Protected areas are the backbone of biodiversity conservation but vulnerable to climate change. Thailand has a large and well-planned protected area system, covering most remaining natural vegetation. A statistically derived global environmental stratification (GEnS) was used to predict changes in bioclimatic conditions across the protected area system for 2050 and 2070, based on projections from three CMIP5 earth system models and two representative concentration pathways (RCPs). Five bioclimatic zones were identified composed of 28 strata. Substantial spatial reorganization of bioclimates is projected in the next 50 years, even under RCP2.6, while under RCP8.5 the average upward shift for all zones by 2070 is 328–483 m and the coolest zone disappears with two models. Overall, 7.9–31.0% of Thailand’s land area will change zone by 2070, and 31.7–90.2% will change stratum. The consequences for biodiversity are less clear, particularly in the lowlands where the existing vegetation mosaic is determined largely by factors other than climate. Increasing connectivity of protected areas along temperature and rainfall gradients would allow species to migrate in response to climate change, but this will be difficult in much of Thailand. For isolated protected areas and species that cannot move fast enough, more active, species-specific interventions may be necessary.

Although 23% of Thailand’s land is in protected areas, these are vulnerable to climate change. We used spatial distribution modelling for 866 vertebrate and 591 plant species to understand potential climate change impacts on species in protected areas. Most mammals, birds, and plants were projected to decline by 2070, but most amphibians and reptiles were projected to increase. By 2070 under RCP8.5, 54% of modeled species will be threatened and 11 nationally extinct. However, SDMs are sensitive to truncation of the climate space currently occupied by habitat loss and hunting, and apparent truncation by data limitations. In Thailand, lowland forest clearance has biased records for forest-dependent species to cooler uplands (> 250 m a.s.l.) and hunting has confined larger vertebrates to well-protected areas. In contrast, available data is biased towards lowland non-forest taxa for amphibians and reptiles. Niche truncation may therefore have resulted in overestimation of vulnerability for some mammal and plant species, while data limitations have likely led to underestimation of the threat to forest-dependent amphibians and reptiles. In view of the certainty of climate change but the many uncertainties regarding biological responses, we recommend regular, long-term monitoring of species and communities to detect early signals of climate change impacts.

Sentinel plasticine prey has been increasingly used to estimate predation pressure. The use of plasticine prey may, however, bias the results, as this method was originally designed to account for predation by organisms that can visually recognize the shapes and colors of their prey. To evaluate the limitations of using sentinel plasticine prey, we compared predator attack rates between real prey – dead and live mealworms, Tenebrio molitor L. (Coleoptera: Tenebrionidae) – and plasticine models in a monsoonal tropical rainforest of southeastern China. The attack rates by invertebrates were highest on dead prey followed by live prey and plasticine models, whereas the attack rates by vertebrates were lowest on dead prey, and did not differ between live prey and plasticine models. These results confirm that bias imposed by using the plasticine models is affected by the type of predators. In addition, we tested the validity and generality of the premise that predators can distinguish the shapes of plasticine model prey and preferentially attack a caterpillar‐like shape over other shapes. To test this hypothesis, we conducted three independent experiments in China, Papua New Guinea, and Finland. In the two latter localities, predation rates on plasticine caterpillars were higher than on models of other shapes, whereas in China, these differences were not significant. Taken together, our study suggests that plasticine models may underestimate the predation by invertebrates to a greater extent than predation by vertebrates, and the preference of model shape by predators may be locality‐specific, presumably due to differences in the composition of the predator community. We propose that predation be estimated on both live and plasticine prey in future studies to measure the potential bias imposed by using plasticine models and its variation among various habitats and predator groups.