scholarly journals Canopy Temperature Differences between Liana-Infested and Non-Liana Infested Areas in a Neotropical Dry Forest

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 890 ◽  
Author(s):  
Xu Yuan ◽  
Kati Laakso ◽  
Philip Marzahn ◽  
G. Arturo Sanchez-Azofeifa
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Forest Disturbance ◽  
Statistical Tests ◽  
Tropical Dry Forest ◽  
Thermal Infrared ◽  
Dry Forest ◽  
Woody Vines ◽  
Forest Gaps ◽  
Higher Temperature

Lianas (woody vines) are important non-structural elements of all tropical forests. Current field observations across the Neotropics suggest that liana abundance is rising as a result of forest disturbance, increasing atmospheric CO2, and more frequent extreme climate events. Lianas can cause mechanical stress on their host trees, thus increasing mortality, in addition to potentially reducing carbon storage capacity. Furthermore, previous studies have suggested that liana leaves have an overall higher temperature than tree leaves, which presents the question of whether these differences can be extended from the leaf to the canopy. In this context, the ability to detect these temperature differences from a remote sensing platform has so far not been put into test, despite the importance such knowledge can have in large-scale land surface modeling studies and liana extent monitoring. To partially fill this knowledge gap, we acquired thermal infrared data using an unmanned aerial vehicle (UAV) system over an intermediate tropical dry forest in Costa Rica, Central America. Classification results from a previous study in the same area were used to subset the thermal infrared images into liana-infested areas, non-liana infested areas, and forest gaps. The temperature differences between these three image components were then investigated using the Welch and Games–Howell post-hoc statistical tests. Our results suggest that liana-infested areas have, on average, a statistically significant higher temperature than non-liana infested areas. Shadowed forest gaps, used as reference, have a cooler temperature than forest canopies. Our findings on the temperature differences between liana-infested and non-liana infested areas support previous leaf-level observations and open the door to the use of new approaches for the classification and modeling of liana infestation in tropical ecosystems.

Revealing the spatial pattern of subsurface soil salinity over the Argentinean Dry Chaco

2021 ◽  
Author(s):  
Michiel Maertens ◽  
Veerle Vanacker ◽  
Gabriëlle De Lannoy ◽  
Frederike Vincent ◽  
Raul Giménez ◽  
...  
Keyword(s):  
Soil Salinity ◽  
Land Surface ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Regional Scale ◽  
Shallow Groundwater ◽  
Soil Salinization ◽  
Dry Forest ◽  
Surface Model ◽  
Subsurface Soil

<p>The South-American Dry Chaco is a unique ecoregion as it is one of the largest sedimentary plains in the world hosting the planet’s largest dry forest. The 787.000 km² region covers parts of Argentina, Paraguay, and Bolivia and is characterized by a negative climatic water balance as a consequence of limited rainfall inputs (800 mm/year) and high temperatures (21°C). In combination with the region’s extreme flat topography (slopes < 0.1%) and shallow groundwater tables, saline soils are expected in substantial parts of the region. In addition, it is expected that large-scale deforestation processes disrupt the hydrological cycle resulting in rising groundwater tables and further increase the risk for soil salinization.</p><p>In this study, we identified the regional-scale patterns of subsurface soil salinity in the Dry Chaco.  Field data were obtained during a two-month field campaign in the dry season of 2019. A total of 492 surface- and 142 subsurface-samples were collected along East-West transects to determine soil electric conductivity, pH, bulk density and humidity. Spatial regression techniques were used to reveal the topographic and ecohydrological variables that are associated with subsurface soil salinity over the Dry Chaco. The hydrological information was obtained from a state-of-the-art land surface model with an improved set of satellite-derived vegetation and land cover parameters.</p><p>In the presentation, we will present a subsurface soil salinity map for a part of the Argentinean Dry Chaco and provide relevant insights into the driving mechanisms behind it.</p>

Effect of forest disturbance on ant (Hymenoptera: Formicidae) diversity in a Mexican tropical dry forest canopy

2020 ◽  
Author(s):  
Jaime Hernández‐Flores ◽  
Alejandro Flores‐Palacios ◽  
Miguel Vásquez‐Bolaños ◽  
Víctor Hugo Toledo‐Hernández ◽  
Ofelia Sotelo‐Caro ◽  
...  
Keyword(s):  
Forest Canopy ◽  
Forest Disturbance ◽  
Tropical Dry Forest ◽  
Dry Forest

scholarly journals Quantifying Changes on Forest Succession in a Dry Tropical Forest Using Angular-Hyperspectral Remote Sensing

2018 ◽  
Vol 10 (12) ◽  
pp. 1865 ◽  
Author(s):  
Virginia Garcia Millan ◽  
Arturo Sanchez-Azofeifa
Keyword(s):  
Large Scale ◽  
Forest Succession ◽  
Early Stage ◽  
Tropical Dry Forest ◽  
Intermediate Stage ◽  
Hyperspectral Data ◽  
Dry Forest ◽  
Support Vector ◽  
Spectral Angle Mapper ◽  
Different Levels

The tropical dry forest (TDF) is one the most threatened ecosystems in South America, existing on a landscape with different levels of ecological succession. Among satellites dedicated to Earth observation and monitoring ecosystem succession, CHRIS/PROBA is the only satellite that presents quasi-simultaneous multi-angular pointing and hyperspectral imaging. These two characteristics permit the study of structural and compositional differences of TDFs with different levels of succession. In this paper, we use 2008 and 2014 CHRIS/PROBA images from a TDF in Minas Gerais, Brazil to study ecosystem succession after abandonment. Using a −55° angle of observation; several classifiers including spectral angle mapper (SAM), support vector machine (SVM), and decision trees (DT) were used to test how well they discriminate between different successional stages. Our findings suggest that the SAM is the most appropriate method to classify TDFs as a function of succession (accuracies ~80 for % for late stage, ~85% for the intermediate stage, ~70% for early stage, and ~50% for other classes). Although CHRIS/PROBA cannot be used for large-scale/long-term monitoring of tropical forests because of its experimental nature; our results support the potential of using multi-angle hyperspectral data to characterize the structure and composition of TDFs in the near future.

scholarly journals How BFAST Trend and Seasonal Model Components Affect Disturbance Detection in Tropical Dry Forest and Temperate Forest

2021 ◽  
Vol 13 (11) ◽  
pp. 2033
Author(s):  
Yan Gao ◽  
Jonathan V. Solórzano ◽  
Alexander Quevedo ◽  
Jaime Octavio Loya-Carrillo
Keyword(s):  
Time Series ◽  
Forest Disturbance ◽  
Accuracy Assessment ◽  
Tropical Dry Forest ◽  
Dry Forest ◽  
Historical Period ◽  
Forest Types ◽  
Seasonal Model ◽  
Model Components ◽  
Disturbance Detection

Time series analysis has gained popularity in forest disturbance monitoring thanks to the availability of satellite and airborne remote sensing images and the development of different time series methods for change detection. Previous research has focused on time series data noise reduction, the magnitude of breakpoints, and accuracy assessment; however, few have looked in detail at how the trend and seasonal model components contribute to disturbance detection in different forest types. Here, we use Landsat time series images spanning 1994–2018 to map forest disturbance in a western Pacific area of Mexico, where both temperate and tropical dry forests have been subject to severe deforestation and forest degradation processes. Since these two forest types have distinct seasonal characteristics, we investigate how trend and seasonal model components, such as the goodness-of-fit (R2), magnitude of change, amplitude, and model length in a stable historical period, affect forest disturbance detection. We applied the Breaks For Additive Season and Trend Monitor (BFAST) algorithm and after accuracy assessment by stratified random sample points, and we obtained 68% and 86% of user accuracy and 75.6% and 86% of producer’s accuracy in disturbance detection, in tropical dry forests and temperate forests, respectively. We extracted the noncorrelated trend and seasonal model components R2, magnitude, amplitude, length of the stable historical period, and percentage of pixels with NA and tested their effects on disturbance detection employing forest-type specific logistic regression. Our results showed that, for all forests combined, the amplitude and stable historical period length contributed to disturbance detection. While for tropical dry forest alone, amplitude was the main predictor, and for the temperate forest alone, the stable historical period length contributed most to the prediction, although it was not statistically significant. These findings provide insights for improving the results of forest disturbance detection in different forest types.

scholarly journals Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252063
Author(s):  
Jonathan Pando Ocón ◽  
Thomas Ibanez ◽  
Janet Franklin ◽  
Stephanie Pau ◽  
Gunnar Keppel ◽  
...  
Keyword(s):  
Land Surface ◽  
Forest Cover ◽  
Tropical Dry Forest ◽  
Aridity Index ◽  
Dry Forest ◽  
Data Sets ◽  
Climatic Data ◽  
Data Set ◽  
Field Plots ◽  
Forest Biome

There is a debate concerning the definition and extent of tropical dry forest biome and vegetation type at a global spatial scale. We identify the potential extent of the tropical dry forest biome based on bioclimatic definitions and climatic data sets to improve global estimates of distribution, cover, and change. We compared four bioclimatic definitions of the tropical dry forest biome–Murphy and Lugo, Food and Agriculture Organization (FAO), DryFlor, aridity index–using two climatic data sets: WorldClim and Climatologies at High-resolution for the Earth’s Land Surface Areas (CHELSA). We then compared each of the eight unique combinations of bioclimatic definitions and climatic data sets using 540 field plots identified as tropical dry forest from a literature search and evaluated the accuracy of World Wildlife Fund tropical and subtropical dry broadleaf forest ecoregions. We used the definition and climate data that most closely matched field data to calculate forest cover in 2000 and change from 2001 to 2020. Globally, there was low agreement (< 58%) between bioclimatic definitions and WWF ecoregions and only 40% of field plots fell within these ecoregions. FAO using CHELSA had the highest agreement with field plots (81%) and was not correlated with the biome extent. Using the FAO definition with CHELSA climatic data set, we estimate 4,931,414 km2 of closed canopy (≥ 40% forest cover) tropical dry forest in 2000 and 4,369,695 km2 in 2020 with a gross loss of 561,719 km2 (11.4%) from 2001 to 2020. Tropical dry forest biome extent varies significantly based on bioclimatic definition used, with nearly half of all tropical dry forest vegetation missed when using ecoregion boundaries alone, especially in Africa. Using site-specific field validation, we find that the FAO definition using CHELSA provides an accurate, standard, and repeatable way to assess tropical dry forest cover and change at a global scale.

scholarly journals Data Validation and Case Studies using the TET-1 Thermal Infrared Satellite System

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1177-1182 ◽  
Author(s):  
C. Fischer ◽  
D. Klein ◽  
G. Kerr ◽  
E. Stein ◽  
E. Lorenz ◽  
...  
Keyword(s):  
Land Surface ◽  
Spectral Characteristics ◽  
Thermal Infrared ◽  
Satellite System ◽  
Radiative Power ◽  
Spectral Algorithm ◽  
Higher Temperature ◽  
Linear Nature ◽  
Fire Radiative Power ◽  
Infrared Channel

Based on the DLR satellite system BIRD, launched and operated in the early 2000, the TET-1 satellite has been launched in 2012 as part of the FireBird satellite constellation. The constellation will consist of two satellites, the second one to be launched in the first half of 2016. Acquired imagery is processed and archived by DLR and will be publicly available. For this purpose, a processing chain has been implemented converting raw data (level 0 product) to geo-annotated at-sensor radiance (level 1b). Further data products can be derived, e.g. information on brightness temperature, fire radiative power, and surface emissivity. Other processing levels, such as atmospherically corrected reflectance, could also be produced. The sensitivity of a Thermal Infrared (TIR) sensor system depends on its spectral characteristics and its spatial resolution. Various methods for high temperature event (HTE) detection and quantification have been developed, which can be categorized into single- and multi-band algorithms. While single band methods rely on the robust demarcation of background pixels and higher temperature pixels, considered as being anomalous, the TET-1 system facilitates the application of the widely used bi-spectral algorithm approach introduced by Dozier (1981), using the mid-infrared and longwave-infrared channel. This approach takes advantage of the non-linear nature of the Planck’s curves to calculate temperatures and the HTE area on a sub-pixel basis. TIR remote sensing can make a significant contribution to the detection and, partly, the monitoring of land surface temperature (LST), HTE and of parameters describing the surface energy balance for specific areas.

The impact of Cyclone Fanele on sifaka body condition and reproduction in the tropical dry forest of western Madagascar

2011 ◽  
Vol 27 (4) ◽  
pp. 429-432 ◽  
Author(s):  
R. J. Lewis ◽  
F. Rakotondranaivo
Keyword(s):  
Evolutionary History ◽  
Large Scale ◽  
Global Climate ◽  
Tropical Dry Forest ◽  
Dry Forest ◽  
Natural Disturbances ◽  
Specific Effects ◽  
Before And After ◽  
History Of ◽  
The Impact

Cyclones have been suggested to play a major role in the evolutionary history of the flora and fauna of Madagascar (Wright 1999). In spite of the proposed significance of cyclonic activity, very little is known about the specific effects of cyclones on Malagasy ecosystems (Birkinshaw & Randrianjanahary 2007). Understanding the effects of these severe natural disturbances requires comparing data collected both before and after the event. Because cyclones are stochastic, researching the influence of cyclones on Madagascar's biodiversity is difficult and opportunities to study their impact on forests are rare. Nevertheless, studies of the impact of cyclones on Malagasy biota are imperative because models of global climate patterns predict that large-scale tropical disturbances will increase in frequency and intensity in the future (Metcalfe et al. 2008).

scholarly journals Using large‐scale tropical dry forest restoration to test successional theory

2020 ◽  
Vol 30 (6) ◽  
Author(s):  
Leland K. Werden ◽  
Erick Calderón‐Morales ◽  
Pedro Alvarado J. ◽  
Milena Gutiérrez L. ◽  
Derek A. Nedveck ◽  
...  
Keyword(s):  
Forest Restoration ◽  
Large Scale ◽  
Tropical Dry Forest ◽  
Dry Forest ◽  
Dry Forest Restoration

Land Use Change and Commodity Frontiers

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel M. Cáceres ◽  
Esteban Tapella ◽  
Diego A. Cabrol ◽  
Lucrecia Estigarribia
Keyword(s):  
Large Scale ◽  
Field Work ◽  
Dry Forest ◽  
Social Actors ◽  
Goods And Services ◽  
Fast Pace ◽  
Forest Use ◽  
The Government ◽  
Social Environmental ◽  
Management Recommendations

Argentina is experiencing an expansion of soya and maize cultivation that is pushing the agricultural frontier over areas formerly occupied by native Chaco forest. Subsistance farmers use this dry forest to raise goats and cattle and to obtain a broad range of goods and services. Thus, two very different and non-compatible land uses are in dispute. On the one hand subsistance farmers fostering an extensive and diversified forest use, on the other hand, large-scale producers who need to clear out the forest to sow annual crops in order to appropriate soil fertility. First, the paper looks at how these social actors perceive Chaco forest, what their interests are, and what kind of values they attach to it. Second, we analyze the social-environmental conflicts that arise among actors in order to appropriate forest’s benefits. Special attention is paid to the role played by the government in relation to: (a) how does it respond to the demands of the different sectors; and (b) how it deals with the management recommendations produced by scientists carrying out social and ecological research. To put these ideas at test we focus on a case study located in Western Córdoba (Argentina), where industrial agriculture is expanding at a fast pace, and where social actors’ interests are generating a series of disputes and conflicts. Drawing upon field work, the paper shows how power alliances between economic and political powers, use the institutional framework of the State in their own benefit, disregarding wider environmental and social costs. 

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