Plant wax evidence for precipitation and vegetation change from a coastal sinkhole lake in the Bahamas spanning the last 3000 years

2020 ◽  
Vol 150 ◽  
pp. 104120
Author(s):  
Anne E. Tamalavage ◽  
Peter J. van Hengstum ◽  
Patrick Louchouarn ◽  
Patricia L. Fall ◽  
Jeffrey P. Donnelly ◽  
...  
Keyword(s):  
Vegetation Change ◽  
The Bahamas ◽  
Plant Wax ◽  
Sinkhole Lake

scholarly journals Neogene biomarker record of vegetation change in eastern Africa

2016 ◽  
Vol 113 (23) ◽  
pp. 6355-6363 ◽  
Author(s):  
Kevin T. Uno ◽  
Pratigya J. Polissar ◽  
Kevin E. Jackson ◽  
Peter B. deMenocal
Keyword(s):  
Vegetation Change ◽  
Tooth Enamel ◽  
Eastern Africa ◽  
Mammalian Evolution ◽  
Potential Influence ◽  
Coherent Signal ◽  
Sparse Vegetation ◽  
Grassland Ecosystems ◽  
Isotopic Analyses ◽  
Plant Wax

The evolution of C4grassland ecosystems in eastern Africa has been intensely studied because of the potential influence of vegetation on mammalian evolution, including that of our own lineage, hominins. Although a handful of sparse vegetation records exists from middle and early Miocene terrestrial fossil sites, there is no comprehensive record of vegetation through the Neogene. Here we present a vegetation record spanning the Neogene and Quaternary Periods that documents the appearance and subsequent expansion of C4grasslands in eastern Africa. Carbon isotope ratios from terrestrial plant wax biomarkers deposited in marine sediments indicate constant C3vegetation from ∼24 Ma to 10 Ma, when C4grasses first appeared. From this time forward, C4vegetation increases monotonically to present, with a coherent signal between marine core sites located in the Somali Basin and the Red Sea. The response of mammalian herbivores to the appearance of C4grasses at 10 Ma is immediate, as evidenced from existing records of mammalian diets from isotopic analyses of tooth enamel. The expansion of C4vegetation in eastern Africa is broadly mirrored by increasing proportions of C4-based foods in hominin diets, beginning at 3.8 Ma inAustralopithecusand, slightly later,Kenyanthropus. This continues into the late Pleistocene inParanthropus, whereasHomomaintains a flexible diet. The biomarker vegetation record suggests the increase in open, C4grassland ecosystems over the last 10 Ma may have operated as a selection pressure for traits and behaviors inHomosuch as bipedalism, flexible diets, and complex social structure.

An Exploratory Study on Augmentative and Alternative Communication Classroom Integration Training for Special Educators Who Work With Children With Complex Communication Needs in the Bahamas

2019 ◽  
Vol 4 (5) ◽  
pp. 991-1016
Author(s):  
Shameka Stanford ◽  
Ovetta Harris
Keyword(s):  
Augmentative And Alternative Communication ◽  
Special Educators ◽  
Communication Disorders ◽  
Alternative Communication ◽  
The Bahamas ◽  
Complex Communication Needs ◽  
English Speaking ◽  
Communication Needs ◽  
Classroom Integration ◽  
And Training

Purpose In 2011, the United Nations estimated there were between 180 and 220 million youth with disabilities living around the world, and 80% of them resided in developing countries. Over the last 6 years, this number has increased significantly, and now, over 1 million people live in the Caribbean with some form of disability such as communication disorders resulting in complex communication needs (CCN). Method This publication discusses the benefits of an exploratory, descriptive, nonexperimental study on augmentative and alternative communication (AAC) classroom integration training for 8 special educators in the Bahamas who work with children with CCN. Results The results of this study revealed that 100% of the participants reported the study to be effective in increasing their knowledge and skill in the area of implementing AAC into their classrooms, enhancing their ability to team teach and incorporate AAC opportunities for all students with CCN within their classrooms, and increasing their knowledge and skill overall in the areas of AAC and CCN. Conclusion The findings highlight an important area of potential professional development and training that can be replicated in other English-speaking Caribbean territories focused on AAC classroom integration training program for special educators who teach students with CCN.

Possible vegetation change in Mountain Altai under climate warming and compiling the prognosis maps

2000 ◽  
pp. 26-31
Author(s):  
E. I. Parfenova ◽  
N. M. Chebakova
Keyword(s):  
Climate Warming ◽  
Vegetation Change ◽  
Climate Change Scenario ◽  
Change Scenario ◽  
Forest Steppe ◽  
Vegetation Map ◽  
Climatic Indices ◽  
Bioclimatic Model ◽  
Open Woodland ◽  
Mountain Taiga

Global climate warming is expected to be a new factor influencing vegetation redistribution and productivity in the XXI century. In this paper possible vegetation change in Mountain Altai under global warming is evaluated. The attention is focused on forest vegetation being one of the most important natural resources for the regional economy. A bioclimatic model of correlation between vegetation and climate is used to predict vegetation change (Parfenova, Tchebakova 1998). In the model, a vegetation class — an altitudinal vegetation belt (mountain tundra, dark- coniferous subalpine open woodland, light-coniferous subgolets open woodland, dark-coniferous mountain taiga, light-coniferous mountain taiga, chern taiga, subtaiga and forest-steppe, mountain steppe) is predicted from a combination of July Temperature (JT) and Complex Moisture Index (CMI). Borders between vegetation classes are determined by certain values of these two climatic indices. Some bioclimatic regularities of vegetation distribution in Mountain Altai have been found: 1. Tundra is separated from taiga by the JT value of 8.5°C; 2. Dark- coniferous taiga is separated from light-coniferous taiga by the CMI value of 2.25; 3. Mountain steppe is separated from the forests by the CMI value of 4.0. 4. Within both dark-coniferous and light-coniferous taiga, vegetation classes are separated by the temperature factor. For the spatially model of vegetation distribution in Mountain Altai within the window 84 E — 90 E and 48 N — 52 N, the DEM (Digital Elevation Model) was used with a pixel of 1 km resolution. In a GIS Package IDRISI for Windows 2.0, climatic layers were developed based on DEM and multiple regressions relating climatic indices to physiography (elevation and latitude). Coupling the map of climatic indices with the authors' bioclimatic model resulted into a vegetation map for the region of interest. Visual comparison of the modelled vegetation map with the observed geobotanical map (Kuminova, 1960; Ogureeva, 1980) showed a good similarity between them. The new climatic indices map was developed under the climate change scenario with summer temperature increase 2°C and annual precipitation increase 20% (Menzhulin, 1998). For most mountains under such climate change scenario vegetation belts would rise 300—400 m on average. Under current climate, the dark-coniferous and light-coniferous mountain taiga forests dominate throughout Mountain Altai. The chern forests are the most productive and floristically rich and are also widely distributed. Under climate warming, light-coniferous mountain taiga may be expected to transform into subtaiga and forest-steppe and dark-coniferous taiga may be expected to transform partly into chern taiga. Other consequences of warming may happen such as the increase of forest productivity within the territories with sufficient rainfall and the increase of forest fire occurrence over territories with insufficient rainfall.

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