Title: Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists: Survey Data Open Access Deposited
|Citations to related material|
(2017). Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists: Survey Data [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/Z2FF3QJ9
Files (Count: 7; Size: 896 KB)
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|Ecosystem Services Adoption Readme.txt||2017-12-21||2017-12-21||7.5 KB||Open Access||
|Ecosystem Services and Resource ...a.csv||2017-09-06||2017-12-21||60.6 KB||Open Access||
|Ecosystem Services and Research ...x.csv||2017-12-21||2017-12-21||61.4 KB||Open Access||
|Ecosystem Services and Research ...y.pdf||2017-09-06||2018-07-09||341 KB||Open Access||
|Ecosystem Services and Research ...a.csv||2017-09-06||2017-12-21||36 KB||Open Access||
|Ecosystem Services and Resource ...x.csv||2017-12-21||2017-12-21||60.6 KB||Open Access||
|Ecosystem Services and Resource ...y.pdf||2017-09-06||2018-07-09||329 KB||Open Access||
Read Me File for the Data Set: Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists: Survey Data
Daniel D. Engel, Mary Anne Evans , Bobbi S. Low , and Jeff Schaeffer
Contact: Daniel D. Engel, University of Michigan, email@example.com
Description of the Data Set:
This data set was compiled as an attempt to understand how natural resource managers and research ecologists in the Great Lakes region integrate the ecosystem services (ES) paradigm into their work.
This dataset is comprised of six files:
* Ecosystems Services and Research Ecologists Survey Data.csv contains the results of an online survey of Resource Ecologists in the Great Lakes region.
* Ecosystems Services and Research Ecologists Data Index.csv contains information about the questions asked in the survey and how to interpret the responses.
* Ecosystems Services and Research Ecologists Survey.pdf contains the survey instrument used in gathering data from Research Ecologists for this project.
* Ecosystems Services and Research Managers Survey Data.csv contains the results of an online survey of Resource Managers in the Great Lakes region.
* Ecosystems Services and Research Managers Data Index.csv contains information about the questions asked in the survey and how to interpret the responses.
* Ecosystems Services and Research Managers Survey.pdf contains the survey instrument used in gathering data from Research Managers for this project.
Ecosystem services (ES), or the benefits people obtain from ecosystems, have gained much momentum in natural resource management in recent decades as a relatively comprehensive approach to provide quantitative tools for improving decision-making and policy design. However, to date we know little about whether and how natural resource practitioners, from natural resource managers to research ecologists (hereafter managers and ecologist respectively), have adopted the ES paradigm into their respective work.
We addressed this knowledge gap by surveying managers and ecologists about whether and how they have adopted the ES paradigm into their respective work. First, we surveyed federal, state, provincial and tribal managers in the Great Lakes region about their perception and use of ES as well as the relevance of specific services to their work. Although results indicate that fewer than 31% of the managers said they currently consider economic values of ES, 79% of managers said they would use economic information on ES if they had access to it. Additionally, managers reported that ES-related information was generally inadequate for their resource management needs. We also assessed managers by dividing them into identifiable groups (e.g. managers working in different types of government agencies or administrative levels) to evaluate differential ES integration. Overall, results suggest a desire among managers to transition from considering ES concepts in their management practices to quantifying economic metrics, indicating a need for practical and accessible valuation techniques.
Due to a sample of opportunity at the USGS Great Lakes Science Center (GLSC), we also evaluated GLSC research ecologists integration of the ES paradigm because they play an important role by contributing requisite ecological knowledge for ES models. Managers and ecologists almost unanimously agreed that it was appropriate to consider ES in resource management and also showed convergence on the high priority ES. However, ecologists appeared to overestimate the adequacy of ES-related information they provide as managers reported the information was inadequate for their needs. This divergence may reflect an underrepresentation of ecological economists in this system who can aid in translating ecological models into estimates of human well-being. (This abstract was adopted from the thesis Understanding Ecosystem Services Adoption by Resource Managers and Research Ecologists https://deepblue.lib.umich.edu/handle/2027.42/113076.)
The dataset for the research ecologists has had some data removed as it could be considered personally identifiable information due to the small sample size in that population. The surveys associated with both data sets have also been included in PDF format.
For data on how natural resource managers have adopted the ES paradigm, we used a web-based survey to collect responses from a stratified random sample of 1,041 resource managers in the Great Lakes basin. We designed the survey using Qualtrics Research Suite (qualtrics.com, 2015) and distributed it via email. Respondents were informed that the survey was voluntary and that all data would be kept anonymous by aggregating and de-identifying the information. We designed survey questions to gather information on the relevance of ES to managers' work as well as their backgrounds, jurisdictions, and priorities. Most questions were closed-ended, while a few were open-ended, allowing the managers to respond more freely.
We received 245/1041 responses from managers, a response rate of 23.5%. We interpret this to be a conservative representation of our target audience because our sampling methods likely led to some percentage of non-resource managers receiving an invitation to participate. Of these 245 respondents, 46.1% agreed to do the survey, self-identified themselves as a resource manager in the Great Lakes basin, and completed the survey, leaving a final sample size of 113 for analysis.
For research ecologists, we used two methods for collecting data about the study subjects: interviews and surveys. The interviews with research ecologists and associated data are not provided here because they include too much personally identifiable information.
Following the interviews, we sent the survey to 36 ecologists, of which 32 responded for a response rate of 89%. Of these, 7 individuals declined to take part in the survey, self-identified as non-research scientists, or did not complete the survey, leaving a final sample size of 25 completed surveys.
As with the managers, the online surveys were designed in Qualtrics Research Suite (qualtrics.com) and distributed via email to the scientists following the interview. Survey responses were kept anonymous resulting in our not being able to connect individual responses between the interview and survey. The survey had primarily closed-response questions with a few open-ended questions allowing respondents to provide clarification for their responses. We designed questions to gain information regarding the ecologists' research, how ES might relate to their research, and their perspective on integrating ES into resource management.
In one series of questions important to the analysis, we presented a list of 32 ES and asked the managers and ecologist to rate the relevance of each ES from 0 (Strongly Unrelated to their research) to 4 (Strongly Related). In this series of questions, we used a Qualtrics tool called a slider bar on which the respondents could select any decimal from 0 to 4 down to the hundredths place, making it a functionally continuous variable. This list of ES was adapted from the Millennium Ecosystem Assessment's list of ES (2005).
This data set is made available under a Creative Commons Attribution license (CC-BY). Please cite this data as:
Engel, D. D., M.A. Evans, B.S. Low & J. Schaeffer (2017). Resource Management in the Great Lakes Region: Integration of Ecosystem Services into Decision-Making [Data set]. University of Michigan. https://doi.org/10.7302/z2ff3qj9