Cooperative Ecosystem Studies Unit, Rocky Mountain CESU | G17AS00049

Opportunity Information: Apply for G17AS00049

The Cooperative Ecosystem Studies Unit, Rocky Mountain CESU funding opportunity (Funding Opportunity Number G17AS00049) is a US Geological Survey (USGS) Northern Rocky Mountain Science Center (NOROCK) cooperative agreement aimed at advancing how ecologists combine and analyze complex, mixed data. The core need driving the award is that modern ecological research and management increasingly depend on pulling together heterogeneous information, such as data collected by different methods, across different spatial extents, time periods, and even across multiple species. NOROCK identifies this integration problem as a pressing challenge because many real-world ecological questions cannot be answered well with a single tidy dataset, and because missteps in combining datasets can lead to biased conclusions and uncertainty that is either underestimated or not recognized at all.

The funded work is specifically focused on producing a review of Bayesian approaches for integrating multi-type and multi-species ecological data, with a strong emphasis on spatial and spatiotemporal settings. In practice, this means the project is not primarily about collecting new field data, but about synthesizing and evaluating existing statistical methods and research literature to clarify what works, what assumptions are commonly made, and where current methods fall short when data have spatial structure (nearby locations are related) and temporal structure (observations over time are related). Because ecological processes are rarely independent across space and time, NOROCK wants a review that takes those dependencies seriously rather than treating them as an afterthought.

A major theme in the opportunity is integrated population models (IPMs) and related Bayesian hierarchical models. IPMs are highlighted because they offer a structured way to combine multiple datasets, for example counts, capture-recapture, productivity, telemetry, or occupancy-type observations, to estimate demographic or population parameters more effectively than any single dataset could support on its own. NOROCK underscores why this is important: ecological data collection is often expensive, logistically difficult, and incomplete, so there is a practical need to blend information sources that differ in quality, scale, and sampling design. At the same time, the opportunity points out that conventional IPMs often assume that different datasets are independent, an assumption that may not be realistic when datasets share sampling sites, observers, detection processes, or underlying environmental drivers. The review is expected to address these issues, including how Bayesian methods can relax unrealistic independence assumptions and more appropriately represent shared processes and observation error.

The opportunity also calls attention to challenges unique to multi-species data. In many ecological analyses, multi-species datasets are treated too simplistically, with analysts failing to properly account for species-to-species differences in detection, habitat relationships, or demographic rates. NOROCK notes that this can produce inaccurate inferences and leave key uncertainties unidentified. The intended review should therefore help clarify how multi-species Bayesian hierarchical models can represent species heterogeneity while still borrowing strength across species when appropriate, particularly in spatial and spatiotemporal contexts where computational and modeling complexity can rise quickly.

In terms of program mechanics, this is a discretionary funding opportunity under the Department of the Interior, USGS, using a cooperative agreement as the funding instrument. The CFDA number is 15.808, and the opportunity anticipated a single award with an award ceiling of $40,118. Eligibility is limited to CESU partners (with details referenced in the opportunity’s eligibility clarification text), consistent with how CESU announcements typically operate by leveraging a network of partner institutions to deliver research and technical syntheses relevant to federal science and management needs. The announcement was created on March 29, 2017, with an original closing date of April 14, 2017.

The expected product is a rigorous review that does more than summarize papers; it is intended to function as a bridge to future work and proposals with other partners, particularly proposals that push forward IPMs and Bayesian hierarchical modeling approaches for multi-species and multi-source datasets. In other words, the deliverable is meant to set the table for follow-on applied and methodological projects by clearly mapping the state of the science, identifying gaps, and outlining promising directions for integrating heterogeneous ecological data in spatial and spatiotemporal frameworks.

• The Department of the Interior, Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Ecosystem Studies Unit, Rocky Mountain CESU" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.808.
• This funding opportunity was created on Mar 29, 2017.
• Applicants must submit their applications by Apr 14, 2017. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $40,118.00 in funding.
• The number of recipients for this funding is limited to 1 candidate(s).
• Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).

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