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L.L. Pierce

Publications and source records attributed to L.L. Pierce.

3 recordsLinked to original sources

The effect of predation on stunted and nonstunted white perch

Predation is widely regarded as a means to prevent or minimise the establishment of a stunted (high density of slow growing individuals) population. We investigated the effect of predation on two different white perch Morone americana populations (stunted and nonstunted) by examining the stomach contents of piscivorous fishes. White perch and gizzard shad dominated piscivore diets in Branched Oak Lake, whereas white perch dominated piscivore diets in Pawnee Lake. White perch consumed in the stunted population (Branched Oak Lake) were larger and older than white perch consumed in the nonstunted population (Pawnee Lake). Many of the consumed white perch in the stunted population were sexually mature and had the opportunity to spawn at least once. In contrast, all of the consumed white perch in the nonstunted population were sexually immature. Predation may have reinforced the stunting of white perch in Branched Oak Lake through removal of the largest, oldest individuals. ?? 2010 John Wiley & Sons A/S.

Ecology of Freshwater Fish↗

Modeled responses of terrestrial ecosystems to elevated atmospheric CO2: A comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP)

Although there is a great deal of information concerning responses to increases in atmospheric CO 2 at the tissue and plant levels, there are substantially fewer studies that have investigated ecosystem-level responses in the context of integrated carbon, water, and nutrient cycles. Because our understanding of ecosystem responses to elevated CO 2 is incomplete, modeling is a tool that can be used to investigate the role of plant and soil interactions in the response of terrestrial ecosystems to elevated CO 2 . In this study, we analyze the responses of net primary production (NPP) to doubled CO 2 from 355 to 710 ppmv among three biogeochemistry models in the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): BIOME-BGC (BioGeochemical Cycles), Century, and the Terrestrial Ecosystem Model (TEM). For the conterminous United States, doubled atmospheric CO 2 causes NPP to increase by 5% in Century, 8% in TEM, and 11% in BIOME-BGC. Multiple regression analyses between the NPP response to doubled CO 2 and the mean annual temperature and annual precipitation of biomes or grid cells indicate that there are negative relationships between precipitation and the response of NPP to doubled CO 2 for all three models. In contrast, there are different relationships between temperature and the response of NPP to doubled CO 2 for the three models: there is a negative relationship in the responses of BIOME-BGC, no relationship in the responses of Century, and a positive relationship in the responses of TEM. In BIOME-BGC, the NPP response to doubled CO 2 is controlled by the change in transpiration associated with reduced leaf conductance to water vapor. This change affects soil water, then leaf area development and, finally, NPP. In Century, the response of NPP to doubled CO 2 is controlled by changes in decomposition rates associated with increased soil moisture that results from reduced evapotranspiration. This change affects nitrogen availability for plants, which influences NPP. In TEM, the NPP response to doubled CO 2 is controlled by increased carboxylation which is modified by canopy conductance and the degree to which nitrogen constraints cause down-regulation of photosynthesis. The implementation of these different mechanisms has consequences for the spatial pattern of NPP responses, and represents, in part, conceptual uncertainty about controls over NPP responses. Progress in reducing these uncertainties requires research focused at the ecosystem level to understand how interactions between the carbon, nitrogen, and water cycles influence the response of NPP to elevated atmospheric CO 2 .

Oecologia↗

A vegetation classification logic-based on remote-sensing for use in global biogeochemical models

A simple new classification logic for global vegetation is proposed. The critical features of this classification are that: it is based on simple, observable, unambiguous character- istics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation; the structural characteristics can be determined by remote sensing, so that repeatable and efficient global re-classifications of existing vegetation will be possible; and the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km Normalized Difference Vegetation Index database. Currently recognized global biome classes can easily be derived from this classification by adding climate descriptors and defining mixtures of these fundamental six vegetation classes.

Ambio↗