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

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TLDR
In this article, the authors 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.
Abstract
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 km 2 of closed canopy (≥ 40% forest cover) tropical dry forest in 2000 and 4,369,695 km 2 in 2020 with a gross loss of 561,719 km 2 (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.

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Phyto-ecological studies and distribution pattern of plant species and communities of Dhirkot, Azad Jammu and Kashmir, Pakistan.

TL;DR: In this article, the authors explored the plant species composition, distribution pattern, communities formation and their respective indicators under the influence of various environmental factors in the Dhirkot region, Azad Jammu and Kashmir.
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Phyto-ecological analysis of Phytolacca acinosa Roxb. assemblages in Kashmir Himalaya, India

TL;DR: In this paper , the authors analyzed the phytosociological and soil characteristics of Phytolacca acinosa communities and their correlation, and found that areas with highest floral diversity had high soil fertility while areas with low soil fertility possess lower diversity and need restoration.
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A geomorphometric model to determine topographic parameters controlling wildfires occurrence in tropical dry forests

TL;DR: In this article, the authors used a Generalized Linear Model (GLM) to study the occurrence of wildfires in a tropical dry forests (TDF) on a protected area at northwest Costa Rica.
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The Bioclimatic Change of the Agricultural and Natural Areas of the Adriatic Coastal Countries

TL;DR: In this article , a survey on De Martonne's bioclimatic categories' spatial distribution over the entire examined area and individual countries is conducted for the reference period (1981-2010) and for three more future time periods (2011-2040, 2041-2070, 2071-2100) under two emissions scenarios (ssp370/RCP7 and ssp585/RCP8.5).
References
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Journal ArticleDOI

Biodiversity hotspots for conservation priorities

TL;DR: A ‘silver bullet’ strategy on the part of conservation planners, focusing on ‘biodiversity hotspots’ where exceptional concentrations of endemic species are undergoing exceptional loss of habitat, is proposed.
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High-Resolution Global Maps of 21st-Century Forest Cover Change

TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
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WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas

TL;DR: In this paper, the authors created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km2), including monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970-2000, using data from between 9000 and 60,000 weather stations.
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Google Earth Engine: Planetary-scale geospatial analysis for everyone

TL;DR: Google Earth Engine is a cloud-based platform for planetary-scale geospatial analysis that brings Google's massive computational capabilities to bear on a variety of high-impact societal issues including deforestation, drought, disaster, disease, food security, water management, climate monitoring and environmental protection.
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