{"help":"Return the metadata of a dataset (package) and its resources. :param id: the id or name of the dataset :type id: string","success":true,"result":[{"id":"1260bed2-eac3-42b7-bfbb-35f309630239","name":"code-zaiats-et-al-2023-landscape-ecology","title":"Code for Zaiats et al. 2023 Landscape Ecology","author":"Andrii Zaiats, Megan E. Cattau, David S. Pilliod, Rongsong Liu, Juan M. Requena-Mullor \u0026amp; T. Trevor Caughlin ","author_email":"andriizaiats@u.boisestate.edu","maintainer":"RCDS Data Repository","maintainer_email":"rcds-web@uidaho.edu","notes":"\u003Cp\u003EThis code was used for the study in: Zaiats, A., Cattau M.E., Pilliod D.S., Liu R., Requena-Mullor, J.M., Caughlin, T.T. (2023) Forecasting natural regeneration of sagebrush after wildfires using population models and spatial matching. Landscape Ecology, \u003Ca href=\u0022http:\/\/doi.org\/10.1007\/s10980-023-01621-1\u0022\u003Ehttp:\/\/doi.org\/10.1007\/s10980-023-01621-1\u003C\/a\u003E\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003Cbr \/\u003E\n\u003Cem\u003EContext\u003C\/em\u003E\u003Cbr \/\u003E\nAddressing ecosystem degradation in the Anthropocene will require ecological restoration across large spatial extents. Identifying areas where natural regeneration will occur without direct resource investment will improve scalability of restoration actions.\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EObjectives\u003C\/em\u003E\u003Cbr \/\u003E\nAn ecoregion in need of large scale restoration is the Great Basin of the Western US, where increasingly large and frequent wildfires threaten ecosystem integrity and its foundational shrub species. We develop a framework to forecast where post-wildfire regeneration of sagebrush cover (Artemisia spp.) is likely to occur within the burnt areas across the region (\u0026gt;\u2009900,000 km2).\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EMethods\u003C\/em\u003E\u003Cbr \/\u003E\nFirst, we parameterized population models using Landsat satellite-derived time series of sagebrush cover. Second, we evaluated the out-of-sample performance by predicting natural regeneration in wildfires not used for model training. This model assessment reproduces a management-oriented scenario: making restoration decisions shortly after wildfires with minimal local information. Third, we asked how accounting for increasingly fine-scale spatial heterogeneity could improve model forecasting accuracy.\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EResults\u003C\/em\u003E\u003Cbr \/\u003E\nRegional-level models revealed that sagebrush post-fire recovery is slow, estimating \u0026gt; 80-year time horizon to reach an average cover at equilibrium of 16.6% (CI95% 9\u201325). Accounting for wildfire and within-wildfire spatial heterogeneity improved out-of-sample forecasts, resulting in a mean absolute error of 3.5\u2009\u00b1\u20094.3% cover, compared to the regional model with an error of 7.2\u2009\u00b1\u20095.1% cover.\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EConclusions\u003C\/em\u003E\u003Cbr \/\u003E\nWe demonstrate that combining population models and non-parametric spatial matching provides a flexible framework for forecasting plant population recovery. Models for population recovery applied to Landsat-derived time series will assist restoration decision-making, including identifying priority targets for restoration.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EData Use\u003C\/strong\u003E\u003Cbr \/\u003E\n\u003Cem\u003ELicense\u003C\/em\u003E\u003Cbr \/\u003E\nOpen Access-No license specified\u003Cbr \/\u003E\n\u003Cem\u003ERecommended Citation\u003C\/em\u003E\u003Cbr \/\u003E\nZaiats A, Cattau ME, Pilliod DS, Liu R, Requena-Mullor JM, Caughlin TT. 2023. Code for Zaiats et al. 2023 Landscape Ecology (v1.1). Zenodo. \u003Ca href=\u0022https:\/\/doi.org\/10.5281\/zenodo.7737647\u0022\u003Ehttps:\/\/doi.org\/10.5281\/zenodo.7737647\u003C\/a\u003E\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EFunding\u003C\/strong\u003E\u003Cbr \/\u003E\nUS National Science Foundation and Idaho EPSCoR: OIA-1757324\u003C\/p\u003E\n","url":"https:\/\/data.nkn.uidaho.edu\/dataset\/code-zaiats-et-al-2023-landscape-ecology","state":"Active","log_message":"Edited by awchild.","private":true,"revision_timestamp":"Wed, 09\/06\/2023 - 14:34","metadata_created":"Wed, 04\/26\/2023 - 11:23","metadata_modified":"Wed, 09\/06\/2023 - 14:34","creator_user_id":"6cc16f2c-77c2-4d12-ac06-56bbb86b535b","type":"Dataset","resources":[{"id":"ad5683be-799b-4995-9870-ba1c7ce19e33","revision_id":"","url":"https:\/\/doi.org\/10.5281\/zenodo.7737647","description":"","format":"html","state":"Active","revision_timestamp":"Wed, 09\/06\/2023 - 14:29","name":"Code Access via Zenodo | Code for Zaiats et al. 2023 Landscape Ecology","mimetype":"html","size":"","created":"Wed, 04\/26\/2023 - 11:24","resource_group_id":"bff301ea-b742-427b-954e-e6a326c2ea45","last_modified":"Date changed Wed, 09\/06\/2023 - 14:29"}],"tags":[{"id":"b655b714-945c-42ab-af65-dfbb833d4239","vocabulary_id":"2","name":"ecological forecasting"},{"id":"a31fabc7-430d-4162-b72e-aec639e8d25a","vocabulary_id":"2","name":"natural regeneration"},{"id":"514e354d-5e44-4d87-81f6-f7612e8e6e93","vocabulary_id":"2","name":"ecological restoration"},{"id":"0b3fae08-7bf8-4e8a-a8e2-33f4d1c2364d","vocabulary_id":"2","name":"wildfire"},{"id":"faf6044f-c660-4fa1-9eb1-bd1fc15a5dd4","vocabulary_id":"2","name":"Great Basin"},{"id":"0fd5f6e9-babb-45d4-a5fe-d355a4994b37","vocabulary_id":"2","name":"sagebrush (Artemisia spp.)"}],"groups":[{"description":"\u003Cp\u003EBoise State University is a Carnegie-classified doctoral research university and our students have opportunities to work with talented and accomplished faculty on research, even as undergraduates. Our students go into the workforce better prepared, with expertise outside of their major by taking advantage of opportunities such as certificates in business anthropology, entrepreneurship, or cybersecurity. \u003C\/p\u003E\n\u003Cp\u003ELearn more at \u003Ca href=\u0022https:\/\/www.boisestate.edu\/\u0022\u003Ehttps:\/\/www.boisestate.edu\/\u003C\/a\u003E\u003C\/p\u003E\n","id":"bff301ea-b742-427b-954e-e6a326c2ea45","image_display_url":"https:\/\/data.nkn.uidaho.edu\/sites\/default\/files\/bsu_logo.jpg","title":"Boise State University","name":"group\/boise-state-university"},{"description":"\u003Cp\u003EThe primary objective of Idaho EPSCoR is to stimulate research in niche areas that can become fully competitive in the disciplinary and multidisciplinary research programs of the National Science Foundation and other relevant agencies. Idaho EPSCoR provides support for sustainable increases in Research and Development capacity and advances science and engineering capabilities within the state. \u003C\/p\u003E\n\u003Cp\u003EVisit them at \u003Ca href=\u0022https:\/\/www.idahoepscor.org\u0022\u003Ehttps:\/\/www.idahoepscor.org\u003C\/a\u003E\u003C\/p\u003E\n","id":"e696b239-9ecb-412e-b032-03a75b2b9fd6","image_display_url":"https:\/\/data.nkn.uidaho.edu\/sites\/default\/files\/Idaho_epscor_logo_no_white_background.png","title":"Idaho EPSCoR","name":"group\/idaho-epscor"},{"description":"\u003Cp\u003EGEM3 is an NSF EPSCoR research program seeking to understand how genetic diversity and phenotypic plasticity affect species response to environmental change, shaping both population response and adaptive capacity.\u003C\/p\u003E\n\u003Cp\u003EVisit them at: \u003Ca href=\u0022https:\/\/www.idahogem3.org\u0022\u003Ehttps:\/\/www.idahogem3.org\u003C\/a\u003E\u003C\/p\u003E\n","id":"1812a312-11a4-492d-960b-9a78b4abfe0c","image_display_url":"https:\/\/data.nkn.uidaho.edu\/sites\/default\/files\/GEM3_nov5_logo.png","title":"EPSCoR GEM3","name":"group\/epscor-gem3"}]}]} Error | RCDS Data Repository

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