Modeling cross-scale relationships between climate, hydrology, and individual animals: generating scenarios for stream salamanders

Abstract

Hybrid modeling provides a unique opportunity to study cross-scale relationships in environmental systems by linking together models of global, regional, landscape, and local-scale processes, yet the approach is rarely applied to address conservation and management questions. Here, we demonstrate how a hybrid modeling approach can be used to assess the effect of cross-scale interactions on the survival of the Allegheny Mountain Dusky Salamander (Desmognathus ochrophaeus) in response to changes in temperature and water availability induced by climate change at the northern limits of its distribution. To do so, we combine regional climate modeling with a landscape-scale integrated surface-groundwater flow model and an individual-based model of stream salamanders. On average, climate scenarios depict a warmer and wetter environment for the 2050 horizon. The increase in average annual temperature and extended hydrological activity time series in the future, combined with a better synchronization with the salamanders' reproduction period, result in a significant increase in the long-term population viability of the salamanders. This indicates that climate change may not necessarily limit the survivability of small, stream-dwelling animals in headwater basins located in cold and humid regions. This new knowledge suggests that habitat conservation initiatives for amphibians with large latitudinal distributions in Eastern North America should be prioritized at the northern limits of their ranges to facilitate species migration and persistence in the face of climate change. This example demonstrates how hybrid models can serve as powerful tools for informing management and conservation decisions.

Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation

“…In summary, results showed the wide range of problems these approaches are used for, but also highlighted the limited number of models applications dealing with climate impacts in mountain environments (Balbi et al, 2016(Balbi et al, , 2013Girard et al, 2015;Grêt-Regamey and Straub, 2006;Lacasse et al, 2008;Marzocchi et al, 2012). This gap is particularly clear for system dynamic models and hybrid models, highlighting potential room for further applications and methodological improvements.…”

“…In particular, Balbi et al (2013) applied an agentbased approach to assess the socio-economic consequences at local level looking at behaviours of winter and summer tourists for different snow cover scenarios in the Alps. Moreover, Girard et al (2015) considered a mountain environment to understand salamander population distribution and dynamics in case of temperature and water availability variation due to climate change.…”

“…Due to its characteristics of explicit temporal dynamic description, ABMs were applied to look at future scenarios of human-environment interactions. In particular, Mashhadi Ali et al (2017), Haer et al (2016) and Girard et al (2015) integrated future scenarios of climate change representing social dynamics and interactions with the environment for risk assessment purposes. In addition to climate change scenarios, Acosta et al (2014) and Balbi et al (2013) also considered future economic changes as main drivers of social emergent behaviours, assessing potential consequences at local level.…”

Understanding and managing the interactions of impacts from nature-based recreation and climate change

“…For example, the influence of mountain biking disturbance (smaller-scale factor in space and time) on ungulate reproduction (response variable) may vary with the amount of climate warming (broader-scale factor in space and time). Statistical methods for studying cross-scale interactions include hybrid modeling that combines regional, landscape, and individual-based models (Girard et al 2015); Bayesian or non-Bayesian hierarchical models (Sorrano et al 2014); and use of standard interaction terms (Neter et al 1989) in analysis of variance and regression.…”

Satellite‐enhanced dynamical downscaling for the analysis of extreme events

“…Regional modeling systems have increased our understanding on the relevance of cross‐scale interactions through the dynamical downscaling of general circulation models, with many applications [e.g., Girard et al , ]. Other related subjects, for example, water resources, food production and risk assessment studies, have also benefited from dynamically downscaled global outputs [e.g., Leung et al , ; Graham et al , ; Moore et al , ; Mearns et al , ].…”