Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution

Hong S He,Zhiwei Wu,Ben Bond-Lamberty,Jacob S Fraser,Yu Liang

doi:10.1371/journal.pone.0067889

Abstract

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Highlights

Concerns about global climate change, habitat fragmentation, and biodiversity loss have increasingly stimulated researchers to predict vegetation dynamics at broad spatial scales [1,2,3]
For most species, the proportions of type III sums of square values for thematic resolution were obviously larger than those for spatial resolution and their interaction, indicating that the relative importance of thematic resolution effects on predictions of species distribution was far larger than spatial resolution
For fir, the proportion of type III sums of square values of thematic resolution was near 95%, whereas the proportion of spatial resolution was only 5% (Fig. 4)

Summary

Introduction

Concerns about global climate change, habitat fragmentation, and biodiversity loss have increasingly stimulated researchers to predict vegetation dynamics at broad spatial scales [1,2,3]. The primary tools for predicting broad-scale forest vegetation dynamics include niche models [4,5], process models [6,7], and forest landscape models [8]. All of these models need to account for the effects of physical environment or environmental heterogeneity in the modelling framework. Compositional heterogeneity is characterized by the number of classes that describe environmental heterogeneity and the proportional area of each class in the study landscape These classes are often known as land types or ecoregions depending on study scales (hereafter called land type). Landscapes with more land types or more complex spatial patterns are considered more heterogeneous [13,14]

Objectives

Methods

Results

Discussion

Conclusion