| 1. Identity statement | ||||
| Reference Type | Journal Article | |||
| Site | mtc-m21c.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34R/3TCFC6B | |||
| Repository | sid.inpe.br/mtc-m21c/2019/05.27.11.21 (restricted access) | |||
| Last Update | 2019:05.27.11.21.11 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21c/2019/05.27.11.21.11 | |||
| Metadata Last Update | 2020:01.06.11.42.14 (UTC) administrator | |||
| DOI | 10.1016/j.foreco.2019.05.016 | |||
| ISSN | 0378-1127 | |||
| Citation Key | SilveiraEWACMMSTCS:2019:PrMoPl | |||
| Title | Pre-stratified modelling plus residuals kriging reduces the uncertainty of aboveground biomass estimation and spatial distribution in heterogeneous savannas and forest environments  | |||
| Year | 2019 | |||
| Month | Aug. | |||
| Access Date | 2024, May 18 | |||
| Type of Work | journal article | |||
| Secondary Type | PRE PI | |||
| Number of Files | 1 | |||
| Size | 9208 KiB | |||
| 2. Context | ||||
| Author | 1 Silveira, Eduarda M. O. 2 Espírito Santos, Fernando D. 3 Wulder, Michael A. 4 Acerbi Júnior, Fausto W. 5 Carvalho, Mônica C. 6 Mello, Carlos R. 7 Mello, José Márcio 8 Shimabukuro, Yosio Edemir 9 Terra, Marcela Castro Nunes Santos 10 Carvalho, Luis Marcelo T. 11 Scolforo, José R. S. | |||
| Resume Identifier | 1 2 3 4 5 6 7 8 8JMKD3MGP5W/3C9JJCQ | |||
| Group | 1 2 3 4 5 6 7 8 DIDSR-CGOBT-INPE-MCTIC-GOV-BR | |||
| Affiliation | 1 Universidade Federal de Lavras (UFLA) 2 University of Leicester 3 Canadian Forest Service (Pacific Forestry Centre) 4 Universidade Federal de Lavras (UFLA) 5 Universidade Federal de Lavras (UFLA) 6 Universidade Federal de Lavras (UFLA) 7 Universidade Federal de Lavras (UFLA) 8 Instituto Nacional de Pesquisas Espaciais (INPE) 9 Universidade Federal de Lavras (UFLA) 10 Universidade Federal de Lavras (UFLA) 11 Universidade Federal de Lavras (UFLA) | |||
| Author e-Mail Address | 1 dudalavras@hotmail.com 2 3 mike.wulder@canada.ca 4 fausto@dcf.ufla.br 5 monicacanaam@gmail.com 6 crmello@deg.ufla.br 7 josemarcio@dcf.ufla.br 8 yosio.shimabukuro@inpe.br 9 marcelacsn@gmail.com 10 passarinho@ufla.br 11 jscolforo@dcf.ufla.br | |||
| Journal | Forest Ecology and Management | |||
| Volume | 445 | |||
| Pages | 96-109 | |||
| Secondary Mark | A1_ZOOTECNIA_/_RECURSOS_PESQUEIROS A1_INTERDISCIPLINAR A1_GEOGRAFIA A1_ENGENHARIAS_III A1_CIÊNCIAS_AMBIENTAIS A1_BIODIVERSIDADE A2_GEOCIÊNCIAS A2_ENGENHARIAS_I A2_CIÊNCIAS_AGRÁRIAS_I B1_MATERIAIS B1_ENGENHARIAS_II B1_CIÊNCIAS_BIOLÓGICAS_I B1_BIOTECNOLOGIA | |||
| History (UTC) | 2019-05-27 11:21:11 :: simone -> administrator :: 2019-05-27 11:21:12 :: administrator -> simone :: 2019 2019-05-27 11:22:28 :: simone -> administrator :: 2019 2020-01-06 11:42:14 :: administrator -> simone :: 2019 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Content Type | External Contribution | |||
| Version Type | publisher | |||
| Keywords | AGB Random forests Brazilian biomes Climate Seasonality | |||
| Abstract | Mapping aboveground biomass (AGB)is a challenge in heterogeneous environments, such as the Brazilian savannas and tropical forests located in Minas Gerais state (MG), Brazil. The factors linked to AGB stocks vary in climate, soil characteristics, and stand-level structural attributes over short distances, making generalization of AGB difficult over regional-scales. We offer the hypothesis that stratification into vegetation types at the plot level plus a regression kriging technique, can reduce the variability of factors controlling AGB, helping to select the appropriate predictor variables and result in an ability to produce reliable models and maps. To do so, we incorporate remotely sensed data (Landsat and MODerate resolution Imaging Spectroradiometer-MODIS), spatio-environmental variables, and forest inventory data to develop spatial-explicit maps of AGB across three important Brazilian biomes (savanna, Atlantic forest, and semi-arid woodland). We modelled and predicted the spatial distribution of AGB of six individual vegetation types of savanna-forest biomes (shrub savanna, woodland savanna, densely wooded savanna, deciduous forest, semi-deciduous forest and rain forest), utilizing a random forests (RF)algorithm plus residual kriging, selecting the lowest number of variables that offer the best predictive performance. The stratified models notably improved the AGB prediction by reducing the mean absolute error MAE (%)and the root-mean-square error RMSE (Mg/ha)for all vegetation types, mainly for shrub savanna (MAE reduced from 82.69 to 54.73%). The AGB spatial distribution is governed mainly by precipitation and seasonality. The south and east of MG presented high values of AGB due to the predominance of semi-deciduous trees and rain forest conditions within Atlantic forest biome (total of 491,456,607 Mg), with a higher amount rain over the year, lower temperatures, and lower precipitation seasonality. Rain forests have the largest mean AGB per area (157.71 Mg/ha)while semi-deciduous forests hold the largest AGB stocks in the state (583,176,472 Mg). Shrub savannas, located in the central, northwest and north regions of MG (lower amount of rain, higher temperatures and strong seasonality), accounted the lowest amount of AGB in both total AGB (27,906,281 Mg)and AGB per area (18.80 Mg/ha). Our study demonstrates that stratification can reduce variability and improve estimates by developing individual models and selecting optimal predictor variables dependent on the characteristics of specific vegetation types. The methods demonstrated and the resultant maps and estimates improve the quality of regional biomass estimates needed to understand and mitigate climate change, enabling researchers to refine estimates of greenhouse gas emissions. | |||
| Area | SRE | |||
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Pre-stratified modelling plus... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| Language | en | |||
| Target File | Silveira1-s2.0-S0378112719301185-main.pdf | |||
| User Group | simone | |||
| Reader Group | administrator simone | |||
| Visibility | shown | |||
| Archiving Policy | denypublisher denyfinaldraft24 | |||
| Read Permission | deny from all and allow from 150.163 | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Next Higher Units | 8JMKD3MGPCW/3ER446E | |||
| Citing Item List | sid.inpe.br/bibdigital/2013/09.13.21.11 1 | |||
| Dissemination | WEBSCI; PORTALCAPES; COMPENDEX; SCOPUS. | |||
| Host Collection | urlib.net/www/2017/11.22.19.04 | |||
| 6. Notes | ||||
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||