Spatial Autocorrelation in Species Distribution Models: Simultaneous Incorporation of Multiple Scales of Influence Using a Bayesian Framework

نویسندگان

  • Melissa Anthony
  • Daryl Trumbo
  • Jason Knouft
چکیده

Spatial autocorrelation (SAC), defined as the positive association between sample similarity and spatial proximity, is pervasive in ecological data. Several methods exist for the incorporation of SAC into statistical models, but not until recently have these methods been applied to species distribution data. When incorporated into species distribution models, SAC has been found to significantly alter model coefficients, subsequently changing the statistical inference of the model. Models without a SAC component run the risk of overestimating the relationship between environmental variables and the presence or abundance of a species, potentially resulting in poor predictive ability of the model. Numerous studies have demonstrated the improvement in species distribution model performance after the incorporation of SAC suggesting inclusion of this spatial component is essential for developing statistical models that accurately predict species distributions in novel environments.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparison of Geographically Weighted Regression and Regression Kriging to Estimate the Spatial Distribution of Aboveground Biomass of Zagros Forests

Aboveground biomass (AGB) of forests is an essential component of the global carbon cycle. Mapping above-ground biomass is important for estimating CO2 emissions, and planning and monitoring of forests and ecosystem productivity. Remote sensing provides wide observations to monitor forest coverage, the Landsat 8 mission provides valuable opportunities for quantifying the distribution of above-g...

متن کامل

تحلیل فضایی خشکسالی اقلیمی شمال غرب ایران با استفاده از آماره خودهمبستگی فضایی

Drought is the most important natural disaster, due to its widespread and comprehensive short and long term consequences. Several meteorological drought indices have been offered to determine the features. These indices are generally calculated based on one or more climatic elements. Due to ease of calculation and use of available precipitation data, SPI index usually was calculated for any des...

متن کامل

Joint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis

Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...

متن کامل

Hierarchical analysis of species distributions and abundance across environmental gradients.

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes interact across scales. Tra...

متن کامل

Bayesian Inference for Spatial Beta Generalized Linear Mixed Models

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012