Microhabitat selection in the common lizard: implications of biotic interactions, age, sex, local processes, and model transferability among populations

Abstract

Modeling species' habitat requirements are crucial to assess impacts of global change, for conservation efforts and to test mechanisms driving species presence. While the influence of abiotic factors has been widely examined, the importance of biotic factors and biotic interactions, and the potential implications of local processes are not well understood. Testing their importance requires additional knowledge and analyses at local habitat scale. Here, we recorded the locations of species presence at the microhabitat scale and measured abiotic and biotic parameters in three different common lizard (Zootoca vivipara) populations using a standardized sampling protocol. Thereafter, space use models and cross‐evaluations among populations were run to infer local processes and estimate the importance of biotic parameters, biotic interactions, sex, and age. Biotic parameters explained more variation than abiotic parameters, and intraspecific interactions significantly predicted the spatial distribution. Significant differences among populations in the relationship between abiotic parameters and lizard distribution, and the greater model transferability within populations than between populations are in line with effects predicted by local adaptation and/or phenotypic plasticity. These results underline the importance of including biotic parameters and biotic interactions in space use models at the population level. There were significant differences in space use between sexes, and between adults and yearlings, the latter showing no association with the measured parameters. Consequently, predictive habitat models at the population level taking into account different sexes and age classes are required to understand a specie's ecological requirements and to allow for precise conservation strategies. Our study therefore stresses that future predictive habitat models at the population level and their transferability should take these parameters into account.

Outstanding Challenges in the Transferability of Ecological Models

“…Colors indicate whether transfers were considered successful (green, unbroken lines; 1-9) or not (dark red, dashed lines; [16][17][18][19][20], as reported by the authors and irrespective of the statistical methods chosen to build the models or the metrics used to evaluate them. Dual colors indicate scenarios in which the quality of transfers varied as a function of modeling algorithms (10-11), space (12), or species (13)(14)(15) contemporaneous sites at different positions along an environmental gradient can approximate temporal variability [72]. Such would be the case, for example, for areas subject to temperature regimes similar to those anticipated in the future, noting it will not be appropriate for species occupying small ranges or those not well-represented in the fossil record.…”

“…This goal fundamentally requires better transferability metrics and estimates of prediction uncertainty, which can assist in selecting the most consistent and effective management options while avoiding unanticipated outcomes [84]. Evidence indicates discrepancies in model performance among taxa with divergent life-history traits, and populations with different age structures and sex ratios (e.g., [14]). Meta-analyses demonstrate that body size and trophic position are strong indicators of ecological predictability [15], with some studies also indicating greater hurdles in building transferable models for wide-ranging organisms with broad environmental niches than for narrow-ranging specialists [16].…”

Climate Effects on Growth, Body Condition, and Survival Depend on the Genetic Characteristics of the Population

“…The common lizard is a small, sexually dimorphic (e.g., females are longer than males, sexes differ in ventral coloration), ground-dwelling lacertid that preferentially inhabits hygrophilic and mesophilic habitats, and its spatial distribution is linked with soil humidity (Braña 1996;Peñalver-Alcázar et al 2016). Zootoca vivipara has a highly permeable skin, which increases the risk of hydric loss (Grenot et al 1987), and its hydric balance is mainly controlled by environmental factors and behavioral regulation (i.e., by microhabitat selection or use; Grenot and Heulin 1990;Lorenzon et al 1999).…”

“…Adult males exhibit a genetic color polymorphism (San-Jose et al 2012Fitze et al 2014), and the polymorphism frequency reflects the genetic characteristics of the populationthat is, the genotype frequencies at the morph loci (at the locus or loci contributing to color morph) and all linked loci (Sinervo et al 2007(Sinervo et al , 2008. Zootoca vivipara occurrence is strongly associated with humidity (Pilorge 1987;Ceirans 2007;Peñalver-Alcázar et al 2016), and climate change models predict a global increase in overall precipitation, mean and extreme temperature, and alteration of local precipitation patterns (IPCC 2013). Given the importance of humidity for Z. vivipara, we simulated environmental change by experimentally exposing lizards to different humidity regimes and crossed this treatment with a morph frequency treatment using a 2 # 3 design.…”

Age-dependent effects of moderate differences in environmental predictability forecasted by climate change, experimental evidence from a short-lived lizard (Zootoca vivipara)

“…To this end, we experimentally tested in age-structured populations whether and how differences in precipitation predictability affect life-history strategies and life history traits of different age-classes (adults, yearlings, juveniles) of the European common lizard ( Zootoca vivipara ; Lichtenstein, 1823). Zootoca vivipara exhibits high dependency on water 22–24 and water availability constrains its life history traits, e.g., its growth and reproduction 11,25 . Its hydric balance is mainly controlled by environmental factors and behavioural regulation 23 .…”