Toward canonical trophic aggregations

The attractiveness of the trophic concept is that it was the first attempt at a holistic perspective on an ecosystem which met with any degree of success. Just as temperature, pressure, and volume allow one to characterize the incomprehensible multitude of particulate motions in a simple gas, the hope is that a small set of figures, such as trophic storages or trophic efficiencies, permit one to compare two ecosystems with overwhelmingly disparate complexities. Thus, if it were possible to demonstrate that an arbitrary network of ecosystem flows could be reduced to a trophic configuration, the aggregation process thus defined would become a key component of the evolving discipline of "macroscopic ecology" (see also Odum 1977 and Ulanowicz 1979).

Validation of a semi-Lagrangian, canonical regression model of climates in the southwestern United States

EXTRACT (SEE PDF FOR FULL ABSTRACT): A local climate model (LCM) has been developed to simulate the modern and 18 ka climate of the southwestern United States. ... LCM solutions indicate summers were about 1°C cooler and winters 11°C cooler at 18 ka. Annual PREC increased 68% at 18 ka, with large increases in spring and fall PREC and diminished summer monsoonal PREC. ... Validation of simulations of 18 ka climate indicate general agreement with proxy estimates of climate for that time. However, the LCM estimates of summer temperatures are about 5 to 10°C higher than estimates from proxy reconstructions.

Zonation of submerged vegetation in Lake Kariba, Zimbabwe and its ecological interpretation

The submerged vegetation of Lake Kariba is described in relation to degree of slope (lake morphometry), depth and light transparency. The direct gradient analysis technique - canonical correspondence analysis and the TWINSPAN classification programs were used to analyse the data set. The western end of the lake with low transparency has a low species diversity (with Vallisneria aethiopica dominating). Species diversity increases with increased transparency in the other parts of the lake. The classification revealed monospecific communities for all species as well as mixed communities with Lagarosiphon as the associate species with the broadest distribution. The ordination revealed a first axis strongly related to the depth and transparency gradients and the second axis related to slope.

Importance of shoreface sand ridges as habitat for fishes off the northeast coast of the United States

To determine if shoreface sand ridges provide unique habitats for fish on the inner continental shelf, two cross-shelf trawl surveys (23 km in length) were conducted in southern New Jersey (July and September 1991−95 with a beam trawl and July and September 1997−06 with an otter trawl) to assess whether species abundance, richness, and assemblages differed on and away from the ridge. The dominant species collected with both gears were from the families Paralichthyidae, Triglidae, Gobiidae, Serranidae, Engraulidae, Stromateidae, and Sciaenidae. Overall abundance (n=41,451 individuals) and species richness (n=61 species) were distributed bimodally across the nearshore to offshore transect, and the highest values were found on either side of the sand ridge regardless of gear type. Canonical correspondence analysis revealed three species assemblages: inshore (<5 meters depth), near-ridge (9−14 meters depth), and offshore (>14 meters depth), and variation in species composition between gear types. Environmental factors that corresponded with the assemblage changes included depth, temperature, distance from the top of the ridge, and habitat complexity. The most abundant near-ridge assemblages were distinct and included economically important species. Sand ridges of the inner continental shelf appear to be important habitat for a number of fish species and therefore may not be a suitable area for sand and gravel mining.

Toward identification of larval sailfish (Istiophorus platypterus), white marlin (Tetrapturus albidus), and blue marlin (Makaira nigricans) in the western North Atlantic Ocean*

The identification of larval istiophorid billfishes from the western North Atlantic Ocean has long been problematic. In the present study, a molecular technique was used to positively identify 27 larval white marlin (Tetrapturus albidus), 96 larval blue marlin (Makaira nigricans), and 591 larval sailfish (Istiophorus platypterus) from the Straits of Florida and the Bahamas. Nine morphometric measurements were taken for a subset of larvae (species known), and lower jaw pigment patterns were recorded on a grid. Canonical variates analysis (CVA) was used to reveal the extent to which the combination of morphometric, pigment pattern, and month of capture information was diagnostic to species level. Linear regression revealed species-specific relationships between the ratio of snout length to eye orbit diameter and standard length (SL). Confidence limits about these relationships served as defining characters for sailfish >10 mm SL and for blue and white marlin >17 mm SL. Pigment pattern analysis indicated that 40% of the preflexion blue marlin examined possessed a characteristic lower jaw pigment pattern and that 62% of sailfish larvae were identifiable by lower jaw pigments alone. An identification key was constructed based on pigment patterns, month of capture, and relationships between SL and the ratio of snout length to eye orbit diameter. The key yielded identifications for 69.4% of 304 (blind sample) larvae used to test it; only one of these identifications was incorrect. Of the 93 larvae that could not be identified by the key, 71 (76.3%) were correctly identified with CVA. Although identif ication of certain larval specimens may always require molecular techniques, it is encouraging that the majority (92.4%) of istiophorid larvae examined were ultimately identifiable from external characteristics alone.

A stochastic model of temporal variations in monthly temperature, precipitation, snowfall, and resulting snowpack

We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.