You are here

BCM-PVT - Bioclimatic modeling of potential vegetation types

Predicting plant species shifts under changing climates using bioclimatic modeling of potential vegetation types

Land managers need new tools for accounting for novel futures due to climate change. Species distribution modeling has been used extensively to predict future distributions of individual species under different climates, but the map products are too coarse for operational use and creating the suite of species projections needed for comprehensive land management is impossible due to lack of data and expertise. A new method for predicting ecosystem characteristics, which are germane to land management, into the future is develop in this project.

Potential Vegetation Types (PVTs) were mapped using conventional statistical modeling techniques from ecosystem process and climate variables. Then, future projections of climate are used to generate future PVT maps. Species presence for a number of species as from the PVT classification were then mapped into the future using both the current and future PVT maps, as were other ecological characteristics associated with the PVT categories were also mapped. Using this fast, inexpensive, and comprehensive alternative method, future maps of many ecological characteristics commonly used in land management can be easily created using the PVT associations to show possible climate change scenarios.

Using this fast, inexpensive, and comprehensive alternative method, future maps of many ecological characteristics commonly used in land management can be easily created using the PVT associations.

The flow chart of procedures used in this study to create future Potential Vegetation Type (PVT) and species presence maps.

The flow chart of procedures used in this study to create future Potential Vegetation Type (PVT) and species presence maps. FIA, ECODATA, and FSVEG are data storage systems that contained PVT and species presence data. SDM is species distribution modeling.

The Southwest Crown of the Continent (SWCC) study area.

The Southwest Crown of the Continent (SWCC) study area. This is a large landscape (519,322 ha) that is bounded by the Mission Mountains to the west and the Swan Mountains to the east. It is an important area because it is part of a landscape management cooperative. The study area consists of a wide valley bounded by high mountain ranges. Blue dots are the polygons and field data locations in the SWCC.

Predictions of Potential Vegetation Types

Predictions of Potential Vegetation Types (PVT; Pfister et al. 1977 habitat types) from the BCM-PVT method under (A) contemporary climate and (B) future climate based on the HadGEM2-ES global climate model under RCP 8.5 radiative forcing scenario. Definitions for the habitat types shown in the legend are in Table 1.

BCM-PVT predictions

BCM-PVT predictions of (A) tree and (B) non-tree species distributions under current climate and HadGEM2-ES global climate model with the RCP 8.5 radiative forcing scenario. Tree species include Psuedostuga menzenzii (PSME), Abies lasiocarpa (ABLA), Thuja plicata (THPL), Larix occidentalis (LAOC), and Pinus albicaulus (PIAL). Non tree species are Vaccinium scoparim (VASC), Xerophyllum tenex (XETE), Linnea borealis (LIBO), Clintonia uniflora (CLUN), and Menziesia ferruginea (MEFE).

Predictions of Larix occidentalis (LAOC) distributions

Predictions of Larix occidentalis (LAOC) distributions from the BCM-PVT approach and the two other SDM products (SDM-F=FORECASTS, SDM-M=Moscow FSL). Blue indicates LAOC distributions. See Table 4 for accuracy and percent coverage.

Modified: Mar 10, 2020

Select Publications & Products

Keane, RE; Holsinger L. 2020 [in review]. An alternative to species niche modeling for predicting plant species distributions under changing climates: bioclimatic modeling of potential vegetation types. Forest Ecology and Management [refereed]