Projected impacts of climate change on the range and phenology of three culturally-important shrub species

Abstract

Climate change is shifting both the habitat suitability and the timing of critical biological events, such as flowering and fruiting, for plant species across the globe. Here, we ask how both the distribution and phenology of three food-producing shrubs native to northwestern North America might shift as the climate changes. To address this question, we compared gridded climate data with species location data to identify climate variables that best predicted the current bioclimatic niches of beaked hazelnut (Corylus cornuta), Oregon grape (Mahonia aquifolium), and salal (Gaultheria shallon). We also developed thermal-sum models for the timing of flowering and fruit ripening for these species. We then used multi-model ensemble future climate projections to estimate how species range and phenology may change under future conditions. Modelling efforts showed extreme minimum temperature, climate moisture deficit, and mean summer precipitation were predictive of climatic suitability across all three species. Future bioclimatic niche models project substantial reductions in habitat suitability across the lower elevation and southern portions of the species' current ranges by the end of the 21 st century. Thermal-sum phenology models for these species indicate that flowering and the ripening of fruits and nuts will advance an average of 25 days by the mid-21 st century, and 36 days by the late-21 st century under a high emissions scenario (RCP 8.5). Future changes in the climatic niche and phenology of these important food-producing species may alter trophic relationships, with cascading impacts on regional ecosystems.

Predicted distribution of a rare and understudied forest carnivore: Humboldt marten (Martes caurina humboldtensis)

“…Salal and evergreen huckleberry appear particularly important, as the berries of each occur in Humboldt marten diets and provide food for marten prey species ( Eriksson et al, 2019 ; Manlick et al, 2019 ; Moriarty et al, 2019 ). We modeled probabilities of species occurrence of salal and evergreen huckleberry, creating the model for evergreen huckleberry following methods published for salal and other shrub species ( Prevéy, Parker & Harrington, 2020 ; Prevéy et al., 2020 ). We related locations to contemporary (1981–2010) bioclimatic variables from the AdaptWest project ( Wang et al, 2016 ) to depict the probability of species occurrence (1–100%).…”

Cryopreservation of Agronomic Plant Germplasm Using Vitrification-Based Methods: An Overview of Selected Case Studies

“…According to Lambers [ 3 ], one of the biggest concerns of biologists is that the rapid warming rates projected for the planet could lead many species to perish. Climate change is altering environmental niches, forcing species to shift their habitat range [ 4 ]. They can suffer from extinction if the specific habitat disappears or becomes inaccessible, due to geographical barriers or the species’ inability to disperse.…”

Predicted distribution of a rare and understudied forest carnivore: Humboldt martens (Martes caurina humboldtensis)

“…Humboldt martens have been associated with dense shrub cover throughout their range (Moriarty et al 2019; Slauson et al 2007); salal ( Gautheria shallon ) and evergreen huckleberry ( Vaccinium ovatum ) appear particularly important, as the berries of each occur in Humboldt marten diets and also provide food for marten prey items (Eriksson et al 2019; Moriarty et al 2019). We modeled salal and evergreen huckleberry occurrence and combined model outputs to create a shrub cover variable (shrub), which was the sum of the probabilities of species occurrence of both respective shrub rasters (Prevéy et al 2020a; Prevéy et al 2020b). We modeled our shrub cover variable using Maxent, version 3.3 (Phillips & Dudík 2008) with detailed methods published elsewhere (Prevéy et al 2020a; Prevéy et al 2020b).…”

“…We modeled salal and evergreen huckleberry occurrence and combined model outputs to create a shrub cover variable (shrub), which was the sum of the probabilities of species occurrence of both respective shrub rasters (Prevéy et al 2020a; Prevéy et al 2020b). We modeled our shrub cover variable using Maxent, version 3.3 (Phillips & Dudík 2008) with detailed methods published elsewhere (Prevéy et al 2020a; Prevéy et al 2020b). Briefly, these models used locations from 10 sources, including FIA plots, USDA Forest Service Ecology and Bureau of Land Management plots, iNaturalist, Oregon Flora Project, Consortium of Pacific Northwest Herbaria, and the Global Biodiversity Information Forum.…”

“…Briefly, these models used locations from 10 sources, including FIA plots, USDA Forest Service Ecology and Bureau of Land Management plots, iNaturalist, Oregon Flora Project, Consortium of Pacific Northwest Herbaria, and the Global Biodiversity Information Forum. We related locations to contemporary (1981-2010) bioclimatic variables from the AdaptWest project (Wang et al 2016) to depict the probability of species occurrence (1-100%), or expected habitat quality, for each species (Prevéy et al 2020a; Prevéy et al 2020b). The evergreen huckleberry model has not been published previously, but we created it using the same methods as the published salal model (Prevéy et al 2020a; Prevéy et al 2020b).…”