Rural Wage-Earners’ Attitudes Towards Diverse Wildlife Groups Differ Between Tropical Ecoregions: Implications for Forest and Savanna Conservation in the Brazilian Amazon

Understanding people’s attitudes towards wildlife species is key for developing and effectively implementing conservation initiatives. Although attitudes towards different wildlife classes have been examined separately within a variety of regions, there have been no comprehensive comparisons of attitudes towards wildlife between different tropical ecoregions over large spatial scales. Here, we examined attitudes of 106 rural wage-earners from two ecoregions in the eastern Brazilian Amazon. We used generalized Linear Models (GLMs) to examine the influence of socioeconomic variables and ecoregion type on attitudes towards wildlife species, grouped into three classes (liked, disliked, and damage income). Overall we obtained attitudes regarding 57 wildlife species that were organized into 11 faunal groups (amphibians, ants, bats, birds, fishes, medium-bodied mammals, large-bodied mammals, primates, snakes, tortoises and turtles, and other invertebrates). Ecoregions where wage-earners lived was the strongest predictor of the total number of liked and disliked wildlife species. The total number of species damaging income was explained by socioeconomic variables related to the number of people living in the property and level of education. Medium and large-bodied mammals were most frequently reported both as liked and causing damage, while snakes were most frequently reported as disliked in both ecoregions. Although socioeconomic variables were important predictors to wage-earners’ attitudes towards wildlife species, the environment (ecoregion) was the strongest predictor affecting human-wildlife attitudes. Our findings contribute with information about the importance of considering differences in local attitudes across a representative spectrum of wildlife species to inform the identification of effective focal species in different tropical regions.

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Preparation burning may not improve short-term seed survival in an Amazonian savanna

Experimental Results ◽

10.1017/exp.2021.2 ◽

2021 ◽

Vol 2 ◽

Author(s):

Victor J. U. R Rodriguez Chuma ◽

Darren Norris ◽

Taires P. da Silva ◽

Jéssica A. da Silva ◽

Keison S. Cavalcante ◽

...

Keyword(s):

Generalized Linear Models ◽

Linear Models ◽

Brazilian Amazon ◽

Seed Removal ◽

Euterpe Oleracea ◽

Seed Type ◽

Short Term ◽

Tropical Regions ◽

Seed Infestation

Abstract The role of fire in the management of degraded areas remains strongly debated. Here we experimentally compare removal and infestation of popcorn kernels (Zea mays L. – Poaceae) and açaí fruits (Euterpe oleracea Mart. – Arecaceae) in one burned and two unburned savanna habitats in the eastern Brazilian Amazon. In each habitat, a total of ten experimental units (five per seed type) were installed, each with three treatments: (1) open access, (2) vertebrate access, and (3) invertebrate access. Generalized linear models showed significant differences in both seed removal (P < 0.0001) and infestation (P < 0.0001) among seed type, habitats and access treatments. Burned savanna had the highest overall seed infestation rate (24.3%) and invertebrate access increased açaí seed infestation levels to 100% in the burned savanna. Increased levels of invertebrate seed infestation in burned savanna suggest that preparation burning may be of limited use for the management and restoration of such habitats in tropical regions.

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Spatial scales of temperature and salinity variability estimated from Argo observations

Ocean Science Discussions ◽

10.5194/osd-12-1793-2015 ◽

2015 ◽

Vol 12 (4) ◽

pp. 1793-1814

Author(s):

F. Ninove ◽

P. Y. Le Traon ◽

E. Remy ◽

S. Guinehut

Keyword(s):

Large Scale ◽

Spatial Scales ◽

Deep Ocean ◽

General Tendency ◽

Zero Crossing ◽

Tropical Regions ◽

Covariance Functions ◽

Salinity Variability ◽

First Time

Abstract. Argo observations from 2005 to 2013 are used to characterize spatial scales temperature and salinity variations from the surface down to 1500 m. Simulations are first performed to analyze the sensitivity of results to Argo sampling; they show that several years of Argo observations are required to estimate the spatial scales of ocean variability over 20° × 20° boxes. Spatial scales are then computed over several large scale areas. Zonal and meridional spatial scales (Lx and Ly which are also zero crossing of covariance functions) vary as expected with latitudes. Scales are of about 100 km at high latitudes and more of 700 km in the Indian and Pacific equatorial/tropical regions. Zonal and meridional scales are similar: except in these tropical/equatorial regions where zonal scales are much larger (by a factor of 2 to 3) than meridional scales. Spatial scales are the largest close to the surface and have a general tendency for temperature to increase in deeper layers. There are significant differences between temperature and salinity scales, in particular, in the deep ocean. Results are consistent with previous studies based on sparse in-situ observations or satellite altimetry. They provide, however, for the first time a global description of temperature and salinity scales of variability and a characterization of their variations according to depths.

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The role of spatial scale and background climate in the latitudinal temperature response to deforestation

Earth System Dynamics Discussions ◽

10.5194/esdd-6-1897-2015 ◽

2015 ◽

Vol 6 (2) ◽

pp. 1897-1937 ◽

Cited By ~ 2

Author(s):

Y. Li ◽

N. de Noblet-Ducoudré ◽

E. L. Davin ◽

N. Zeng ◽

S. Motesharrei ◽

...

Keyword(s):

Temperature Change ◽

Vegetation Change ◽

Spatial Scales ◽

Empirical Studies ◽

Temperature Response ◽

Shortwave Radiation ◽

Climate Conditions ◽

Tropical Regions ◽

Underlying Mechanisms ◽

Background Climate

Abstract. Previous modeling and empirical studies have shown that the biophysical impact of deforestation is to warm the tropics and cool the extra-tropics. In this study, we use an earth system model to investigate how deforestation at various spatial scales affects ground temperature, with an emphasis on the latitudinal temperature response and its underlying mechanisms. Results show that the latitudinal pattern of temperature response depends non-linearly on the spatial extent of deforestation and the fraction of vegetation change. Compared with regional deforestation, temperature change in global deforestation is greatly amplified in temperate and boreal regions, but is dampened in tropical regions. Incremental forest removal leads to increasingly larger cooling in temperate and boreal regions, while the temperature increase saturates in tropical regions. The latitudinal and spatial patterns of the temperature response are driven by two processes with competing temperature effects: decreases in absorbed shortwave radiation due to increased albedo and decreases in evapotranspiration. These changes in the surface energy balance reflect the importance of the background climate on modifying the deforestation impact. Shortwave radiation and precipitation have an intrinsic geographical distribution that constrains the effects of biophysical changes and therefore leads to temperature changes that are spatially varying. For example, wet (dry) climate favors larger (smaller) evapotranspiration change, thus warming (cooling) is more likely to occur. Further analysis on the contribution of individual biophysical factors (albedo, roughness, and evapotranspiration efficiency) reveals that the latitudinal signature embodied in the temperature change probably result from the background climate conditions rather than the initial biophysical perturbation.

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Integration of Sentinel-1 and Sentinel-2 for Classification and LULC Mapping in the Urban Area of Belém, Eastern Brazilian Amazon

Sensors ◽

10.3390/s19051140 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1140 ◽

Cited By ~ 26

Author(s):

Paulo Tavares ◽

Norma Beltrão ◽

Ulisses Guimarães ◽

Ana Teodoro

Keyword(s):

Optical Sensors ◽

Brazilian Amazon ◽

Synthetic Aperture ◽

Tropical Regions ◽

Cloud Coverage ◽

Optical Images ◽

Vegetation Indexes ◽

Tropical Areas ◽

The City ◽

Sentinel 2

In tropical regions, such as in the Amazon, the use of optical sensors is limited by high cloud coverage throughout the year. As an alternative, Synthetic Aperture Radar (SAR) products could be used, alone or in combination with optical images, to monitor tropical areas. In this sense, we aimed to select the best Land Use and Land Cover (LULC) classification approach for tropical regions using Sentinel family products. We choose the city of Belém, Brazil, as the study area. Images of close dates from Sentinel-1 (S-1) and Sentinel-2 (S-2) were selected, preprocessed, segmented, and integrated to develop a machine learning LULC classification through a Random Forest (RF) classifier. We also combined textural image analysis (S-1) and vegetation indexes (S-2). A total of six LULC classifications were made. Results showed that the best overall accuracy (OA) was found for the integration of S-1 and S-2 (91.07%) data, followed by S-2 only (89.53%), and S-2 with radiometric indexes (89.45%). The worse result was for S-1 data only (56.01). For our analysis the integration of optical products in the stacking increased de OA in all classifications. However, we suggest the development of more investigations with S-1 products due to its importance for tropical regions.

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Evaluation of Multi-Reanalysis Solar Radiation Products Using Global Surface Observations

Atmosphere ◽

10.3390/atmos10020042 ◽

2019 ◽

Vol 10 (2) ◽

pp. 42 ◽

Cited By ~ 4

Author(s):

Xiaomin Peng ◽

Jiangfeng She ◽

Shuhua Zhang ◽

Junzhong Tan ◽

Yang Li

Keyword(s):

Solar Radiation ◽

Large Scale ◽

Spatial Scales ◽

Global Solar Radiation ◽

Hydrological Process ◽

China Meteorological Administration ◽

Surface Solar Radiation ◽

Climate Zones ◽

Tropical Regions ◽

Spatial Coverage

Solar radiation incident at the Earth’s surface is an essential driver of the energy exchange between the atmosphere and the surface and is also an important input variable in the research on the surface eco-hydrological process. The reanalysis solar radiation dataset is characterized by a long time series and wide spatial coverage and is used in the research of large-scale eco-hydrological processes. Due to certain errors in their production process of the reanalysis of solar radiation products, reanalysis products should be evaluated before application. In this study, three global solar-radiation reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) in different temporal scales and climate zones were evaluated using surface solar-radiation observations from the National Meteorological Information Center of the China Meteorological Administration (CMA, Beijing, China) and the Global Energy Balance Archive (GEBA, Zürich, Switzerland) from 2000 to 2009. All reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) overestimated with an annual bias of 14.86 W/m2, 22.61 W/m2, and 31.85 W/m2; monthly bias of 15.17 W/m2, 21.29 W/m2, and 36.91 W/m2; and seasonal bias of 15.08 W/m2, 21.21 W/m2, and 36.69 W/m2, respectively. In different Köppen climate zones, the annual solar radiation of ERA-Interim performed best in cold regions with a bias of 10.30 W/m2 and absolute relative error (ARE) of 8.98%. However, JRA-55 and NCEP-DOE showed the best performance in tropical regions with a bias of 20.08 W/m2 and −0.12 W/m2, and ARE of 11.00% and 9.68%, respectively. Overall, through the evaluations across different temporal and spatial scales, the rank of the three reanalysis products in order was the ERA-Interim, JRA-55, and NCEP-DOE. In addition, based on the evaluation, we analyzed the relationship between the error (ARE) of the reanalysis products and cloud cover, aerosol, and water vapor, which significantly influences solar radiation and we found that cloud was the main cause for errors in the three solar radiation reanalysis products. The above can provide a reference for the application and downscaling of the three solar radiation reanalysis products.

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The role of spatial scale and background climate in the latitudinal temperature response to deforestation

Earth System Dynamics ◽

10.5194/esd-7-167-2016 ◽

2016 ◽

Vol 7 (1) ◽

pp. 167-181 ◽

Cited By ~ 28

Author(s):

Yan Li ◽

Nathalie De Noblet-Ducoudré ◽

Edouard L. Davin ◽

Safa Motesharrei ◽

Ning Zeng ◽

...

Keyword(s):

Temperature Change ◽

Vegetation Change ◽

Spatial Scales ◽

Empirical Studies ◽

Temperature Response ◽

Shortwave Radiation ◽

Climate Conditions ◽

Tropical Regions ◽

Biophysical Changes ◽

Background Climate

Abstract. Previous modeling and empirical studies have shown that the biophysical impact of deforestation is to warm the tropics and cool the extratropics. In this study, we use an earth system model of intermediate complexity to investigate how deforestation on various spatial scales affects ground temperature, with an emphasis on the latitudinal temperature response and its underlying mechanisms. Results show that the latitudinal pattern of temperature response depends nonlinearly on the spatial extent of deforestation and the fraction of vegetation change. Compared with regional deforestation, temperature change in global deforestation is greatly amplified in temperate and boreal regions but is dampened in tropical regions. Incremental forest removal leads to increasingly larger cooling in temperate and boreal regions, while the temperature increase saturates in tropical regions. The latitudinal and spatial patterns of the temperature response are driven by two processes with competing temperature effects: decrease in absorbed shortwave radiation due to increased albedo and decrease in evapotranspiration. These changes in the surface energy balance reflect the importance of the background climate in modifying the deforestation impact. Shortwave radiation and precipitation have an intrinsic geographical distribution that constrains the effects of biophysical changes and therefore leads to temperature changes that are spatially varying. For example, wet (dry) climate favors larger (smaller) evapotranspiration change; thus, warming (cooling) is more likely to occur. Our analysis reveals that the latitudinal temperature change largely results from the climate conditions in which deforestation occurs and is less influenced by the magnitude of individual biophysical changes such as albedo, roughness, and evapotranspiration efficiency.

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Human–wildlife interactions and attitudes towards wildlife and wildlife reserves in Rajasthan, India

Oryx ◽

10.1017/s0030605317001028 ◽

2017 ◽

Vol 53 (3) ◽

pp. 523-531 ◽

Cited By ~ 4

Author(s):

Krithi K. Karanth ◽

Shivangi Jain ◽

Erika Weinthal

Keyword(s):

Comparative Study ◽

Crop Damage ◽

Mitigation Measures ◽

Level Of Education ◽

Livestock Predation ◽

History Of ◽

People’S Attitudes ◽

Years Of Schooling

AbstractHuman–wildlife interactions affect people's livelihoods, attitudes and tolerance towards wildlife and wildlife reserves. To investigate the effect of such interactions on people's attitudes and livelihoods, we surveyed 2,233 households located around four wildlife reserves in Rajasthan, India. We modelled respondents’ attitudes towards wildlife and wildlife reserves, experience of crop damage and livestock predation, and likelihood of mitigation use. Crop damage was reported by 76% of surveyed households, and livestock predation was reported by 15%. Seventy-one percent of households used at least one of eight mitigation measures against crop damage, and 19% used at least one of seven mitigation measures against livestock predation. We found that male respondents and households with a higher level of education valued wildlife and wildlife reserves more. Households at higher elevations and growing a greater variety of crops were more prone to crop damage. Proximity to reserves, elevation and larger livestock herds were associated with a higher incidence of livestock predation. Households in which a member had > 12 years of schooling and households with a history (6–10 years) of interaction with wildlife (i.e. crop damage) were most likely to use mitigation against crop damage. Households that owned more livestock and had a history of interaction (1–5 years and > 10 years) were most likely to mitigate against predation. Our comparative study provides insights into factors that influence interaction and tolerance, which could be used to improve existing management and prevention efforts in Rajasthan.

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Coexistence between wildlife and humans at fine spatial scales

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1210490109 ◽

2012 ◽

Vol 109 (38) ◽

pp. 15360-15365 ◽

Cited By ~ 156

Author(s):

Neil H. Carter ◽

Binoj K. Shrestha ◽

Jhamak B. Karki ◽

Narendra Man Babu Pradhan ◽

Jianguo Liu

Keyword(s):

Human Impacts ◽

Spatial Scales ◽

Activity Patterns ◽

Quantitative Information ◽

Global Challenge ◽

Human Needs ◽

Wildlife Species ◽

Chitwan National Park ◽

Low Levels ◽

Conservation Plans

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal’s Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger–human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge—meeting human needs while sustaining wildlife.

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Feedbacks, climate sensitivity and the limits of linear models

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2015.0146 ◽

2015 ◽

Vol 373 (2054) ◽

pp. 20150146 ◽

Cited By ~ 66

Author(s):

Reto Knutti ◽

Maria A. A. Rugenstein

Keyword(s):

Climate Sensitivity ◽

Linear Models ◽

Spatial Scales ◽

Earth System ◽

Global Response ◽

Feedback Parameter ◽

Specific Process ◽

Climate Research ◽

Formal Framework ◽

Educational Perspective

The term ‘feedback’ is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify and quantify parts of the complex Earth system. We combine new model results with a historical and educational perspective to organize existing ideas around feedbacks and linear models. Our results suggest that the state- and forcing-dependency of feedbacks are probably not appreciated enough, and not considered appropriately in many studies. A non-constant feedback parameter likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system.

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A matrix clustering method to explore patterns of land-cover transitions in satellite-derived maps of the Brazilian Amazon

Nonlinear Processes in Geophysics ◽

10.5194/npg-24-113-2017 ◽

2017 ◽

Vol 24 (1) ◽

pp. 113-123 ◽

Cited By ~ 7

Author(s):

Finn Müller-Hansen ◽

Manoel F. Cardoso ◽

Eloi L. Dalla-Nora ◽

Jonathan F. Donges ◽

Jobst Heitzig ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Transition Probabilities ◽

Brazilian Amazon ◽

Regional Patterns ◽

Local Climate ◽

Tropical Regions ◽

Land Cover Types ◽

Socioeconomic Drivers ◽

Land Cover Dynamics

Abstract. Changes in land-use systems in tropical regions, including deforestation, are a key challenge for global sustainability because of their huge impacts on green-house gas emissions, local climate and biodiversity. However, the dynamics of land-use and land-cover change in regions of frontier expansion such as the Brazilian Amazon are not yet well understood because of the complex interplay of ecological and socioeconomic drivers. In this paper, we combine Markov chain analysis and complex network methods to identify regimes of land-cover dynamics from land-cover maps (TerraClass) derived from high-resolution (30 m) satellite imagery. We estimate regional transition probabilities between different land-cover types and use clustering analysis and community detection algorithms on similarity networks to explore patterns of dominant land-cover transitions. We find that land-cover transition probabilities in the Brazilian Amazon are heterogeneous in space, and adjacent subregions tend to be assigned to the same clusters. When focusing on transitions from single land-cover types, we uncover patterns that reflect major regional differences in land-cover dynamics. Our method is able to summarize regional patterns and thus complements studies performed at the local scale.

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