A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Gardner, Toby A.; Ferreira, Juliana Ceccato; Barlow, Jos; Lees, Alexander Charles; Parry, Luke; Vieira, Ima Célia Guimarães; Berenguer, Eduard; Abramovay, Ricardo; Aleixo, Alexandre; Andretti, Christian Borges; Aragão, Luiz E. O. C.; Araújo, Izabel Pesqueira Ribeiro de; Ávila, Williams Souza de; Bardgett, R. D.; Batistella, M.; Begotti, Rodrigo Anzolin; Beldini, Troy Patrick; Blas, Driss Ezzine de; Braga, Rodrigo Fagundes; Braga, Danielle de Lima; Brito, Janaína Gomes de; Camargo, Plínio Barbosa de; Santos, F.; Oliveira, Vinícius Cunha; Cordeiro, Amanda Cardoso Nunes; Cardoso, Thiago Mota; Carvalho, Donato Ribeiro de; Castelani, Sergio; Chaul, Júlio Cesar Mario; Cerri, Carlos Eduardo Pellegrino; Costa, Francisco de Assis; Costa, Clayton; Coudel, Émilie; Coutinho, A. C.; Cunha, Dilip da; D’Antona, Álvaro de Oliveira; Dezincourt, J.; Dias-Silva, Karina; Durigan, Mariana Regina; Esquerdo, J. C. D. M.; Féres, José Gustavo; Ferraz, Sílvio; Ferreira, A. E. d. M.; Fiorini, Alexandria; Silva, L. V. F. da; Frazão, Fábio; Garrett, Rachael; Gomes, Augusto; Goncalves, K. d. S.; Guerrero, José Benito; Hamada, Neusa; Hughes, Ross; Igliori, D.; Jesus, Ederson da Conceição; Juen, Leandro; Júnior, Melo; O., J. M. B. d.; O., R. C. d.; S., C.; Kaufmann, Philip R.; Korasaki, Vanesca; Leal, Cecília Gontijo; Leitão, Rafael P.; Lima, Nereida K. C.; Almeida, Machado de; Lourival, Reinaldo; Louzada, Júlio; Nally, Ralph Mac; Marchand, Sébastien; Maués, M. M.; Moreira, F. M. S.; Morsello, Carla; Moura, Nárgila; Nessimian, Jorge Luiz; Nunes, Sâmia; Oliveira, Victor Hugo Fonseca; Pardini, Renata; Pereira, Heloisa Correia; Pompeu, Paulo Santos; Ribas, Carla R.; Rossetti, F.; Schmidt, Falk; Silva, R. da; Silva, R. C. V. M. da; Silva, T. F. M. R. da; Silveira, Joseph G.; Siqueira, João Victor; Carvalho, Teotônio Soares de; Solar, Ricardo; Tancredi, Nicola Saverio Holanda; Thomson, James Robertson; Torres, Pablo; Vaz‐de‐Mello, Fernando Z.; Veiga, Ruan Carlo Stülpen; Venturieri, Adriano; Viana, Cecilia Fadigas; Weinhold, Diana; Zanetti, Ronald; Zuanon, Jansen

doi:10.1098/rstb.2013.0307

Cited by 18 publications

(5 citation statements)

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“…Our fieldwork was carried out in the municipalities of Santarém and Belterra, Pará state, Brazil (figure 1) under the auspices of the Sustainable Amazon Network [38]. The study region was divided into 286 natural water catchments (mean area 3721 ha, s.d.…”

Section: Materials and Methods (A) Study Regionmentioning

confidence: 99%

Road networks predict human influence on Amazonian bird communities

et al. 2014

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Road building can lead to significant deleterious impacts on biodiversity, varying from direct road-kill mortality and direct habitat loss associated with road construction, to more subtle indirect impacts from edge effects and fragmentation. However, little work has been done to evaluate the specific effects of road networks and biodiversity loss beyond the more generalized effects of habitat loss. Here, we compared forest bird species richness and composition in the municipalities of Santarém and Belterra in Pará state, eastern Brazilian Amazon, with a road network metric called 'roadless volume (RV)' at the scale of small hydrological catchments (averaging 3721 ha). We found a significant positive relationship between RV and both forest bird richness and the average number of unique species (species represented by a single record) recorded at each site. Forest bird community composition was also significantly affected by RV. Moreover, there was no significant correlation between RV and forest cover, suggesting that road networks may impact biodiversity independently of changes in forest cover. However, variance partitioning analysis indicated that RV has partially independent and therefore additive effects, suggesting that RV and forest cover are best used in a complementary manner to investigate changes in biodiversity. Road impacts on avian species richness and composition independent of habitat loss may result from road-dependent habitat disturbance and fragmentation effects that are not captured by total percentage habitat cover, such as selective logging, fire, hunting, traffic disturbance, edge effects and road-induced fragmentation.

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Section: Materials and Methods (A) Study Regionmentioning

confidence: 99%

Road networks predict human influence on Amazonian bird communities

et al. 2014

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“…Mapping forest-agriculture mosaics is essential for understanding effects of land cover changes on economic (e.g., agricultural and silvicultural production, timber extraction, ecotourism) and non-market ecosystem services (e.g., carbon sequestration, water quality, stream flow, species conservation) [1]. Cropland and pastures are the largest use of Earth's ice-free land [2] and have particularly high biodiversity potential [3].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Sentinel-1 and 2 Time Series for Land Cover Classification of Forest–Agriculture Mosaics in Temperate and Tropical Landscapes

et al. 2019

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Monitoring forest–agriculture mosaics is crucial for understanding landscape heterogeneity and managing biodiversity. Mapping these mosaics from remotely sensed imagery remains challenging, since ecological gradients from forested to agricultural areas make characterizing vegetation more difficult. The recent synthetic aperture radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) time series provide a great opportunity to monitor forest–agriculture mosaics due to their high spatial and temporal resolutions. However, while a few studies have used the temporal resolution of S-2 time series alone to map land cover and land use in cropland and/or forested areas, S-1 time series have not yet been investigated alone for this purpose. The combined use of S-1 & S-2 time series has been assessed for only one or a few land cover classes. In this study, we assessed the potential of S-1 data alone, S-2 data alone, and their combined use for mapping forest–agriculture mosaics over two study areas: a temperate mountainous landscape in the Cantabrian Range (Spain) and a tropical forested landscape in Paragominas (Brazil). Satellite images were classified using an incremental procedure based on an importance rank of the input features. The classifications obtained with S-2 data alone (mean kappa index = 0.59–0.83) were more accurate than those obtained with S-1 data alone (mean kappa index = 0.28–0.72). Accuracy increased when combining S-1 and 2 data (mean kappa index = 0.55–0.85). The method enables defining the number and type of features that discriminate land cover classes in an optimal manner according to the type of landscape considered. The best configuration for the Spanish and Brazilian study areas included 5 and 10 features, respectively, for S-2 data alone and 10 and 20 features, respectively, for S-1 data alone. Short-wave infrared and VV and VH polarizations were key features of S-2 and S-1 data, respectively. In addition, the method enables defining key periods that discriminate land cover classes according to the type of images used. For example, in the Cantabrian Range, winter and summer were key for S-2 time series, while spring and winter were key for S-1 time series.

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“…We sampled 45 streams varying from first to third order (according to Strahler [30]) located in the municipality of Paragominas, the northeastern state of Pará, Brazil (Figure 1). The region's climate is mostly rainy and tropical (Köppen's "Aw") with monthly precipitation lower than 60 mm, an average annual temperature of 27.2 • C, air humidity of 81%, and average annual precipitation of 2000 mm [31][32][33]. The region's vegetation type consists of dense rain forests, tropical open forests mixed with lianas and palm trees, and dense alluvial forests [33].…”

Section: Study Areamentioning

confidence: 99%

“…It drains a landscape under the direct and indirect influence of the deforestation process and the construction of federal roads. The region also exhibits mechanized agricultural activities, silviculture, urban areas that are important for the cattle business, and activities that are carried out both by small farmer-colonies and settlements, and large agribusiness farms (see Gardner et al [33] and Oliveira-Junior et al [34] for more details).…”

Section: Study Areamentioning

confidence: 99%

“…Therefore, the collection of field data in The streams were distributed along a gradient of anthropic impact. We selected streams aiming to encompass drainage microbasins with different amounts of native forest remnants and anthropized areas [33]. This region is considered a mosaic of land uses due to its historical land-use patterns.…”

Section: Biological Samplingmentioning

confidence: 99%

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Effects of Environmental Changes on Gerromorpha (Heteroptera: Hemiptera) Communities from Amazonian Streams

et al. 2022

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The presence of environmental conditions that are suitable for the development of agricultural and cattle-raising activities has favored the expansion of land use in the Brazilian Amazon. This expansion changes the environmental conditions of aquatic ecosystems by altering the structure of the streambeds and the physicochemical conditions of the water. Therefore, this manuscript aimed to assess the effect of changes in environmental conditions along a gradient of different land uses on the richness and species composition of Gerromorpha (Heteroptera: Hemiptera) communities in streams from the Brazilian Amazon. We sampled Gerromorpha communities and environmental variables (physical structure of the habitat and physicochemical characteristics of the water) in 45 streams in the municipality of Paragominas in the state of Pará, Brazil. We then performed variation partitioning analyses to assess the relative contribution of habitat structure and water physicochemical variables on the richness and species composition. The Habitat Integrity Index (HII), which measures the habitat physical structure, was the best predictor of species richness. The HII and physicochemical variables were jointly the best predictors of species composition. Our results show that Gerromorpha communities respond to gradients of environmental anthropization in the Amazon region, which reinforces the importance of habitat integrity and water quality for the maintenance of Gerromorpha communities.

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A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Cited by 18 publications

References 0 publications

Road networks predict human influence on Amazonian bird communities

Road networks predict human influence on Amazonian bird communities

Evaluation of Sentinel-1 and 2 Time Series for Land Cover Classification of Forest–Agriculture Mosaics in Temperate and Tropical Landscapes

Effects of Environmental Changes on Gerromorpha (Heteroptera: Hemiptera) Communities from Amazonian Streams

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