International Journal of Molecular Evolution and Biodiversity 2024, Vol.14, No.2, 91-103 http://ecoevopublisher.com/index.php/ijmeb 96 4 Predictive Models and Climate Change Scenarios 4.1 Overview of predictive models Predictive models are essential for understanding how climate change will affect biodiversity. These models can be broadly categorized into three types: correlative models, mechanistic models, and hybrid models. Correlative models, such as species distribution models (SDMs), use statistical relationships between species occurrences and environmental variables to predict future distributions. Mechanistic models, including climate envelope models, incorporate physiological and ecological processes to predict how species will respond to environmental changes. Hybrid models combine elements of both correlative and mechanistic approaches to leverage the strengths of each. Correlative models are relatively easy to implement and can handle large datasets, but they often fail to capture complex biological interactions and evolutionary processes (Wright et al., 2016). Mechanistic models provide detailed insights into species’ responses to environmental changes but require extensive data on physiological and ecological processes, which can be difficult to obtain (Kearney et al., 2018). Hybrid models offer more comprehensive predictions by integrating aspects of both correlative and mechanistic models; however, they also require extensive data and sophisticated modeling techniques. 4.2 Species distribution models (SDMs) SDMs predict future species distributions based on current relationships between species occurrences and environmental variables. These models are particularly useful for identifying potential range shifts due to climate change. By analyzing current distribution data and environmental conditions, SDMs can forecast suitable habitats under future climate scenarios, helping to identify species most vulnerable to climate change. This information guides habitat restoration, species translocation, and protected area planning, enhancing species’ chances of survival in changing climate conditions. Desert lizards, such as those in the Chihuahuan Desert, may experience range contractions due to increasing temperatures and reduced water availability. For instance, projections for the horned lizard (Phrynosoma spp.) indicate significant habitat loss under future climate scenarios (Lara-Resendiz et al., 2015). SDMs for forest-dwelling snakes suggest that these species may shift their ranges to higher elevations or more northern latitudes in response to warming temperatures. For example, the distribution of certain tropical snakes is expected to move towards cooler, more suitable habitats (Nori et al., 2016). 4.3 Climate envelope models Climate envelope models define the range of climatic conditions within which a species can survive and reproduce. These models are used to predict how shifts in climate variables will alter the distribution of suitable habitats for species. Tropical reptiles, such as those in the Amazon rainforest, are predicted to experience significant shifts in suitable habitats. For example, projections indicate that the habitat of the common lizard (Zootoca vivipara) will move to higher elevations or more temperate regions as temperatures rise (Levy et al., 2015). Similarly, other species that are highly specialized to specific climatic conditions may face the risk of reduced habitat availability, leading to potential declines in population sizes and genetic diversity. As the climate changes, these models also suggest that some lowland species may be forced into increasingly fragmented and limited areas of suitable habitat, particularly in mountainous regions where they can no longer migrate upward to escape rising temperatures. This scenario poses significant risks for species with limited dispersal abilities and those that require specific microhabitats to thrive. 4.4 Integrated models Integrated models combine ecological, genetic, and physiological data to provide a comprehensive understanding of species’ responses to climate change. These models can predict potential range expansions or contractions and assess species’ adaptive capacities. By integrating data from different disciplines, integrated models can more accurately simulate how species will survive and reproduce in changing environments. For example, these models can identify species with high genetic diversity and physiological plasticity, which are more likely to adapt to new
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