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Micromammal Paleoecology: Past and Present Relationships Between African Small Mammals and Their Habitats

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Micromammal Paleoecology: Past and Present Relationships Between African Small Mammals and Their Habitats Micromammal Paleoecology: Past and present relationships between African small mammals and their habitats A Dissertation Presented by Denn´eNakima Reed to The Graduate School in Partial fulfillment of the Requirements for the Degree of Doctor of Philosophy in Anthropology Stony Brook University December 2003 Contents 1 Background and Introduction 1 1.1 Background ............................... 2 1.2 Overview of Materials and Methods . 8 1.2.1 Materials ............................ 8 1.2.2 Data representation . 9 1.2.3 Tests of independence and association . 12 1.2.4 Correlations........................... 13 1.2.5 Similarity Coefficients . 14 1.2.6 RunsTest ............................ 15 1.2.7 Correspondence analysis . 15 1.2.8 Statistical Software . 16 1.2.9 Data independence . 16 1.2.10 Samplesize ........................... 18 1.3 ChapterSummaries........................... 19 2 Study Area 22 2.1 Introduction............................... 22 2.1.1 GIS and remote sensing fundamentals . 25 2.1.1.1 Raster versus vector data. 26 2.1.1.2 Map projections and geographical coordinate systems 27 2.1.1.3 Global positioning systems . 28 2.1.2 Image classification . 29 2.2 Data Sources and Methods . 30 2.2.1 Hydrology............................ 30 2.2.2 Elevation and topography . 31 2.2.3 Precipitation . 31 iv CONTENTS v 2.2.4 Soils ............................... 34 2.2.5 Land cover classification . 36 2.2.5.1 Image preparation . 38 2.2.5.2 DRSRS land cover classification system . 40 2.2.5.3 Ground truth data . 43 2.2.5.4 Additional reference data sources . 46 2.2.5.5 Image texture . 46 2.2.5.6 Image stratification and signature development . 48 2.2.5.7 Fuzzy classification and fuzzy convolution filtering 49 2.2.6 Thresholding .......................... 50 2.3 Classification Results L7 Path 169 Row 61 and 62 . 51 2.4 General Vegetation Patterns . 56 2.4.1 Climate ............................. 56 2.4.2 Topography and soils . 59 2.4.3 Disturbance ........................... 61 2.5 Vegetation Patterns at the Individual Roosts . 64 2.5.1 Roost 24 – Gol Kopjes . 64 2.5.2 Roost 3 – Wandamu River Kopjes . 66 2.5.3 Roost 13 - Turner Spring Kopjes . 66 2.5.4 Roost 18 – Ngare Nanyuki . 67 2.5.5 Roost 4 – SRI-Oloserian . 67 2.5.6 Roost12–Seronera ...................... 68 2.5.7 Roost 23 – Pipeline Kopje . 68 2.5.8 Roost 44 – Kogatende . 69 2.6 Summary and Conclusions . 70 3 Fauna 72 3.1 Introduction............................... 72 3.2 Methods................................. 74 3.2.1 Identification . 77 3.2.2 Faunal Database . 80 3.2.3 Quantification and Aggregation . 80 3.3 Results.................................. 84 3.4 Discussion . 90 3.4.1 Autecological profiles of Serengeti micromammals . 91 CONTENTS vi 3.4.2 Micromammal niche models . 106 3.4.3 Comparison with previous Serengeti small mammal studies . 110 3.4.4 Patterns of faunal association between roosts . 114 3.4.5 Correlations of sample size and faunal abundances . 121 3.5 Conclusions ...............................122 4 Taphonomy 125 4.1 Introduction............................... 125 4.2 Methods.................................128 4.3 Results..................................129 4.3.1 RoostingType ......................... 129 4.3.2 Prey Preference . 129 4.4 Review of the predators . 132 4.4.1 Barn Owls, Tyto alba affinis Blyth ..............132 4.4.2 EagleOwls ...........................144 4.5 Taphonomic Implications . 146 4.5.1 Taphonomic mode and site formation . 146 4.5.2 Trophic overlap and comparative taphonomy . 148 4.6 Conclusions ...............................150 5 Paleoenvironmental Analysis 152 5.1 Introduction............................... 152 5.1.1 Fundamental Assumptions . 153 5.2 Materials and Methods . 155 5.3 Correlation Analysis . 159 5.4 Niche representation and indicator species . 166 5.4.1 Taxonomic Ratios . 170 5.4.2 Taxonomic Habitat Index . 171 5.4.3 Species diversity . 179 5.4.3.1 Defining species diversity . 179 5.4.3.2 Sample size effects on species diversity . 179 5.4.3.3 Rarefaction . 181 5.4.4 Patterns of species richness between Serengeti taphocoenoses 181 5.4.4.1 Species abundance models . 183 5.4.4.2 Patterns in species abundance and diversity . 184 CONTENTS vii 5.4.4.3 Patterns of species diversity in the Serengeti as- semblages . 188 5.4.4.4 Conclusions . 192 5.5 Olduvai Paleoenvironments . 192 5.5.1 Timing of environmental change. 195 5.5.2 Paleoenvironment . 196 5.6 Conclusions ...............................198 6 Summary and Conclusions 199 A Signature Listings Training Data 229 A.1 Signature Zonation . 229 B Mathematical Topics 233 B.1 Nonparametric correlation statistics . 233 B.1.1 Spearman’s rank correlation, ρ .................233 B.1.2 Kendall’s coefficient of rank correlation, τ ..........234 B.1.3 Kendall’s coefficient of concordance, W . 235 B.1.4 Gamma Distributions . 235 B.1.5 The Chi-square, χ2, Distribution . 236 B.2 RunsTest ................................237 B.3 Raster Imagery and Basic Definitions . 238 B.4 Classification Theory . 238 B.5 Distance Measures . 238 B.6 Maximum-Likelihood Classification . 240 B.7 Fuzzy Classification . 241 List of Figures 1.1 Overview of the processes resulting in taphonomic and fossil as- semblages of micromammals. The biocoenosis is influenced both by ecological factors shaping local niches and historical contingencies influencing what lineage are present to exploit the niches. Often owls, or some other predator, sample the biocoenosis and accumu- late prey remains at a site such as a roost or latrine (curved arrow). Repetitive use of these sites results in a taphocoenosis or death as- semblage. This may become buried and eventually form a fossil assemblage which is recovered and analyzed. Alterations to the as- semblage may accrue along the way and some examples are listed below the boxes representing the different stages. 4 1.2 Plots of the chi-square probability density functions for several val- ues of ν= d.f. When ν is small the curve is uniformly decreasing with greater chi-square values (x axis). Greater values of ν reveal a unimodalshape. ............................ 13 2.1 Map of the Serengeti National Park and adjacent protected areas, overlying a shaded area depicting the extent of the Serengeti Ecosys- tem. The ecosystem is defined as the area covered by the wildebeest (Connochaetes taurinus) during their annual migrations. Map inset shows the location of the study area within the East African subregion. 23 viii LIST OF FIGURES ix 2.2 Regional hydrology and river density. Dark blue lines indicate major rivers, these are usually flowing year-round. Light blue lines indicate seasonal rivers and drainages. A river density image, derived from they hydrology coverage is plotted in the lower right. White spaces in both maps indicate the absence of rivers altogether. From both it is clear that few rivers dissect the plains in the southeastern portion ofSerengeti................................ 32 2.3 Regional elevation contours, digital elevation model and slope model. Percent slope values range from a flat surface (0% slope), to a ver- tical surface (200% slope). An incline of 45 degrees will have a 100% slope.................................... 33 2.4 Distribution of rain measurement stations in the study area. Rain measurements are recorded monthly. Labels indicate place-names forthegauges............................... 34 2.5 Interpolated surface of mean annual precipitation (MAP) derived by ordinary kriging from the point coverage of rainguages. 3D point plot at bottom shows the NW-SE precipitation trend. 35 2.6 Flow chart of steps taken during image classification. 37 2.7 Area covered by the Landsat 7 scenes purchased for this study. 38 2.8 False color image of Landsat 7 ETM+ scene, path 169 row 62: Red near infrared (band 4), Green mid infrared (band 5), Blue red visible light (band 3. With this color combination dense vegetation appears red, and moderate vegetation appears dark green. Sparse vegetation appears blue as does shallow water. Deep water appears darker blue orblack.................................. 40 2.9 Distribution of Ground Truth Points. A total of 869 ground truth points were surveyed across the ecosystem. 620 overlap with the Path 169 imagery and were incorporated in this study. 45 2.10 The challenge of separating grassland and woodland land cover is shown here. Grassland and woodland areas have similar tones but differ in texture. Two areas in Serengeti are shown; one in the grass- lands and one in the woodlands. Upper inserts show the satellite imagery, lower inserts the resulting classification. 47 LIST OF FIGURES x 2.11 False color image of Landsat 7 scene, path 169 rows 61 and 62: near infrared (band 4) is depicted as red, mid infrared (band 5) as green and red visible light (band 3) as blue. Detail shows the transition between the grassland zone and the woodland zone and the accompanying shift in image tones and texture. 48 2.12 Level B supervised fuzzy classification of central-southern Serengeti and Ngorongoro Conservation Area. The legend codes are described inTable2.6................................ 51 2.13 Maximum likelihood classification with five classes. 54 2.14 Interpolated surface of mean annual precipitation (MAP) derived by ordinary kriging from the point coverage of rainguages. 3D point plot at bottom shows the NW-SE precipitation trend. 58 2.15 False color landsat 7 insert demonstrating seepage lines. Bands as inFigure2.8. .............................. 62 2.16 Distribution of analyzed roost sites. The upper left pane shows the roosts against a background map of woody vegetation, and against precipitation in the lower left. Remaining panes show close-ups of roosts outlined by 1.5 km buffer against a landsat background. The background includes a semi-transparent overlay of the vegetation classification to highlight woody vegetation. 65 3.1 Distribution of analyzed roost sites. The upper left pane shows the roosts against a background map of woody vegetation, and against precipitation in the lower left. Remaining panes show close-ups of roosts outlined by 1.5 km buffer against a landsat background.
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