Final report : verification of bay productivity measurement by remote sensors

From University of Texas at Austin Marine Science Institute to Texas Water Development BoardInteragency cooperative contract TWDB contract no. IA03-483-003July 2004Ecosystem function in estuarine environments is known to be an important indicator of ecosystem health and productivity. There is a need to quantify estuarine ecosystem function variability and link to freshwater inflow to enable better management of ecosystem health and productivity. An important and quantifiable component of ecosystem function is ecosystem metabolism. Results indicate that open water methods were more appropriate than light-dark bottle methods for measuring net ecosystem metabolism in shallow water estuarine ecosystems because of the large contribution of benthos, which is ignored in water bottles. Spatial and temporal variability in net ecosystem metabolism was found. Spatial variability was attributed to differences in benthic habitats and/or station locations with respect to freshwater inflow point sources. Temporal variability in net ecosystem metabolism may be driven by differences in seasonal temperatures and freshwater inflow differences on seasonal time scales. Net ecosystem metabolism was directly related to amounts of freshwater inflow. The strength of this relationship depended on proximity to freshwater sources. Future studies of whole ecosystem metabolism in shallow estuarine ecosystems should employ open water methods and should strive to link other dynamic environmental conditions, such as temperature or irradiance, to ecosystem health, function, and productivity.Marine Scienc

Biodiversity and ecosystem function in soil

1. Soils are one of the last great frontiers for biodiversity research and are home to an extraordinary range of microbial and animal groups. Biological activities in soils drive many of the key ecosystem processes that govern the global system, especially in the cycling of elements such as carbon, nitrogen and phosphorus. 2. We cannot currently make firm statements about the scale of biodiversity in soils, or about the roles played by soil organisms in the transformations of organic materials that underlie those cycles. The recent UK Soil Biodiversity Programme (SBP) has brought a unique concentration of researchers to bear on a single soil in Scotland, and has generated a large amount of data concerning biodiversity, carbon flux and resilience in the soil ecosystem. 3. One of the key discoveries of the SBP was the extreme diversity of small organisms: researchers in the programme identified over 100 species of bacteria, 350 protozoa, 140 nematodes and 24 distinct types of arbuscular mycorrhizal fungi. Statistical analysis of these results suggests a much greater 'hidden diversity'. In contrast, there was no unusual richness in other organisms, such as higher fungi, mites, collembola and annelids. 4. Stable-isotope (C-13) technology was used to measure carbon fluxes and map the path of carbon through the food web. A novel finding was the rapidity with which carbon moves through the soil biota, revealing an extraordinarily dynamic soil ecosystem. 5. The combination of taxonomic diversity and rapid carbon flux makes the soil ecosystem highly resistant to perturbation through either changing soil structure or removing selected groups of organisms

Impacts of farming practice within organic farming systems on below-ground ecology and ecosystem function

Maintaining ecosystem function is a key issue for sustainable farming systems which contribute broadly to global ecosystem health. A focus simply on the diversity of belowground organisms is not sufficient and there is a need to consider the contribution of below-ground biological processes to the maintenance and enhancement of soil function and ecosystem services. A critical literature review on the impacts of land management practices on below-ground ecology and function shows that farm management practices can have a major impact. A particular challenge for organic farming systems is to explore to what extent reduced tillage can be adopted to the benefit of below-ground ecology without critically upsetting the whole farm management balance

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Microbes as engines of ecosystem function : When does community structure enhance predictions of ecosystem processes?

FUNDING This work was supported by NSF grant DEB-1221215 to DN, as well as grants supporting the generation of our datasets as acknowledged in their original publications and in Supplementary Table S1. ACKNOWLEDGMENT We thank the USGS Powell Center ‘Next Generation Microbes’ working group, anonymous reviews, Brett Melbourne, and Alan Townsend for valuable feedback on this project.Peer reviewedPublisher PD

Optimal ecosystem management with structural dynamics

We address the problem of optimal management of a self organizing ecosystem along ecological succession. A dynamic carrying capacity is interpreted as depicting the dynamics of habitat creation and occupation along ecological succession. The ecosystem may have three growth modes: pure compensation (concave ecosystem regeneration function), depensation (convex-concave regeneration function) and critical depensation (additionally having negative growth rates for low biomass). We analyse the optimal policies for the management of the ecosystem for the three growth modes. Accordingly, we prove the existence of a Skiba points for certain types of ecosystems. Further, we compare usual golden rule paths with the derived optimal policies near the Skiba points.Ecosystem management; habitat creation; optimal policies; Skiba point

Eco-Defense against Invasions

Characterizing patterns of invasion across space, time, and taxonomic group will help reveal how invasive species affect ecosystem function and individual native specie

An exactly solvable coarse-grained model for species diversity

We present novel analytical results about ecosystem species diversity that stem from a proposed coarse grained neutral model based on birth-death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results of ecological neutral theory and empirical evidence on species diversity preservation. Neutral model of biodiversity deals with ecosystems in the same trophic level where per-capita vital rates are assumed to be species-independent. Close-form analytical solutions for neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain: the probability distribution function of the number of species in the ecosystem both in transient and stationary states; the n-points connected time correlation function; and the survival probability, definned as the distribution of time-spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from a estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications on biodiversity and conservation biology.Comment: 20 pages, 4 figures. To appear in Journal of Statistichal Mechanic