Space-time analysis of vegetation trends and drought occurrence in domain area of tropical forest

Branco, Elvis Ricardo Figueira; Santos, Alexandre Rosa dos; Pezzopane, José Eduardo Macedo; Santos, Áureo Banhos dos; Alexandre, Rodrigo Sobreira; Bernardes, Vanessa Pimentel; Silva, Rosane Gomes da; Souza, Kaíse Barbosa de; Moura, Marks Melo

doi:10.1016/j.jenvman.2019.05.097

Cited by 26 publications

(9 citation statements)

References 83 publications

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“…However, if that change is not persistent (i.e., sustained), a more in-depth investigation would be suggested to make an appropriate decision, especially in the sense of long-term sustainable development. Besides, analysing the vegetation trend within each type of LULC change, which has not been considered in the previous studies (Branco et al, 2019;Tran, Tran, Myint, Huang, et al, 2019;Zhang et al, 2015), was taken into account in our research. This kind of analysis demonstrates more details in the vegetation trend pattern and examines which types of change would likely continue in the future.…”

Section: The Advantages Of Integrating Linear Regression Analysis and The Hurst Exponent For Vegetation Change Analysismentioning

confidence: 99%

“…Tong et al, 2018;Wanyama et al, 2020). This approach holds substantial promise for investigating the long-term dynamics of vegetation fluctuations (Branco et al, 2019;Wardlow, Egbert, & Kastens, 2007). Several time-series analysis tools have been developed [e.g., the national forest trend (Lehmann, Wallace, Caccetta, Furby, & Zdunic, 2013); the recurrent neural network (Reddy & Prasad, 2018)] to assess and monitor spatiotemporal changes in vegetation conditions (Chen et al, 2014).…”

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confidence: 99%

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Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Tran

Nguyen

et al. 2021

Land Degrad Dev

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Spatiotemporal analysis and monitoring of vegetation help us investigate ecological health and guide better forest conservation and land management practices for sustainable development. This paper proposes the use of spatial analysis approaches (i.e., ordinary least squares [OLS] and the Hurst exponent) combined with time-series analysis using enhanced vegetation index (EVI) data, derived from LANDSAT via the Google Earth Engine, to estimate the trends and sustainability of vegetation dynamics in the Tra Vinh Province in the Mekong River Delta. We also assessed the EVI changes connected to land change issues to examine the influence of land use conversion on vegetation dynamics. Results show that a large portion of the study area was covered by abundant vegetation (over 50% of the total area), and the increased EVI area was about 5.5-times greater than the area of EVI reduction. Additionally, vegetation sustainability was being seriously compromised (e.g., a decrease in the total area of 8,275 ha) due to several land conversion drivers such as shrimp farming, urbanisation, and industrialisation. Furthermore, results obtained from this research provide insight into the spatiotemporal dynamics of vegetation coverage and reveal the consistency of future vegetation trends. Moreover, the study also quantitatively assessed the positive impacts of Buddhist doctrines on reducing the negative trend of vegetation change in the study area. These findings can lay the ground to formulate sustainable land and environmental plans that meet the 11th, 13th and 15th Sustainable Development Goals (SDGs) (i.e., the sustainable cities and communities, the climate actions, and the life on land). Besides, the analytical procedure adopted in this study can also be applicable to any other coastal areas that require the accurate assessment of vegetation status over time.

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Section: The Advantages Of Integrating Linear Regression Analysis and The Hurst Exponent For Vegetation Change Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Tran

Nguyen

et al. 2021

Land Degrad Dev

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“…For productivity, we estimated the mean and seasonality as the CV from the monthly mean values with the vegetation index of enhanced vegetation index (EVI), which were compiled from the 16‐day products of the Terra Moderate Resolution Imaging Spectroradiometer at 250 m from 2000 to 2015 (Didan, 2015). EVI has been broadly used to estimate ecosystem productivity (Huete et al., 2002) and better detects seasonality in dense tropical forests than the normalized difference vegetation index (NDVI; Figueira Branco et al., 2019; Sarmah et al., 2018).…”

Section: Methodsmentioning

confidence: 99%

“…Palaeoenvironmental changes in forest cover were measured as differences in land-cover rank be- (Didan, 2015). EVI has been broadly used to estimate ecosystem productivity (Huete et al, 2002) and better detects seasonality in dense tropical forests than the normalized difference vegetation index (NDVI;Figueira Branco et al, 2019;Sarmah et al, 2018).…”

Section: Evolutionary and Environmental Predictorsmentioning

confidence: 99%

Evolutionary history and environmental variability structure contemporary tropical vertebrate communities

Hsieh,

Gorczynski,

Bitariho

et al. 2024

Global Ecol Biogeogr

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AimTropical regions harbour over half of the world's mammals and birds, but how their communities have assembled over evolutionary timescales remains unclear. To compare eco‐evolutionary assembly processes between tropical mammals and birds, we tested how hypotheses concerning niche conservatism, environmental stability, environmental heterogeneity and time‐for‐speciation relate to tropical vertebrate community phylogenetic and functional structure.LocationTropical rainforests worldwide.Time periodPresent.Major taxa studiedGround‐dwelling and ground‐visiting mammals and birds.MethodsWe used in situ observations of species identified from systematic camera trap sampling as realized communities from 15 protected tropical rainforests in four tropical regions worldwide. We quantified standardized phylogenetic and functional structure for each community and estimated the multi‐trait phylogenetic signal (PS) in ecological strategies for the four regional species pools of mammals and birds. Using linear regression models, we test three non‐mutually exclusive hypotheses by comparing the relative importance of colonization time, palaeo‐environmental changes in temperature and land cover since 3.3 Mya, contemporary seasonality in temperature and productivity and environmental heterogeneity for predicting community phylogenetic and functional structure.ResultsPhylogenetic and functional structure showed non‐significant yet varying tendencies towards clustering or dispersion in all communities. Mammals had stronger multi‐trait PS in ecological strategies than birds (mean PS: mammal = 0.62, bird = 0.43). Distinct dominant processes were identified for mammal and bird communities. For mammals, colonization time and elevation range significantly predicted phylogenetic clustering and functional dispersion tendencies respectively. For birds, elevation range and contemporary temperature seasonality significantly predicted phylogenetic and functional clustering tendencies, respectively, while habitat diversity significantly predicted functional dispersion tendencies.Main conclusionsOur results reveal different eco‐evolutionary assembly processes structuring contemporary tropical mammal and bird communities over evolutionary timescales that have shaped tropical diversity. Our study identified marked differences among taxonomic groups in the relative importance of historical colonization and sensitivity to environmental change.

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“…Considering this, we selected an indicator to represent an aspect of the land surface condition. We used the Normalized Difference Vegetation Index (NDVI), which presents a strong correlation between the indicators in evaluating land surfaces and the vegetation cover in plant biomass evaluation (Figueira Branco et al., 2019; Sun et al., 2021; Veloso, Ferreira, Ferreira Júnior, & Barbosa da Silva, 2020). The Modified Soil‐Adjusted Vegetation Index (MSAVI) is a vegetation index used to characterize the high proportions of bare soil or the low concentration of photosynthetic pigments in plants caused by long dry periods which characterize landscape patterns, and the albedo of land surface is a measure of the solar radiation reflected from an object or target to the amount of incident energy, to characterize land surface micrometeorology (de Souza & Oyama, 2011; Jesus, Barros de Souza, Souza de Oliveira, & Gama, 2019; Sá, Cunha, Taura, & Drumond, 2015; Vendruscolo et al., 2020).…”

Section: Methodsmentioning

confidence: 99%

Temporal analysis of desertification vulnerability in Northeast Brazil using Google Earth Engine

Moura

Walter

Lins

et al. 2022

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Intensive agricultural production has negative environmental impacts, increasing predisposition to desertification in areas with inadequate soil management. To evaluate the effects of agriculture, we aimed to perform a temporal analysis and analyze the development of desertification in Northeast Brazil. Initially, the region was separated into four climatic zones, grouping the locations with similar characteristics of air temperature and rainfall. In the analyses, images of the northeast region acquired from the Landsat 5 (1989, 1999, and 2009) and Landsat 8 (2019) satellites were processed using the Google Earth Engine platform. The periods were separated into dry and rainy periods, according to the climatic zones. The evaluation of vegetation index, characterization of the remaining vegetation cover, landscape pattern, and meteorological conditions were performed, respectively, through the Normalized Difference Vegetation Index, Modified Soil‐Adjusted Vegetation Index, and albedo of the terrestrial surface. The desertification index showed an increase in susceptible areas when comparing the interval from 1989 to 2019. In general, our results showed that there is less predisposition for desertification to occur during the rainy season. Also, when the results of our study were compared to official data released by the National Program of Action to Combat Desertification and Mitigate the Effects of Drought, there was disagreement regarding the classification of areas.

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Space-time analysis of vegetation trends and drought occurrence in domain area of tropical forest

Cited by 26 publications

References 83 publications

Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Evolutionary history and environmental variability structure contemporary tropical vertebrate communities

Temporal analysis of desertification vulnerability in Northeast Brazil using Google Earth Engine

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