Measuring at all scales: sourcing data for more flexible restoration references

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Measuring at all scales: sourcing data for more flexible restoration references. / Shackelford, Nancy; Dudney, Joan; Stueber, Melinda M. et al.
In: Restoration Ecology, Vol. 32, No. 8, e13541, 11.2024.

Research output: Journal contributionsScientific review articlesResearch

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Shackelford N, Dudney J, Stueber MM, Temperton VM, Suding KL. Measuring at all scales: sourcing data for more flexible restoration references. Restoration Ecology. 2024 Nov;32(8):e13541. Epub 2021 Sept 3. doi: 10.1111/rec.13541

Bibtex

@article{374e3b7c1ef44de293b0c116d687da62,
title = "Measuring at all scales: sourcing data for more flexible restoration references",
abstract = "Restoration has long used the reference concept as a cornerstone in setting targets, designing interventions, and benchmarking success. Following the initial applications of restoration references, however, the definition and broader relevance has been debated. Particularly in an era of directional global change, using historic or even contemporary ecosystem models has been contentious among restoration scientists and practitioners. In response, there have been calls for increasing flexibility in how references are defined and diversifying sources of data used to describe a reference. Previous frameworks suggest reference information can be drawn from sources across two main axes of time and space, covering historic to contemporary sources, and near to far spatial scales. We extend these axes by including future projections of climate and species composition and regional ecological information that is spatially disconnected from defined ecosystem types. Using this new framework, we conducted a review of restoration literature published between 2010 and 2020, extracting the temporal and spatial scales of reference data and classifying reference metrics by data type. The studies overwhelmingly focused on contemporary, ecosystem-specific references to benchmark a completed project's success. The most commonly reported reference metrics were plant-based, and contemporary reference data sources were more diverse than historical or future reference data. As global conditions continue to shift, we suggest that restoration projects would benefit by expanding reference site information to include forecasted and spatially diverse data. A greater diversity of data sources can enable higher flexibility and long-term restoration success in the face of global change.",
keywords = "disturbance, ecological memory, historical ecology, natural range of variation, restoration success, restoration targets, site similarity, Ecosystems Research, Biology",
author = "Nancy Shackelford and Joan Dudney and Stueber, {Melinda M.} and Temperton, {Vicky M.} and Suding, {Katharine L.}",
note = "{\textcopyright} 2021 Society for Ecological Restoration. ",
year = "2024",
month = nov,
doi = "10.1111/rec.13541",
language = "English",
volume = "32",
journal = "Restoration Ecology",
issn = "1061-2971",
publisher = "Wiley-Blackwell Publishing Ltd.",
number = "8",

}

RIS

TY - JOUR

T1 - Measuring at all scales: sourcing data for more flexible restoration references

AU - Shackelford, Nancy

AU - Dudney, Joan

AU - Stueber, Melinda M.

AU - Temperton, Vicky M.

AU - Suding, Katharine L.

N1 - © 2021 Society for Ecological Restoration.

PY - 2024/11

Y1 - 2024/11

N2 - Restoration has long used the reference concept as a cornerstone in setting targets, designing interventions, and benchmarking success. Following the initial applications of restoration references, however, the definition and broader relevance has been debated. Particularly in an era of directional global change, using historic or even contemporary ecosystem models has been contentious among restoration scientists and practitioners. In response, there have been calls for increasing flexibility in how references are defined and diversifying sources of data used to describe a reference. Previous frameworks suggest reference information can be drawn from sources across two main axes of time and space, covering historic to contemporary sources, and near to far spatial scales. We extend these axes by including future projections of climate and species composition and regional ecological information that is spatially disconnected from defined ecosystem types. Using this new framework, we conducted a review of restoration literature published between 2010 and 2020, extracting the temporal and spatial scales of reference data and classifying reference metrics by data type. The studies overwhelmingly focused on contemporary, ecosystem-specific references to benchmark a completed project's success. The most commonly reported reference metrics were plant-based, and contemporary reference data sources were more diverse than historical or future reference data. As global conditions continue to shift, we suggest that restoration projects would benefit by expanding reference site information to include forecasted and spatially diverse data. A greater diversity of data sources can enable higher flexibility and long-term restoration success in the face of global change.

AB - Restoration has long used the reference concept as a cornerstone in setting targets, designing interventions, and benchmarking success. Following the initial applications of restoration references, however, the definition and broader relevance has been debated. Particularly in an era of directional global change, using historic or even contemporary ecosystem models has been contentious among restoration scientists and practitioners. In response, there have been calls for increasing flexibility in how references are defined and diversifying sources of data used to describe a reference. Previous frameworks suggest reference information can be drawn from sources across two main axes of time and space, covering historic to contemporary sources, and near to far spatial scales. We extend these axes by including future projections of climate and species composition and regional ecological information that is spatially disconnected from defined ecosystem types. Using this new framework, we conducted a review of restoration literature published between 2010 and 2020, extracting the temporal and spatial scales of reference data and classifying reference metrics by data type. The studies overwhelmingly focused on contemporary, ecosystem-specific references to benchmark a completed project's success. The most commonly reported reference metrics were plant-based, and contemporary reference data sources were more diverse than historical or future reference data. As global conditions continue to shift, we suggest that restoration projects would benefit by expanding reference site information to include forecasted and spatially diverse data. A greater diversity of data sources can enable higher flexibility and long-term restoration success in the face of global change.

KW - disturbance

KW - ecological memory

KW - historical ecology

KW - natural range of variation

KW - restoration success

KW - restoration targets

KW - site similarity

KW - Ecosystems Research

KW - Biology

UR - http://www.scopus.com/inward/record.url?scp=85115108266&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/ec5d2efb-1026-3510-a624-8cf1292e729b/

U2 - 10.1111/rec.13541

DO - 10.1111/rec.13541

M3 - Scientific review articles

AN - SCOPUS:85115108266

VL - 32

JO - Restoration Ecology

JF - Restoration Ecology

SN - 1061-2971

IS - 8

M1 - e13541

ER -

DOI