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The Forest Pulse” Revista De Biología Tropical, Vol Revista de Biología Tropical ISSN: 0034-7744 [email protected] Universidad de Costa Rica Costa Rica Olivero, Jesús; Ferri, Francisco; Acevedo, Pelayo; Lobo, Jorge M.; Fa, John E.; Farfán, Miguel Á.; Romero, David; The Amazonian communities of Cascaradura, Niñal, Curimacare, Chapazón, Solano and Guzmán Blanco; Real, Raimundo Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: “The Forest Pulse” Revista de Biología Tropical, vol. 64, núm. 4, 2016, pp. 1661-1682 Universidad de Costa Rica San Pedro de Montes de Oca, Costa Rica Available in: http://www.redalyc.org/articulo.oa?id=44947539024 How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: “The Forest Pulse” Jesús Olivero1*, Francisco Ferri2,3, Pelayo Acevedo4, Jorge M. Lobo2, John E. Fa1,5,6, Miguel Á. Farfán1, David Romero1, the Amazonian communities of Cascaradura, Niñal, Curimacare, Chapazón, Solano and Guzmán Blanco7 & Raimundo Real1 1. Departamento de Biología Animal, Universidad de Málaga, Campus de Teatinos s/n, 29071 Málaga, Spain; [email protected], [email protected], [email protected], [email protected], [email protected] 2. Departamento de Biogeografía y Cambio Global, Museo Nacional de Ciencias Naturales CSIC & Laboratorio Internacional en Cambio Global CSIC-PUC (LINCGlobal), Calle José Gutiérrez Abascal 2, 28006, Madrid, Spain; [email protected] 3. ‘Rui Nabeiro’ Biodiversity Chair, CIBIO, University of Évora, Largo dos Colegiais, 7000, Évora, Portugal; [email protected] 4. SaBio IREC, Instituto de Investigación en Recursos Cinegéticos (UCLM-CSIC-JCCM), Ronda de Toledo s/n, 13071, Ciudad Real, Spain; [email protected] 5. Division of Biology and Conservation Ecology, School of Science and the Environment, Manchester Metropolitan University, Manchester M1 5GD, UK 6. Center for International Forestry Research (CIFOR), Jalan Cifor, Situ Gede, Bogor 16115, Indonesia. 7. Municipios Atabapo, Río Negro and Maroa, Estado Amazonas, Venezuela, see Appendix 1; [email protected] * Correspondence Received 18-XI-2015. Corrected 20-VI-2016. Accepted 21-VII-2016. Abstract: Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conserva- tion of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as “The Forest Pulse”. These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a conse- quence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing, overall hunting, and more specifically the hunting of primates, Mazama americana, Dasyprocta fuliginosa, and Tayassu pecari. Our results showed that TEK-based approaches can serve as a basis for validating the livelihood relevance of landscapes in high-value conservation areas, which can form the basis for furthering the management of natural resources in these regions. Rev. Biol. Trop. 64 (4): 1661-1682. Epub 2016 December 01. Key words: Amazonia, forest conservation, greenness, indigenous people, land cover, land use, remote sensing. Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 64 (4): 1661-1682, December 2016 1661 Alarming deforestation rates for the entire & Rodríguez, 2011), the region’s biodiversity Amazon region imperil the future of this high- is known to be under severe threat (Huber, biodiversity biome (Saatchi, Nelson, Podest, 2001). The remoteness of the region has indi- & Holt, 2000). By the end of the 21st century, rectly ensured its preservation. However, its forest cover in this region is predicted to have inaccessibility has also impeded adequate declined at rates of up to 80 %, as a result of monitoring of the region’s natural richness climate warming and desiccation (Betts, Cox, for its conservation. Collins, Harris, Huntingford, & Jones, 2004; New techniques have emerged that utilize Cox et al., 2004; Intergovernmental Panel local (or traditional) ecological knowledge on Climate Change, 2007; Salazar, Nobre, (hereafter, TEK) to monitor species distribu- & Oyama, 2007; Nepstad, Stickler, Soares- tions and population trends over time. These, alongside the use of geospatial technologies, Filho, & Merry, 2008). Range and rates of can adequately defeat the constraints of assess- deforestation in the Amazon have been deter- ing large natural areas such as the Venezuelan mined using satellite imagery but mostly at Amazonian region (Ostrom, Burger, Field, local scales (Asner, Jeller, Pereira, & Zweede, Norgaard, & Policansky, 1999; Kerr & Ostro- 2002; Marsik, Stevens, & Southworth, 2011). vsky, 2003). To date, a number of regional and However, effective conservation of Amazo- continental land-cover assessments have been nian forest regions requires land cover map- completed for the Amazon Basin (Saatchi et al., ping (Saatchi et al., 2000) to prioritize those 2000; Eva et al., 2004; Gond et al., 2011; Han- expanses in greatest need of protection (Bunce, sen et al., 2013; Mitchard et al., 2014; Pacheco, Barr, Clarke, Howard, & Lane, 1996; Kerr & Aguado, & Mollicone, 2014) that have also Ostrovsky, 2003). included the Venezuelan portion of the Basin. Fieldwork by scientists can be severely By employing a combination of remote sens- constrained in regions where personal secu- ing techniques, supported by TEK, we generate rity may be compromised because of armed a 250 m resolution land-cover classification conflicts, or geographical remoteness. In these map for the Venezuelan Amazon. First, we situations, satellite remote sensing is a power- develop a land-cover map from hyper-temporal ful tool for charting land use patterns and for remotely sensed greenness. Land-cover classes detecting changes over time (Iverson, Graham, are individually related to pulsating patterns & Cook, 1989; Toivonen, Mäki, & Kalliola, of change in greenness, which help landscape 2007; Baratolo et al., 2011). Even then, ade- identification and have potential for character- quate ecological interpretation of the resulting izing the evolution of land classes in future land units may be limited by lack of ground time periods; these profiles form part of the data (Stehman & Czaplewski, 1998; Shao & map legend (De Bie et al., 2008), and for this Wu, 2008). To overcome this limitation, local reason we labelled our map as “The Forest knowledge proffered by indigenous commu- Pulse”. Onto this map we overlay TEK data nities living in the area of interest can assist provided by six indigenous communities to val- land-cover mapping by identifying landscapes idate the relevance of our map for indigenous of value to their livelihoods (Berkes, Cold- livelihoods and land uses. We then characterize ing, & Folke, 2000; Herlihy & Knapp, 2003; land classes using additional remotely sensed Robbins, 2003; Naidoo & Hill, 2006; Lauer & information in order to further understand Aswani, 2008). the correspondence between land classes and The Venezuelan Amazon, wholly included landscape units. within the administrative State of Amazonas, is an isolated part of the country that still remains MATERIAL AND METHODS largely uncharted. Although the standing natu- ral vegetation of the region has remained The study area: The study area (0º15’58” relatively unchanged (Madi, Vázquez, León, - 6º29’20” N & 62º59’35” - 68º7’24” W) 1662 Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 64 (4): 1661-1682, December 2016 covered a total of 51 000 km2 (less than 5 % Orinoco Rivers (mountain landscapes covered of the Venezuelan territory) and is underlined by evergreen forests and scattered with table- by the Guyana Shield (Fig. 1). Due to its high top
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