Multi-scale assessment of a grassland productivity model

<p>Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which t...

Full description

Bibliographic Details
Main Authors: S. D. Taylor, D. M. Browning
Format: Article
Language:English
Published: Copernicus Publications 2021-04-01
Series:Biogeosciences
Online Access:https://bg.copernicus.org/articles/18/2213/2021/bg-18-2213-2021.pdf
id doaj-8a2ee2e82cad46469eb7b19dea956e5f
record_format Article
spelling doaj-8a2ee2e82cad46469eb7b19dea956e5f2021-04-01T07:06:19ZengCopernicus PublicationsBiogeosciences1726-41701726-41892021-04-01182213222010.5194/bg-18-2213-2021Multi-scale assessment of a grassland productivity modelS. D. TaylorD. M. Browning<p>Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial scale for parameterization and thus for subsequently applying it in future productivity projections for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and eastern temperate forest ecoregions of North America. The model was not well suited to grasslands in North American deserts or northwest forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term projections in areas where model performance has been verified, with gaps filled in by future modeling efforts.</p>https://bg.copernicus.org/articles/18/2213/2021/bg-18-2213-2021.pdf
collection DOAJ
language English
format Article
sources DOAJ
author S. D. Taylor
D. M. Browning
spellingShingle S. D. Taylor
D. M. Browning
Multi-scale assessment of a grassland productivity model
Biogeosciences
author_facet S. D. Taylor
D. M. Browning
author_sort S. D. Taylor
title Multi-scale assessment of a grassland productivity model
title_short Multi-scale assessment of a grassland productivity model
title_full Multi-scale assessment of a grassland productivity model
title_fullStr Multi-scale assessment of a grassland productivity model
title_full_unstemmed Multi-scale assessment of a grassland productivity model
title_sort multi-scale assessment of a grassland productivity model
publisher Copernicus Publications
series Biogeosciences
issn 1726-4170
1726-4189
publishDate 2021-04-01
description <p>Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial scale for parameterization and thus for subsequently applying it in future productivity projections for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and eastern temperate forest ecoregions of North America. The model was not well suited to grasslands in North American deserts or northwest forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term projections in areas where model performance has been verified, with gaps filled in by future modeling efforts.</p>
url https://bg.copernicus.org/articles/18/2213/2021/bg-18-2213-2021.pdf
work_keys_str_mv AT sdtaylor multiscaleassessmentofagrasslandproductivitymodel
AT dmbrowning multiscaleassessmentofagrasslandproductivitymodel
_version_ 1724176761672957952