The Brazilian Program for Biodiversity Research (PPBio) Information System

Pezzini, Flávia Fonseca; Melo, Pablo Hendrigo Alves de; Oliveira, Deyvid; Amorim, R. X. De; Figueiredo, Fernando O. G.; Drucker, Debora Pignatari; Rodrigues, Flávio Rogério de Oliveira; Zuquim, Gabriela; Emilio, Thaíse; Costa, Flávia R. C.; Magnusson, William E.; Sampaio, Adeilza Felipe; Lima, Albertina P.; García, Antonio Ruiz; Manzatto, Ângelo Gilberto; Nogueira, Anselmo; Costa, C. P. Da; Barbosa, Carlos Eduardo de Araújo; Bernardes, Débora; Castilho, Carolina V.; Cunha, Cátia Nunes da; Freitas, Cintia; Cavalcante, Claymir de Oliveira; Brandão, Delacyr da Silva; Rodrigues, Domingos de Jesus; Santos, Eder C.; Baccaro, Fabrício Beggiato; Ishida, Françoise Yoko; Carvalho, Fernanda Antunes; Moulatlet, Gabriel M.; Guillaumet, J-L. B.; Pinto, J. L. P. V.; Schietti, Juliana; Vale, Julio Daniel do; Belger, L.; Verdade, Luciano Martins; Pansonato, Marcelo Petratti; Nascimento, Marcelo Trindade; Santos, Maria Clara Vieira dos; Cunha, M. S. Da; Arruda, Rafael; Barbosa, Reinaldo Imbrózio; Romero, Ricardo Laerte; Pansini, Susamar; Pimentel, Tânia P.

doi:10.7809/b-e.00083

Cited by 24 publications

(11 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data collection was carried out between July and October 2015 in a set of 30 permanent plots established by the Brazilian Program for Biodiversity Research (PPBio) in the eastern portion of Maracá Island (Figure ). These plots follow the RAPELD standard and are arranged systematically along six trails, each 5 km in length, which follow an east‐west orientation and form a 25 km² sampling grid (Pezzini et al., ). The central line of each plot is defined by a transect 250 m in length that strictly follows the elevation contours to reduce environmental variability (Magnusson et al., ).…”

Section: Methodsmentioning

confidence: 99%

Amazon soil charcoal: Pyrogenic carbon stock depends of ignition source distance and forest type in Roraima, Brazil

Carvalho

Fearnside

Nascimento

et al. 2018

Global Change Biology

View full text Add to dashboard Cite

Pyrogenic carbon (PyC) derived from charcoal particles (paleo + modern) deposited in the soil column has been little studied in the Amazon, and our understanding of the factors that control the spatial and vertical distribution of these materials in the region's forest soils is still unclear. The objective of this study was to test the effect of forest type and distance from the ignition source on the PyC stocks contained in macroscopic particles of soil charcoal (≥2 mm; 1 m depth) dispersed in ecotone forests of the northern Brazilian Amazon. Thirty permanent plots were set up near a site that had been occupied by pre-Columbian and by modern populations until the late 1970s. The sampled plots represent seasonal and ombrophilous forests that occur under different hydro-edaphic restrictions. Our results indicate that the largest PyC stock was spatially dependent on distance to the ignition source (<3 km), occurring mainly in flood-free ombrophilous forests (3.46 ± 5.22 Mg PyC/ha). The vertical distribution of PyC in the deeper layers of the soil (> 50 cm) in seasonal forests was limited by hydro-edaphic impediments that restricted the occurrence of charcoal. These results suggest that PyC stocks derived from macroscopic charcoal particles in the soil of this Brazilian Amazon ecotone region are controlled by the distance from the ignition source of the fire, and that forest types with higher hydro-edaphic restrictions can inhibit formation and accumulation of charcoal. Making use of these distinctions reduces uncertainty and improves our ability to understand the variability of PyC stocks in forests with a history of fire in the Amazon.

show abstract

Section: Methodsmentioning

confidence: 99%

Amazon soil charcoal: Pyrogenic carbon stock depends of ignition source distance and forest type in Roraima, Brazil

Carvalho

Fearnside

Nascimento

et al. 2018

Global Change Biology

View full text Add to dashboard Cite

show abstract

“…These sites can be considered characteristic of the typical savannas of the central Brazil, while representing well its variability, ranging from a low altitude sandy savannah (PETR) to upland savannahs on rock (PNCV) or deep soil substrates (PESA). For all sites, vegetation inventory data were collected, following a common scheme within the Program for Biodiversity Research (PPBio; Pezzini et al 2012), using the RAPELD principle, adapted for sampling the Cerrado (Magnusson et al 2005, Teixeira 2017). This system is, however, mostly unprotected and highly threatened thus constituting a global biodiversity hotspot (Myers et al 2000, Klink andMachado 2005) which requires monitoring.…”

Section: Study Sites and Field Datamentioning

confidence: 99%

“…Each sampling transect consists of a 250 m center line that follows the elevation contour, with a varying width, according to the taxon sampled (Pezzini et al 2012, Teixeira 2015. It consists of two 5 km long parallel trails with a distance of 1 km between them, placed in a manner that fit fully within natural vegetation areas.…”

Section: Study Sites and Field Datamentioning

confidence: 99%

“…This system is, however, mostly unprotected and highly threatened thus constituting a global biodiversity hotspot (Myers et al 2000, Klink andMachado 2005) which requires monitoring. For all sites, vegetation inventory data were collected, following a common scheme within the Program for Biodiversity Research (PPBio; Pezzini et al 2012), using the RAPELD principle, adapted for sampling the Cerrado (Magnusson et al 2005, Teixeira 2017). This approach constitutes a standardized integrated sampling of vegetation biomass and multi-taxa biodiversity data, thus allowing research on the linkages between carbon and biodiversity (Teixeira 2017.…”

Section: Study Sites and Field Datamentioning

confidence: 99%

See 1 more Smart Citation

From sample to pixel: multi‐scale remote sensing data for upscaling aboveground carbon data in heterogeneous landscapes

et al. 2018

View full text Add to dashboard Cite

In times of rapid global change, ecosystem monitoring is of utmost importance. Combined field and remote sensing data enable large-scale ecosystem assessments, while maintaining local relevance and accuracy. In heterogeneous landscapes, however, the integration of field-collected data with remote sensing image pixels is not a trivial matter. Indeed, much of the uncertainty in models that use remote sensing to map larger areas lies on the field data integration. In this study, we propose to use fine spatial resolution (5 9 5 m 2 ) remote sensing data as auxiliary data for upscaling field-sampled aboveground carbon data to target (meso-scale, i.e., 30 9 30 m 2 ) image pixels. In this process, we assess the effects of field data disaggregation and extrapolation, with and without the auxiliary data. We test this on three study sites in heterogeneous landscapes of the Brazilian savanna. We thus compare two methods that use auxiliary data-surface method, which uses a weighting layer, and regression method, which applies a regression model-with one method without auxiliary data-cartographic method. To evaluate our results, we compared observed vs. estimated aboveground carbon values (for known samples) at the pixel level. Additionally, we fitted a random forest regression model with the assigned carbon estimates and the target satellite imagery and assessed the influence of the fraction of extrapolated vs. sampled carbon values on model performance. We observed that, in heterogeneous landscapes, the use of fine spatial resolution remote sensing data improves the upscaling of field-based aboveground carbon data to coarser image pixels. We also show that a surface method is more suitable for spatial disaggregation, while a regression approach is preferable for extrapolating non-sampled pixel fractions. In our study, larger datasets, which included a higher proportion of estimated values, generally delivered better models of aboveground carbon than smaller datasets that are assumed to more reliably reflect reality. Our approach enables to link field and remote sensing data, which in turn enables the detailed mapping of aboveground carbon in heterogeneous landscapes over large areas through the optimized integration of field data and multi-scale remote sensing data.

show abstract

“…All the data and metadata presented here are available at the permanent repository of data maintained by the Brazilian National Program of Research in Biodiversity (PPBio) (Pezzini et al, 2012) hosted at the National Institute for Amazonian Research (INPA) in Manaus, Brazil (http://ppbio.inpa.gov.br/ repositorio/dados). The new SRTM DEM and the set of 18 HAND images are available in geoTIFF format.…”

Section: Data Set Location and Formatmentioning

confidence: 99%

Mapping hydrological environments in central Amazonia: ground validation and surface model based on SRTM DEM data corrected for deforestation

Moulatlet

Rennó

Costa

et al. 2015

Earth Syst. Sci. Data

View full text Add to dashboard Cite

Abstract. One of the most important freely available digital elevation models (DEMs) for Amazonia is the one obtained by the Shuttle Radar Topography Mission (SRTM). However, since SRTM tends to represent the vegetation surface instead of the ground surface, the broad use of SRTM DEM as a framework for terrain description in Amazonia is hampered by the presence of deforested areas. We present here two data sets: (1) a deforestationcorrected SRTM DEM for the interfluve between the Purus and Madeira rivers, in central Amazonia, which passed through a careful identification of different environments and has deforestation features corrected by a new method of increasing pixel values of the DEM (Rennó, 2009); and (2) a set of 18 hydrological-topographic descriptors based on the corrected SRTM DEM. Deforestation features are related with the opening of an 800 km road in the central part of the interfluve and occupancy of its vicinity. We used topographic profiles from the pristine forest to the deforested feature to evaluate the recovery of the original canopy coverage by minimizing canopy height variation (corrections ranged from 1 to 38 m). The hydrological-topographic description was obtained by the Height Above the Nearest Drainage (HAND) algorithm, which normalizes the terrain elevation (above sea level) by the elevation of the nearest hydrologically connected drainage. The validation of the HAND data set was done by in situ hydrological description of 110 km of walking trails also available in this data set. The new SRTM DEM expands the applicability of SRTM data for landscape modelling; the data sets of hydrological features based on topographic modelling are undoubtedly appropriate for ecological modelling and an important contribution to environmental mapping of Amazonia. The deforestation-corrected SRTM DEM is available at http://ppbio.inpa.gov.br/knb/metacat/naman.318.3/ppbio; the polygons selected for deforestation correction are available at http://ppbio.inpa.gov.br/knb/metacat/naman.317.3/ppbio; the set of hydrological-topographic descriptors is available at http://ppbio.inpa.gov.br/knb/metacat/naman.544.2/ppbio; the environmental description of access trails is available at http://ppbio.inpa.gov.br/knb/metacat/naman.541.2/ppbio; and the limits of deforestation corrections and drainage validation are available at

show abstract

The Brazilian Program for Biodiversity Research (PPBio) Information System

Cited by 24 publications

References 15 publications

Amazon soil charcoal: Pyrogenic carbon stock depends of ignition source distance and forest type in Roraima, Brazil

Amazon soil charcoal: Pyrogenic carbon stock depends of ignition source distance and forest type in Roraima, Brazil

From sample to pixel: multi‐scale remote sensing data for upscaling aboveground carbon data in heterogeneous landscapes

Mapping hydrological environments in central Amazonia: ground validation and surface model based on SRTM DEM data corrected for deforestation

Contact Info

Product

Resources

About