Examination of model predictions at different horizontal grid resolutions

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs and data requirements increase significantly with increasing grid resolution. Therefore, it is important to examine, for any given application, whether the expected benefit of increased grid resolution justifies the extra costs. In this study, we examine temperature and ozone observations and model predictions for three high ozone episodes that occurred over the northeastern United States during the summer of 1995. In the first set of simulations, the meteorological model RAMS4a was run with three two-way nested grids of 108/36/12 km grid spacing covering the United States and the photochemical model UAM-V was run with two grids of 36/12 km grid spacing covering the eastern United States. In the second set of simulations, RAMS4a was run with four two-way nested grids of 108/36/12/4 km grid spacing and UAM-V was run with three grids of 36/12/4 km grid spacing with the finest resolution covering the northeastern United States. Our analysis focuses on the comparison of model predictions for the finest grid domain of the simulations, namely, the region overlapping the 12 km and 4 km domains. A comparison of 12 km versus 4 km fields shows that the increased grid resolution leads to finer texture in the model predictions; however, comparisons of model predictions with observations do not reveal the expected improvement in the predictions. While high-resolution modeling has scientific merit and potential uses, the currently available monitoring networks, in conjunction with the scarceness of highly resolved spatial input data and the limitations of model formulation, do not allow confirmation of the expected superiority of the high-resolution model predictions.The U.S. Governments right to retain a non-exclusive royalty-free licence in and to any copyright is acknowledged.     

The perturbation of historical pollution records in aquatic sediments

It is often claimed that coastal marine and freshwater lake sediments preserve temporal records of anthropogenic input of heavy metals to the environment since the onset of the Industrial Revolution. Growing evidence of perturbatory factors such as physical and biological mixing, other redistributional processes and the early post-depositional diagenetic release and mobility of some elements is reviewed. Fundamental requirements of future studies are outlined.     

Planktivorous damselfish support significant nitrogen and phosphorus fluxes to Mediterranean reefs

In an ecosystem, which is apparently very limited in N and P, the planktivorous damselfish Chromis chromis acts as an important vector in transferring nutrients from the pelagic into littoral food webs. C. chromis are more efficient at absorbing nutrients from their diet than herbivorous Pomacentridae, and excrete more faeces in the spring when their plankton food is more abundant. Faeces released in the water column sink rapidly to the substratum and are consumed by herbivorous and omnivorous fish. Faeces released into night-shelters are rapidly consumed by invertebrate detritivores, and particularly mobile scavengers, such as shrimps and hermit crabs. Night-time accrual of Chromis faeces represents a very important flux of N and P. Such fluxes are predictable in time and space and have thus far been ignored in studies of the western Mediterranean.     

Elk decision-making rules are simplified in the presence of wolves

The risk of predation drives many behavioral responses in prey. However, few studies have directly tested whether predation risk alters the way other variables influence prey behavior. Here we use information theory (Akaike’s Information Criterion, AICc) in a novel way to test the hypothesis that the decision-making rules governing elk behavior are simplified by the presence of wolves. With elk habitat use as the dependent variable, we test whether the number of independent variables (i.e., the size of the models) that best predict this behavior differ when wolves are present vs absent. Thus, we use AICc scores simply to determine the number of variables to which elk respond when making decisions. We measured habitat use using 2,288 locations from GPS collars on 14 elk, over two winters (14 elk winters), in the Gallatin Canyon portion of the Greater Yellowstone Ecosystem. We found that the use of three major habitat components (grass, conifer, sage) was sensitive to many variables on days that wolves were locally absent, with the best models (ΔAICc≤2) averaging 7.4 parameters. In contrast, habitat use was sensitive to few variables on days when wolves were present: the best models averaged only 2.5 parameters. Because fewer variables affect elk behavior in the presence of wolves, we conclude that elk use simpler decision-making rules in the presence of wolves. This simplification of decision-making rules implies that predation risk imposes selection pressures that do not allow prey to respond to other pressures in ways that they otherwise would. If the affected processes are important, then this indirect effect of predation is likely to be important.     

Urbanization affects stream ecosystem function by altering hydrology, chemistry, and biotic richness.

Catchment urbanization can alter physical, chemical, and biological attributes of stream ecosystems. In particular, changes in land use may affect the dynamics of organic matter decomposition, a measure of ecosystem function. We examined leaf-litter decomposition in 18 tributaries of the St. Johns River, Florida, USA. Land use in all 18 catchments ranged from 0% to 93% urban which translated to 0% to 66% total impervious area (TIA). Using a litter-bag technique, we measured mass loss, fungal biomass, and macroinvertebrate biomass for two leaf species (red maple [Acer rubrum] and sweetgum [Liquidambar styraciflua]). Rates of litter mass loss, which ranged from 0.01 to 0.05 per day for red maple and 0.006 to 0.018 per day for sweetgum, increased with impervious catchment area to levels of approximately 30-40% TIA and then decreased as impervious catchment area exceeded 40% TIA. Fungal biomass was also highest in streams draining catchments with intermediate levels of TIA. Macroinvertebrate biomass ranged from 17 to 354 mg/bag for red maple and from 15 to 399 mg/bag for sweetgum. Snail biomass and snail and total invertebrate richness were strongly related to breakdown rates among streams regardless of leaf species. Land-use and physical, chemical, and biological variables were highly intercorrelated. Principal-components analysis was therefore used to reduce the variables into several orthogonal axes. Using stepwise regression, we found that flow regime, snail biomass, snail and total invertebrate richness, and metal and nutrient content (which varied in a nonlinear manner with impervious surface area) were likely factors affecting litter breakdown rates in these streams.     

Non-renewable resource prices: Deterministic or stochastic trends?

In this paper, we examine temporal properties of 11 natural resource real price series from 1870 to 1990. Recent studies by Ahrens and Sharma [Trends in natural resource commodity prices: deterministic or stochastic? J. Environ. Econom. Manage. 33(1997)59–74], Berck and Roberts [Natural resource prices: will they ever turn up? J. Environ. Econom. Manage. 31(1996)65–78], and Slade [Grade selection under uncertainty: least cost last and other anomalies, J. Environ. Econom. Manage. 15(1988)189–205], among others, find that many non-renewable resource prices have a stochastic trend. We revisit this issue by employing a Lagrangian multiplier unit root test that allows for two endogenously determined structural breaks with and without a quadratic trend. Contrary to previous research, we find evidence against the unit root hypothesis for all price series. Our findings support characterizing natural resource prices as stationary around deterministic trends with structural breaks. We additionally show that both pre-testing for unit roots with breaks and allowing for breaks in the forecast model can improve forecast accuracy. Overall, the results in this paper are important in both a positive and normative sense; without an appropriate understanding of the dynamics of a time series, empirical verification of theories, forecasting, and proper inference are potentially fruitless.     

Localization of infaunal prey by the sea star<Emphasis Type="Italic"> Leptasterias polaris</Emphasis>

We performed field and laboratory studies to investigate how large adult Leptasterias polaris detect and locate their major prey, large infaunal bivalves, in the sediment bottom community. A field survey using SCUBA diving showed that 95% of the locations where L. polaris dug into the sediment bottom were over bivalves and this success rate was much greater than if digging was done at random (22%). Furthermore, when sea stars were provided with a low density of randomly distributed prey in a laboratory arena, they dug exclusively in locations where a clam had been buried. These observations indicated that L. polaris locates infaunal prey prior to investing energy into digging. Studies in a laboratory flow tank showed that L. polaris readily detected and moved towards its preferred prey Ensis directus whereas its responses to less preferred prey Mya truncata and Spisula polynyma were much weaker. The degree to which it oriented towards these three common prey seemed to reflect potential energy intake relative to foraging costs (which likely increase with the depth of the different prey) and risks from interactions with other carnivores (which are greatest when feeding on large prey). This is the first study to clearly demonstrate that sea stars use prey odours to locate infaunal prey.Electronic Supplementary Material Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s00227-004-1497-1Communicated by R.J. Thompson, St. Johns     

Effects of Social Structure and Prey Dynamics on Extinction Risk in Gray Wolves

Extinction models based on diffusion theory generally fail to incorporate two important aspects of population biology—social structure and prey dynamics. We include these aspects in an individual-based extinction model for small, isolated populations of the gray wolf (Canis lupus). Our model predicts mean times to extinction significantly longer than those predicted by more general (diffusion) models. According to our model, an isolated population of 50 wolves has a 95% chance of surviving just 9 years and only a 30% chance of surviving beyond 100 years. Reflecting the influence of social structure, a wolf population initially comprising 50 individuals is expected to persist only a few years longer, on average (71 years), than is a population initially comprising just a single reproductive pair (62 years). In contrast, substantially greater average prey abundance leads to dramatically longer expected persistence times. Autocorrelated prey dynamics result in a more complex distribution of extinction times than predicted by many extinction models. We contend that demographic stochasticity may pose the greatest threat to small, isolated wolf populations, although environmental stochasticity and genetic effects may compound this threat. Our work highlights the importance of considering social structure and resource dynamics in the development of population viability analyses.