Species Distribution Models

Transcription

1 Species Distribution Models Whitney Preisser ESSM 689 Quantitative Methods in Ecology, Evolution, and Biogeography

2 Overview What are SDMs? What are they used for? Assumptions and Limitations Data Types Model Algorithms Model Selection Model Evaluation

3 Species Distribution Models (SDMs) Mechanistic vs Correlative Models SDMs model the distribution of suitable environments for a particular species, not the species distribution

4 Mechanistic SDMs Suitable for identifying a species fundamental niche, or potential distribution Predict suitable environments using a species physiological limitations in their tolerance to environmental conditions Do not incorporate known occurrence records Difficult to use due to required knowledge of species

5 Correlative SDMs Aim to estimate environmental conditions suitable for a species using known distributions Correlate known occurrence records with various abiotic and biotic factors

6 SDM Uses Modeling predicted distribution or suitable environments? Conservation Find new populations of known species Identifying sites for reintroduction of species Identifying sites where species may become invasive Discovery of new species similar to modeled species Model a species distribution in response to future conditions Epidemiology Identifying sites of potential disease outbreak

7

8 Assumptions Observed distribution of species is informative of environmental requirements of species

9 Limitations SDMs model suitable environments for species based on modeled environmental variables and known occurrence records Do not model actual species distributions Do not account for all abiotic and biotic variables (interspecific relationships, physical barriers, etc.) Poor sampling in environmental space can inhibit proper modeling Source-sink problem (individuals can be found in unsuitable habitats) Type 4 Errors Can predict distributions that are neither part of the actual or potential distribution Less certainty when extrapolating data Predict distribution for environments with variables outside the range of what was put into the model

10 Data Biological Field surveys, large surveys, museum collections, online databases Presence only or presence/absence Biases False absence Incorrect species identification Biased sampling Easily accessible locations Museum collections

11 Data Environmental Often abiotic variables Climate, topography, land cover, soil type Continuous or categorical (latter more problematic) Point vectors, polygons, raster grid* Avoid predictor variables Elevation vs temperature and air pressure

12 Model Algorithms Probability of a species presence as a function of environmental variables Identify potentially complex non-linear relationships in multi-dimensional environmental space (Pearson 2009)

13

14 Differences between Modeling Algorithms Data type Presence only, presence and background, pseudo-absence Ability to handle categorical data Data Output Continuous or binary output Relative influence of input variables on model prediction

15 Model Selection No simple way Multiple reviews have tested multiple models Different models yield different results Dependent on data type, whether model is parametric or non-parametric, and extrapolation methods Consensus Best models incorporated interactions between variables and identified complex relationships Best models dependent on aim

16 Model Evaluation Test data Vs calibration data Randomization, bootstrapping, k-fold partitioning Confusion Matrix False positive, false negative, true positive, true negative Accuracy, Kappa true over total Requires absence data Sensitivity true positives/total positives Requires only presence data One-tailed binomial or chi-squared tests Specificity true negatives/total negatives Continuous to binary data

17 Works Cited R.G. Pearson Species Distribution Modeling for Conservation Educators and Practitioners. Synthesis. American Museum of Natural History, Lessons in Conservation. Available at Copyright 2009, by the authors of the material, with license for use granted to the Center for Biodiversity and Conservation of the American Museum of Natural History. All rights reserved.