Matching Items (4)

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Vegetation modeling of Holocene landscapes in the southern Levant

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This dissertation creates models of past potential vegetation in the Southern Levant during most of the Holocene, from the beginnings of farming through the rise of urbanized civilization (12 to

This dissertation creates models of past potential vegetation in the Southern Levant during most of the Holocene, from the beginnings of farming through the rise of urbanized civilization (12 to 2.5 ka BP). The time scale encompasses the rise and collapse of the earliest agrarian civilizations in this region. The archaeological record suggests that increases in social complexity were linked to climatic episodes (e.g., favorable climatic conditions coincide with intervals of prosperity or marked social development such as the Neolithic Revolution ca. 11.5 ka BP, the Secondary Products Revolution ca. 6 ka BP, and the Middle Bronze Age ca. 4 ka BP). The opposite can be said about periods of climatic deterioration, when settled villages were abandoned as the inhabitants returned to nomadic or semi nomadic lifestyles (e.g., abandonment of the largest Neolithic farming towns after 8 ka BP and collapse of Bronze Age towns and cities after 3.5 ka BP during the Late Bronze Age). This study develops chronologically refined models of past vegetation from 12 to 2.5 ka BP, at 500 year intervals, using GIS, remote sensing and statistical modeling tools (MAXENT) that derive from species distribution modeling. Plants are sensitive to alterations in their environment and respond accordingly. Because of this, they are valuable indicators of landscape change. An extensive database of historical and field gathered observations was created. Using this database as well as environmental variables that include temperature and precipitation surfaces for the whole study period (also at 500 year intervals), the potential vegetation of the region was modeled. Through this means, a continuous chronology of potential vegetation of the Southern Levantwas built. The produced paleo-vegetation models generally agree with the proxy records. They indicate a gradual decline of forests and expansion of steppe and desert throughout the Holocene, interrupted briefly during the Mid Holocene (ca. 4 ka BP, Middle Bronze Age). They also suggest that during the Early Holocene, forest areas were extensive, spreading into the Northern Negev. The two remaining forested areas in the Northern and Southern Plateau Region in Jordan were also connected during this time. The models also show general agreement with the major cultural developments, with forested areas either expanding or remaining stable during prosperous periods (e.g., Pre Pottery Neolithic and Middle Bronze Age), and significantly contracting during moments of instability (e.g., Late Bronze Age).

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Date Created
  • 2011

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Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem

Description

Climate and land use change are projected to threaten biodiversity over the coming century. However, the combined effects of these threats on biodiversity and the capacity of current conservation networks

Climate and land use change are projected to threaten biodiversity over the coming century. However, the combined effects of these threats on biodiversity and the capacity of current conservation networks to protect species' habitat are not well understood. The goals of this study were to evaluate the effect of climate change and urban development on vegetation distribution in a Mediterranean-type ecosystem; to identify the primary source of uncertainty in suitable habitat predictions; and to evaluate how well conservation areas protect future habitat in the Southwest ecoregion of the California Floristic Province. I used a consensus-based modeling approach combining three different species distribution models to predict current and future suitable habitat for 19 plant species representing different plant functional types (PFT) defined by fire-response (obligate seeders, resprouting shrubs), and life forms (herbs, subshurbs). I also examined the response of species grouped by range sizes (large, small). I used two climate models, two emission scenarios, two thresholds, and high-resolution (90m resolution) environmental data to create a range of potential scenarios. I evaluated the effectiveness of an existing conservation network to protect suitable habitat for rare species in light of climate and land use change. The results indicate that the area of suitable habitat for each species varied depending on the climate model, emission scenario, and threshold combination. The suitable habitat for up to four species could disappear from the ecoregion, while suitable habitat for up to 15 other species could decrease under climate change conditions. The centroid of the species' suitable environmental conditions could shift up to 440 km. Large net gains in suitable habitat were predicted for a few species. The suitable habitat area for herbs has a small response to climate change, while obligate seeders could be the most affected PFT. The results indicate that the other two PFTs gain a considerable amount of suitable habitat area. Several rare species could lose suitable habitat area inside designated conservation areas while gaining suitable habitat area outside. Climate change is predicted to be more important than urban development as a driver of habitat loss for vegetation in this region in the coming century. These results indicate that regional analyses of this type are useful and necessary to understand the dynamics of drivers of change at the regional scale and to inform decision making at this scale.

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Date Created
  • 2012

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Improving species distribution models with bias correction and geographically weighted regression: tests of virtual species and past and present distributions in North American deserts

Description

This work investigates the effects of non-random sampling on our understanding of species distributions and their niches. In its most general form, bias is systematic error that can obscure interpretation

This work investigates the effects of non-random sampling on our understanding of species distributions and their niches. In its most general form, bias is systematic error that can obscure interpretation of analytical results by skewing samples away from the average condition of the system they represent. Here I use species distribution modelling (SDM), virtual species, and multiscale geographically weighted regression (MGWR) to explore how sampling bias can alter our perception of broad patterns of biodiversity by distorting spatial predictions of habitat, a key characteristic in biogeographic studies. I use three separate case studies to explore: 1) How methods to account for sampling bias in species distribution modeling may alter estimates of species distributions and species-environment relationships, 2) How accounting for sampling bias in fossil data may change our understanding of paleo-distributions and interpretation of niche stability through time (i.e. niche conservation), and 3) How a novel use of MGWR can account for environmental sampling bias to reveal landscape patterns of local niche differences among proximal, but non-overlapping sister taxa. Broadly, my work shows that sampling bias present in commonly used federated global biodiversity observations is more than enough to degrade model performance of spatial predictions and niche characteristics. Measures commonly used to account for this bias can negate much loss, but only in certain conditions, and did not improve the ability to correctly identify explanatory variables or recreate species-environment relationships. Paleo-distributions calibrated on biased fossil records were improved with the use of a novel method to directly estimate the biased sampling distribution, which can be generalized to finer time slices for further paleontological studies. Finally, I show how a novel coupling of SDM and MGWR can illuminate local differences in niche separation that more closely match landscape genotypic variability in the two North American desert tortoise species than does their current taxonomic delineation.

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Date Created
  • 2018

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Assessing ponderosa pine (Pinus ponderosa) suitable habitat throughout Arizona in response to future climate models

Description

The species distribution model DISTRIB was used to model and map potential suitable habitat of ponderosa pine throughout Arizona under current and six future climate scenarios. Importance Values for each

The species distribution model DISTRIB was used to model and map potential suitable habitat of ponderosa pine throughout Arizona under current and six future climate scenarios. Importance Values for each climate scenario were estimated from 24 predictor variables consisting of climate, elevation, soil, and vegetation data within a 4 km grid cell. Two emission scenarios, (A2 (high concentration) and B1 (low concentration)) and three climate models (the Parallel Climate Model, the Geophysical Fluid Dynamics Laboratory, and the HadleyCM3) were used to capture the potential variability among future climates and provide a range of responses from ponderosa pine. Summary tables for federal and state managed lands show the potential change in suitable habitat under the different climate scenarios; while an analysis of three elevational regions explores the potential shift of habitat upslope. According to the climate scenarios, mean annual temperature in Arizona could increase by 3.5% while annual precipitation could decrease by 36% over this century. Results of the DISTRIB model indicate that in response to the projected changes in climate, suitable habitat for ponderosa pine could increase by 13% throughout the state under the HadleyCM3 high scenario or lose 1.1% under the average of the three low scenarios. However, the spatial variability of climate changes will result in gains and losses among the ecoregions and federally and state managed lands. Therefore, alternative practices may need to be considered to limit the loss of suitable habitat in areas identified by the models.

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Date Created
  • 2011