Constrained additive ordination

For several decades now, ecologists have sought to determine the shape of species' response curves and how they are distributed along unknown underlying gradients, environmental latent variables, or ordination axes. Its determination has important implications for both continuum theory and community analysis because many theories and models in community ecology assume that responses are symmetric and unimodal. This article proposes a major new technique called constrained additive ordination (CAO) that solves this problem by computing the optimal gradients and flexible response curves. It allows ecologists to see the response curves as they really are, against the dominant gradients. With one gradient, CAO is a generalization of constrained quadratic ordination (CQO; formerly called canonical Gaussian ordination or CGO). It supplants symmetric bell-shaped response curves in CQO with completely flexible smooth curves. The curves are estimated using smoothers such as the smoothing spline. Loosely speaking, CAO models are generalized additive models (GAMs) fitted to a very small number of latent variables. Being data driven rather than model driven, CAO allows the data to "speak for itself" and does not make any of the assumptions made by canonical correspondence analysis. The new methodology is illustrated with a hunting spider data set and a New Zealand tree species data set.     

Hidden process models for animal population dynamics.

Hidden process models are a conceptually useful and practical way to simultaneously account for process variation in animal population dynamics and measurement errors in observations and estimates made on the population. Process variation, which can be both demographic and environmental, is modeled by linking a series of stochastic and deterministic subprocesses that characterize processes such as birth, survival, maturation, and movement. Observations of the population can be modeled as functions of true abundance with realistic probability distributions to describe observation or estimation error. Computer-intensive procedures, such as sequential Monte Carlo methods or Markov chain Monte Carlo, condition on the observed data to yield estimates of both the underlying true population abundances and the unknown population dynamics parameters. Formulation and fitting of a hidden process model are demonstrated for Sacramento River winter-run chinook salmon (Oncorhynchus tshawytsha).     

The functional organization of resin work in honeybee colonies

Resin is an important building material in the nests of honeybees, but little is known about how it is handled within the nest and how its collection is controlled. We studied the functional organization of resin work to better understand how a colony adaptively controls its intake of resin. Two hypotheses have been proposed for how resin collectors stay informed of the need for additional resin: (1) the unloading difficulty hypothesis (resin need is sensed indirectly by the unloading delay) and (2) the caulking activity hypothesis (resin need is sensed directly while engaged in using resin). A falsifiable prediction of the latter hypothesis, but not of the former, is that resin collectors not only gather resin outside the hive but also regularly handle resin inside the hive (taking it from other bees and using it to caulk crevices). Consistent with this prediction are our findings that in the resin sector of a colony’s economy, unlike in the pollen, nectar, and water sectors, there is no strict division of labor between the collectors and the users of a material. Over the course of a day, bees seen collecting resin were also commonly seen using resin. Moreover, we found that the unloading locations of resin collectors are unlike those of water and nectar collectors, being deep inside the hive (at the sites of resin use) rather than at the hive entrance. This arrangement facilitates the engagement in resin use by resin collectors. We conclude that the caulking activity hypothesis is well-supported, but that the unloading difficulty hypothesis also remains viable, for we found that resin collectors experience variable delays in getting rid of their loads, from less than 15 min to more than an hour, consistent with this hypothesis. The stage is now set for experimental tests of these two hypotheses. Both may be correct, which if true will imply that social insect workers, despite their small brains, can acquire and integrate information from multiple sources to improve their knowledge of conditions within the colony.     

The theoretical value of encounters with parasitized hosts for parasitoids

A female parasitoid searching for hosts in a patch experiences a diminishing encounter rate with unparasitized and thus suitable hosts. To use the available time most efficiently, it constantly has to decide whether to stay in the patch and continue to search for hosts or to search for and travel to another patch in the habitat. Several informational cues can be used to optimize the searching success. Theoretically, encounters with unparasitized hosts should lead to a prolonged search in a given patch if hosts are distributed contagiously. The results of empirical studies strongly support this hypothesis. However, it has, to date, not been investigated theoretically whether encounters with already parasitized hosts (which usually entail time costs) provide a parasitoid with valuable information for the optimization of its search in depletable patches, although the empirical studies concerning this question so far have produced ambiguous results. Building on recent advances in Bayesian foraging strategies, we approached this problem by modeling a priori searching strategies (which differ in the amount of information considered) and then testing them in computer simulations. By comparing the strategies, we were able to determine whether and how encounters with already parasitized hosts can yield information that can be used to enhance a parasitoid’s searching success.

Using multi-objective classification to model communities of soil microarthropods

In agricultural soil, a suite of anthropogenic events shape the ecosystem processes and populations. However, the impact from anthropogenic sources on the soil environment is almost exclusively assessed for chemicals, although other factors like crop and tillage practices have an important impact as well. Thus, the farming system as a whole should be evaluated and ranked according to its environmental benefits and impacts. Our starting point is a data set describing agricultural events and soil biological parameters. Using machine learning methods for inducing regression and model trees, we produce empirical models able to predict the soil quality from agricultural measures in terms of quantities describing the soil microarthropod community. We are also interested in discovering additional higher level knowledge. In particular, we have identified the most important factors influencing the population densities of springtails and mites and their biodiversity. We also identify to which agricultural actions different microarthropods react distinctly. To obtain this higher level knowledge, we employ multi-objective regression trees.     

Evidence for struvite in poultry litter: effect of storage and drying

The use of spectroscopic techniques (especially phosphorus-31 nuclear magnetic resonance [(31)P-NMR] and X-ray absorption near edge structure spectroscopy) has recently advanced the analysis of the speciation of P in poultry litter (PL) and greatly enhanced our understanding of changes in P pools in PL that receive alum (aluminum sulfate) to reduce water-soluble P and control ammonia emissions from poultry houses. Questions remain concerning changes of P species during long-term storage, drying, or after application of PL to cropland or for other uses, such as turfgrass. In this study, we investigated a set of six PL samples (of which three were alum-amended and three were unamended) that had been characterized previously. The P speciation was analyzed using solid-state (31)P-NMR spectroscopy, and the mineralogy was analyzed by powder X-ray diffraction (XRD) after storing the samples moist and dried for up to 5 yr under controlled conditions. The magnesium ammonium phosphate mineral struvite was identified in all but one PL samples. Struvite concentrations were generally lower in dried samples (< or = 14%) than in samples stored moist (23 and 26%). The moist samples also had higher concentrations of phosphate bound to aluminum hydroxides. Solid-state NMR spectroscopy was in general more sensitive than XRD in detecting and quantifying P species. Although phosphate associated with calcium and aluminum made up a large proportion of P species, they were not detected by XRD.     

Land management impacts on dairy-derived dissolved organic carbon in ground water

Dairy operations have the potential to elevate dissolved organic carbon (DOC) levels in ground water, where it may interact with organic and inorganic contaminants, fuel denitrification, and may present problems for drinking water treatment. Total and percent bioavailable DOC and total and carbon-specific trihalomethane (THM) formation potential (TTHMFP and STHMFP, respectively) were determined for shallow ground water samples from beneath a dairy farm in the San Joaquin Valley, California. Sixteen wells influenced by specific land management areas were sampled over 3 yr. Measured DOC concentrations were significantly elevated over the background as measured at an upgradient monitoring well, ranging from 13 to 55 mg L(-1) in wells downgradient from wastewater ponds, 8 to 30 mg L(-1) in corral wells, 5 to 12 mg L(-1) in tile drains, and 4 to 15 mg L(-1) in wells associated with manured fields. These DOC concentrations were at the upper range or greatly exceeded concentrations in most surface water bodies used as drinking water sources in California. DOC concentrations in individual wells varied by up to a factor of two over the duration of this study, indicating a dynamic system of sources and degradation. DOC bioavailability over 21 d ranged from 3 to 10%, comparable to surface water systems and demonstrating the potential for dairy-derived DOC to influence dissolved oxygen concentrations (nearly all wells were hypoxic to anoxic) and denitrification. TTHMFP measurements across all management units ranged from 141 to 1731 microg L(-1), well in excess of the maximum contaminant level of 80 microg L(-1) established by the Environmental Protection Agency. STHMFP measurements demonstrated over twofold variation ( approximately 4 to approximately 8 mmol total THM/mol DOC) across the management areas, indicating the dependence of reactivity on DOC composition. The results indicate that land management strongly controls the quantity and quality of DOC to reach shallow ground water and hence should be considered when managing ground water resources and in any efforts to mitigate contamination of ground water with carbon-based contaminants, such as pesticides and pharmaceuticals.     

Impacts of Climate Variability and Land Use Alterations on Frequency Distributions of Terrestrial Runoff Loading to Coastal Waters in Southern California1

Abstract: The transport of water, sediment, dissolved and particulate chemicals, and bacteria from coastal watersheds affects the nearshore marine and estuarine waters. In southern California, coastal watersheds deliver water and associated constituents to the nearshore system in discrete pulses. To better understand the pulsed nature of these watersheds, frequency distributions of simulated runoff events are presented for: (1) three land use conditions (1929, 1998, 2050); (2) three time periods (all water years 1989‐2002), only El Nino years (1992, 1993, 1995, 1998); and only non‐El Nino years; and (3) three regions (watershed, uplands, and lowlands). At the watershed scale, there was a significant increase (>200%) in mean event runoff from 1929 to 2050 (0.4‐1.3 cm) due to localized urbanization, which shifted the dominant sources of runoff from the mountains in 1929 (78% of watershed runoff) to the coastal plane for 2050 conditions (51% of watershed runoff). Inter‐annual climate variability was strong in the rainfall and runoff frequency distributions, with mean event rainfall and runoff 66 and 60% larger in El Nino relative to non‐El Nino years. Combining urbanization and climate variability, 2050 land conditions resulted in El Nino years being five times more likely to produce large (>3.0 cm) runoff events relative to non‐El Nino years. Combining frequency distributions of event runoff with regional nutrient export relationships, we show that in El Nino years, one in five events produced runoff ≥2.5 cm and temporary nearshore nitrate and phosphate concentrations of 12 and 1.4 μM, respectively, or approximately 5‐10 times above ambient conditions.     

Spatial Distribution of Water Supply in the Coterminous United States1

Abstract: Available water supply across the contiguous 48 states was estimated as precipitation minus evapotranspiration using data for the period 1953‐1994. Precipitation estimates were taken from the Parameter‐Elevation Regressions on Independent Slopes Model (PRISM). Evapotranspiration was estimated using two models, the Advection‐Aridity model and the Zhang model. The evapotranspiration models were calibrated using precipitation and runoff data for 655 hydrologically undisturbed basins, and then tested using estimates of natural runoff for the 18 water resource regions (WRR) of the 48 contiguous states. The final water supply coverage reflects a mixture of outputs from the two evapotranspiration models. Political, administrative, and land cover boundaries were mapped over the coverage of mean annual water supply. Across the entire study area, we find that 53% of the water supply originates on forested land, which covers only 29% of the surface area, and that 24% originates on federal lands, including 18% on national forests and grasslands alone. Forests and federal lands are even more important in the West (the 11 western contiguous states), where 65% of the water supply originates on forested land and 66% on federal lands, with national forests and grasslands contributing 51%.