Dr. Walter K. Dodds Division of Biology Kansas State University Manhattan, KS 66506 785 532 6998 wkdodds@ksu.edu
Dr. Margaret A. Palmer Chesapeake Biological Lab University of Maryland Center for Environmental Science Solomons, MD 20688 410 326 7241 mpalmer@umd.edu
Dr Bradley J. Cardinale Dept of Ecology, Evolution & Marine Biology University of California - Santa Barbara Santa Barbara, CA 93106 805 893 4157 cardinale@lifesci.ucsb.edu
Human activities have greatly altered freshwater ecosystems, including depletion and degradation of freshwater supplies, increased nutrient loads, and diminished biodiversity. We know little of how these changes will individually and collectively influence the resistance and resilience of ecosystems in light of climate change. Accordingly, we propose a long-term, continent-wide observational network to detail the mechanisms by which aquatic ecosystems resist and recover from three of the most pervasive forms of human-induced disturbance. This information is central to accurate ecological forecasting. We will focus on streams, rivers, and wetlands, hereafter collectively referred to as streams. Streams are disproportionately important for biodiversity, ecosystem services, and economic, recreational and aesthetic values. Our overarching question is: how will chronic nutrient inputs (nitrogen or phosphorus), higher probabilities of extreme events (droughts and floods), and simplification of food webs (loss of consumers) impact the resistance and resilience of stream ecosystem function (stream-wide respiration, production, and nutrient retention)? We define resistance and resilience as the proportional change in ecosystem functions following a disturbance and the return interval, respectively. There is strong justification for linking the ecosystem drivers that are the subject of this proposal. Streams and other running waters are ideal ecosystems for the proposed network because they (i) have well delimited inputs and outputs, and thus allow quantification of the resistance and resilience of the focal ecosystem-level processes, (ii) are dynamic systems that respond to disturbances over periods of weeks to months - time scales amenable to observation and experimentation, (iii) can be studied with comparable methods spanning the entire continent, (iv) are important sites of nutrient retention and (v) integrate watershed processes that occur on the same scales as those investigated by NEON network sensor platforms. Many of these attributes are unique and allow some types of cross continental observations that are simply not feasible with other ecosystems.
We propose 30 observational sites distributed across the continent to capture variation in hydrology, temperature, nutrient loading, elevation, and biogeographical context. Each observational site will require two aquatic sensor packages to enable study of the effects of in-stream ecosystem processes on water in transit through the study reach. We will also require additional measurements not in the ISEP including total N and total P, decomposition rates, nutrient limitation assays, dissolved gas analyses, and food web analyses using natural abundance of stable isotopes. These additional measurements are required to adequately characterize aquatic community structure and ecosystem function.
This ecological observatory network will complement emerging networks related to water bodies that focus on physical and chemical properties (i.e., EPA-WATERS), and existing networks of long-term ecological studies that have used a variety of methods and site selection protocols (i.e., LTER, USGS hydrologic benchmark stations).
This is one of two linked responses to the NEON RFI’s for observational and experimental continental networks of stream research. Some sections of these two responses are very similar (Scientific Challenge, table of measurements) and others are different given the different requirements of the two RFI’s (e.g. site information, education and outreach, experimental design). The observational network will rigorously assess major drivers influencing streams and wetlands and how they link to other habitats. The experimental network strengthens the inference for a relatively low added cost.