The increasing demand for tropical timber from natural forests has reduced the population sizes of native species such as Cedrela spp. because of their high economic value. To prevent the decline of population sizes of the species, all Cedrela species have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The study presents information about the modeled distribution of the genus Cedrela in Peru that aims to identify potential habitat distribution of the genus, its availability in areas protected by national service of protected areas, and highlighted some areas because of their conservation relevance and the potential need for restoration. We modeled the distribution of the genus Cedrela in Peru using 947 occurrence records that included 10 species (C. odorata, C. montana, C. fissilis, C. longipetiolulata, C. angustifolia, C. nebulosa, C. kuelapensis, C. saltensis, C. weberbaueri, and C. molinensis). We aim to identify areas environmentally suitable for the occurrence of Cedrela that are legally protected by the National Service of Protected Areas (PAs) and those that are ideal for research and restoration projects. We used various environmental variables (19 bioclimatic variables, 3 topographic factors, 9 edaphic factors, solar radiation, and relative humidity) and the maximum entropy model (MaxEnt) to predict the probability of occurrence. We observed that 6.7% (86,916.2 km2) of Peru presents a high distribution probability of occurrence of Cedrela, distributed in 17 departments, with 4.4% (10,171.03 km2) of the area protected by PAs mainly under the category of protection forests. Another 11.65% (21,345.16 km2) of distribution covers areas highly prone to degradation, distributed mainly in the departments Ucayali, Loreto, and Madre de Dios, and needs immediate attention for its protection and restoration. We believe that the study will contribute significantly to conserve Cedrela and other endangered species, as well as to promote the sustainable use and management of timber species as a whole.
A proper geomorphic study of a region can be useful in understanding past and present environmental circumstances and analyzing potential environmental risks. Careful analysis of morphodynamic processes and existing diagnostic landforms reveal several aspects about the origin, characteristics and possible pattern of morpho-climatic interactions on the landscape over temporal scale, which helps significantly in proper terrain evaluation from societal welfare and integrated management point of view, including environmental risk assessment and disaster management. This paper has made a thorough geomorphic investigation based on intensive fieldwork and multi-sourced remote sensing data to characterize the lateritic soil profile and landforms of the study area in respect to their morphology and Physico-chemical properties at the different sites of land degradation to understand the outcome of morphoclimatic interactions on the landscape over time, and to evaluate the severity of operation with pedo-geomorphic constraints in the lateritic environment for sustainable management purposes. It is found that the region is highly sensitive to weathering, mass movement and denudational activities, mainly caused by rainwater erosion which has resulted into varied landforms including well-developed rills and gullies, lateritic ridges, isolated residual hills etc and generated a unique identity to this part of the lateritic region. The study also suggested a model for the development of geomorphic landforms in a lateritic terrain based on past and present morphoclimatic interactions, nature of physiography, lithology, soil characteristics and other biotic and abiotic elements. The region is also found to be a subject to moderate to severe land degradation due to the active geomorphic processes in operation in tropical regions and inherently poor physical and chemical formation of the existing soil profile and radical conversion of land uses as observed at cadastral level leading towards irresistible desertification. Annual topsoil loss amount has been calculated using the Universal Soil Loss Equation method. Three sample Mouzas namely Ballavpur, Shyambati and Chawpahari jungle have been assessed to be having 36.98%, 71.42% and 61.73% of degraded land in respect to their total village area. Various conservative measures like stabilization of gully heads and beds through reforestation and afforestation with cutting earth plug, brush fills and check dams; improvement of the irrigation network, suitable dryland farming etc. have been recommended to arrest the desertification process.
In the work, a new naphthalimide‐linked poly(aryl ether) gelator 1 has been designed and synthesized. It forms gels in various organic and aquous organic solvents and exhibits aggregation‐induced enhancement of emission (AIEE) through the tuning of gelling solvent. Gels are of good viscoelastic nature showing higher magnitude of G′ over G′′ and exhibit fibrous morphology. Among the different gels, DMSO : H2O (7 : 3, v/v) gel with considerable rigidity selectively detects CN− over the other anions via deprotonation mechanism and involves a gel‐to‐sol colour change. In addition, n‐butanol : H2O (9 : 2, v/v) gel shows the same property. The water in gelling medium has the pertinent role in anion recognition selectivity, aggregation and AIEE. While in solution F− interferes in CN− sensing, there is no interference of it in the gel state. Besides sensing, n‐butanol gel of 1 removes the toxic cationic dyes from wastewater to the extent of 98–99 % in phase selective manner.
An unprecedented number of wildfire events during 2019 throughout the Brazilian Amazon caught global attention, due to their massive extent and the associated loss in the Amazonian forest—an ecosystem on which the whole world depends. Such devastating wildfires in the Amazon has strongly hampered the global carbon cycle and significantly reduced forest productivity. In this study, we have quantified such loss of forest productivity in terms of gross primary productivity (GPP), applying a comparative approach using Google Earth Engine. A total of 12 wildfire spots have been identified based on the fire’s extension over the Brazilian Amazon, and we quantified the loss in productivity between 2018 and 2019. The Moderate Resolution Imaging Spectroradiometer (MODIS) GPP and MODIS burned area satellite imageries, with a revisit time of 8 days and 30 days, respectively, have been used for this study. We have observed that compared to 2018, the number of wildfire events increased during 2019. But such wildfire events did not hamper the natural annual trend of GPP of the Amazonian ecosystem. However, a significant drop in forest productivity in terms of GPP has been observed. Among all 11 observational sites were recorded with GPP loss, ranging from −18.88 gC m−2 yr−1 to −120.11 gC m−2 yr−1, except site number 3. Such drastic loss in GPP indicates that during 2019 fire events, all of these sites acted as carbon sources rather than carbon sink sites, which may hamper the global carbon cycle and terrestrial CO2 fluxes. Therefore, it is assumed that these findings will also fit for the other Amazonian wildfire sites, as well as for the tropical forest ecosystem as a whole. We hope this study will provide a significant contribution to global carbon cycle research, terrestrial ecosystem studies, sustainable forest management, and climate change in contemporary environmental sciences.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.