High-resolution natural recording systems: intercomparisons of the response to interannual climatic variability [abstract]

The goal of this work is to examine the properties of recording mechanisms which are common to continuously recording high-resolution natural systems in which climatic signals are imprinted and preserved as proxy records. These systems produce seasonal structures as an indirect response to climatic variability over the annual cycle. We compare the proxy records from four different high-resolution systems: the Quelccaya ice cap of the Peruvian Andes; composite tree ring growth from southern California and the southwestern United States; and the marine varve sedimentation systems in the Santa Barbara basin (off California, United States) and in the Gulf of California, Mexico. An important focus of this work is to indicate how the interannual climatic signal is recorded in a variety of different natural systems with vastly different recording mechanisms and widely separated in space. These high-resolution records are the products of natural processes which should be comparable, to some degree, to human-engineered systems developed to transmit and record physical quantities. We therefore present a simple analogy of a data recording system as a heuristic model to provide some unifying concepts with which we may better understand the formation of the records. This analogy assumes special significance when we consider that natural proxy records are the principal means to extend our knowledge of climatic variability into the past, beyond the limits of instrumentally recorded data.

Periodic autoregressive moving average models for the analysis of streamflow [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Streamflow values show definite seasonal patterns in their month-to-month correlation structure. The structure also seems to vary as a function of the type of stream (coastal versus mountain or humid versus arid region). The standard autoregressive moving average (ARMA) time series model is incapable of reproducing this correlation structure. ... A periodic ARMA time series model is one in which an ARMA model is fitted to each month or season but the parameters of the model are constrained to be periodic according to a Fourier series. This constraint greatly reduces the number of parameters but still leaves the flexibility for matching the seasonally varying correlograms.

Integration of data for nowcasting of harmful algal blooms

Harmful algal blooms (HABs) are a significant and potentially expanding problem around the world. Resource management and public health protection require sufficient information to reduce the impacts of HABs by response strategies and through warnings and advisories. To be effective, these programs can best be served by an integration of improved detection methods with both evolving monitoring systems and new communications capabilities. Data sets are typically collected from a variety of sources, these can be considered as several types: point data, such as water samples; transects, such as from shipboard continuous sampling; and synoptic, such as from satellite imagery. Generation of a field of the HAB distribution requires all of these sampling approaches. This means that the data sets need to be interpreted and analyzed with each other to create the field or distribution of the HAB. The HAB field is also a necessary input into models that forecast blooms. Several systems have developed strategies that demonstrate these approaches. These range from data sets collected at key sites, such as swimming beaches, to automated collection systems, to integration of interpreted satellite data. Improved data collection, particularly in speed and cost, will be one of the advances of the next few years. Methods to improve creation of the HAB field from the variety of data types will be necessary for routine nowcasting and forecasting of HABs.

Pinniped diet composition: a comparison of estimation models

Along the west coast of the United States, the potential impact of increasing pinniped populations on declining salmonid (Oncorhynchus spp.) stocks has become an issue of concern. Fisheries managers need species-specific estimates of consumption by pinnipeds to evaluate their impact on salmonid stocks. To estimate consumption, we developed a model that estimates diet composition by reconstructing prey biomass from fecal samples. We applied the model to data collected from harbor seals (Phoca vitulina) that are present year-round in the lower Columbia River where endangered stocks of salmonids pass as returning adults and as seaward-migrating smolts. Using the same data, we applied the split-sample frequency of occurrence model, which avoids reconstructing biomass by assuming that each fecal sample represents an equal volume of consumption and that within each sample each prey item represents an equal proportion of the volume. The two models for estimating diet composition yielded size-specific differences in consumption estimates that were as large as tenfold for the smallest and largest prey. Conclusions about the impact of harbor seal predation on adult salmonids, some of their largest prey species, remain uncertain without some appropriate rationale or further information (e.g. empirical captive studies) to discriminate between these models.

Toward a rule-based biome model

EXTRACT (SEE PDF FOR FULL ABSTRACT): Current projections of the response of the biosphere to global climatic change indicate as much as 50 to 90% spatial displacement of extratropical biomes. The mechanism of spatial shift could be dominated either by competitive displacement of northern biomes by southern biomes or by drought-induced dieback of areas susceptible to change. The current suite of global biosphere models cannot distinguish between these two processes, hence the need for a mechanistically based biome model. The first steps have been taken toward development of a rule-based, mechanistic model of regional biomes at a continental scale. ... The model is in an early stage of development and will require several enhancements, including: explicit simulation of potential evapotranspiration, extension to boreal and tropical biomes, a shift from steady-state to transient dynamics, and validation on other continents.

Terrestrial ecosystem response to interdecadal climate variability in the western United States [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): We argue that the most important climatically-driven terrestrial ecosystem changes are concentrated in annual- to decadal-scale episodic events. These rapid ecosystem responses to climate change are manifested as regionally synchronized disturbance events (eg, floods, fires, and insect outbreaks) and increased drought-caused plant mortality rates.

Geographic patterns in the lag of temperature response to insolation for El Niño vs. La Niña conditions [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): The most important control on the annual cycle of temperature is insolation, with secondary influences from terms related to moisture, yet direct statistical analysis of the moisture-driven modulations (such as El Niño) of the response of temperature to insolation are not available. We have examined one aspect of the relationship between insolation and the instrumental record of maximum daily temperature - the lag between the two - at 252 stations in the western United States.

River salinity variations in response to discharge: examples from the western United States during the early 1900s

Major controls on river salinity (total dissolved solids) in the western United States are climate, geology, and human activity. Climate, in general, influences soil-river salinity via salt-balance variations. When climate becomes wetter, river discharge increases and soil-river salinity decreases; when climate becomes drier river discharge decreases and soil-river salinity increases. This study characterizes the river salinity response to discharge using statistical-dynamic methods. An exploratory analysis of river salinity, using early 1900s water quality surveys in the western United States, shows much river salinity variability is in response to storm and annual discharge. Presumably this is because river discharge is largely supported by surface flow.