters, and takes into account prior scientific understanding via non-linear relationships between model parameters and space-time response variables. We model the process (i.e., the bird population in this case) as a Poisson response with spatially varying diffusion coefficients as well as a logistic population growth term using a common reaction-diffusion equation that realistically mimics the ecological process. We focus the application on the ongoing invasion of the Eurasian Collared-Dove.     

Effects of timber harvesting on pond-breeding amphibian persistence: testing the evacuation hypothesis.

Numerous studies have documented the decline of amphibians following timber harvest. However, direct evidence concerning the mechanisms of population decline is lacking and hinders attempts to develop conservation or recovery plans and solutions for forest species. We summarized the mechanisms by which abundance of amphibians may initially decline following timber harvest into three testable hypotheses: (1) mortality, (2) retreat, and (3) evacuation. Here, we tested the evacuation hypothesis within a large-scale, replicated experiment. We used drift fences with pitfall traps to capture pond-breeding amphibians moving out of experimental clearcut quadrants and into control quadrants at four replicate arrays located within the Daniel Boone Conservation Area on the upper Ozark Plateau in Warren County, Missouri, USA. During the preharvest year of 2004, only 51.6% of the 312 individuals captured were moving out of pre-clearcut quadrants, and movement did not differ from random. In contrast, during both postharvest years of 2005 and 2006, the number of captures along the quadrant edge increased, and a higher proportion of individuals (59.9% and 56.6%, respectively, by year) were moving out of clearcut quadrants than entering. Salamanders moved out of clearcuts in large percentages (Ambystoma annulatum, 78.2% in 2005, 78.2% in 2006; A. maculatum, 64.0% in 2005, 57.1% in 2006). Frogs and toads also moved out of clearcut quadrants, but in lower percentages (Bufo americanus, 59.6% in 2005, 53.3% in 2006; Rana clamitans, 52.7% in 2006). Salamanders moved out of clearcuts with low-wood treatments more than out of clearcuts with high-wood treatments. Movement of salamanders out of clearcuts was independent of sex. Estimated movement out of clearcuts represented between 8.7% and 35.0% of the total breeding adults captured for two species of salamanders. Although we recognize that some portion of the amphibian population may retreat underground for short periods and others may not survive the effects of timber harvest, these data are the first direct evidence showing that individuals are capable of leaving clearcuts and shifting habitat use.     

Quantitative approaches to the analysis of stable isotope food web data

Ecologists use stable isotopes (delta13C, delta15N) to better understand food webs and explore trophic interactions in ecosystems. Traditionally, delta13C vs. delta15N bi-plots have been used to describe food web structure for a single time period or ecosystem. Comparisons of food webs across time and space are increasing, but development of statistical approaches for testing hypotheses regarding food web change has lagged behind. Here we present statistical methodologies for quantitatively comparing stable isotope food web data. We demonstrate the utility of circular statistics and hypothesis tests for quantifying directional food web differences using two case studies: an arthropod salt marsh community across a habitat gradient and a freshwater fish community from Lake Tahoe, USA, over a 120-year time period. We calculated magnitude and mean angle of change (theta) for each species in food web space using mean delta13C and delta15N of each species as the x, y coordinates. In the coastal salt marsh, arthropod consumers exhibited a significant shift toward dependence on Spartina, progressing from a habitat invaded by Phragmites to a restored Spartina habitat. In Lake Tahoe, we found that all species from the freshwater fish community shifted in the same direction in food web space toward more pelagic-based production with the introduction of nonnative Mysis relicta and onset of cultural eutrophication. Using circular statistics to quantitatively analyze stable isotope food web data, we were able to gain significant insight into patterns and changes in food web structure that were not evident from qualitative comparisons. As more ecologists incorporate a food web perspective into ecosystem analysis, these statistical tools can provide a basis for quantifying directional food web differences from standard isotope data.     

Size and composition distributions of particulate matter emissions: part 1--light-duty gasoline vehicles

Size-resolved particulate matter (PM) emitted from light-duty gasoline vehicles (LDGVs) was characterized using filter-based samplers, cascade impactors, and scanning mobility particle size measurements in the summer 2002. Thirty LDGVs, with different engine and emissions control technologies (model years 1965-2003; odometer readings 1264-207,104 mi), were tested on a chassis dynamometer using the federal test procedure (FTP), the unified cycle (UC), and the correction cycle (CC). LDGV PM emissions were strongly correlated with vehicle age and emissions control technology. The oldest models had average ultrafine PM0.1 (0.056- to 0.1-microm aerodynamic diameter) and fine PM1.8 (< or =1.8-microm aerodynamic diameter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM0.1 and PM1.8 emissions of 51 microg/km and 371 microg/km, respectively. Light duty trucks and sport utility vehicles had PM0.1 and PM1.8 emissions nearly double the corresponding emission rates from passenger cars. Higher PM emissions were associated with cold starts and hard accelerations. The FTP driving cycle produced the lowest emissions, followed by the UC and the CC. PM mass distributions peaked between 0.1- and 0.18-microm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 microm. The majority of the PM was composed of carbonaceous material, with only trace amounts of water-soluble ions. Elemental carbon (EC) and organic matter (OM) had similar size distributions, but the EC/OM ratio in LDGV exhaust particles was a strong function of the adopted emissions control technology and of vehicle maintenance. Exhaust from LDGV classes with lower PM emissions generally had higher EC/OM ratios. LDGVs adopting newer technologies were characterized by the highest EC/OM ratios, whereas OM dominated PM emissions from older vehicles. Driving cycles with cold starts and hard accelerations produced higher EC/OM ratios in ultrafine particles.