Student t-values and probabilities for generalized least squares (GLS) models and alternative GLMM-models (in parenthesis) for wild forest reindeer population size, the moose abundance index and the wolf population in eastern Finland from 1996–2017.

Based on residual autocorrelation tests, AR correlation structures were used in models if the residuals were autocorrelated. Cox & Snell pseudo R 2 were computed for the GLS-models.

Bibliographic Details
Main Authors:	Ilpo Kojola (469975), Ville Hallikainen (5150468), Samuli Heikkinen (11886245), Jukka T. Forsman (8660328), Tuomas Kukko (11886248), Jyrki Pusenius (3839944), Paasivaara Antti (11886251)
Format:	Dataset
Language:	unknown
Published:	2021
Subjects:	Ecology Biological Sciences not elsewhere classified year time series canis lupus </ another independent variable alces alces </ 1996 – 2017 generalized linear mixed apparent competition whereby apparent competition hypothesis wild forest reindeer existing prey species alternative prey hypothesis 2 </ sup general linear models primary prey decreases reindeer population size wolf population size moose population size apparent competition population size performed linear primary prey wolf population population dynamics secondary prey reindeer focuses prey community prey biomass xlink "> wolf (< two hypotheses two co summer predation study period show long resulting pseudo reproductive output positively associated negatively associated negatively affects negative predictions mutually exclusive moose populations moose (< last years increased predation heavily managed habitat restoration first years female ratio consecutive winters almost identical Snell Alces alces Canis lupus
Online Access:	https://doi.org/10.1371/journal.pone.0259246.t001

Description
Summary:	Based on residual autocorrelation tests, AR correlation structures were used in models if the residuals were autocorrelated. Cox & Snell pseudo R 2 were computed for the GLS-models.