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Welcome to
PJ-WIN:Drought Impacts on New Mexico Middle Rio Grande Basin Vegetation Home Page!

In 2005, we proposed two research problems that addressed key issues associated with drought-related mortality and the impacts on pinyon-juniper woodland ecosystems of the Middle Rio Grande Basin (MRGB), New Mexico. The three problems reflected a strategy of scaling from intensive plot level studies (Problem 1) to a landscape-scale assessment of recent drought-related mortality on woodland stand structure and finally to a Basin-wide assessment of mortality that has occurred in pinyon-juniper woodlands within the MRGB (Problem 2)

Problem 1: Determine ecosystem responses in upland watershed(s) to current perturbations caused by drought and bark beetle attacks and clarify how such responses influence dynamics, stability, and productivity of upland ecosystems in relation to watershed capability. Responses well involve Comparison of ecosystem characteristics in areas of significant piñon-juniper mortality and comparable unaffected areas.
Problem 2: Assess the change in stand structure of pinyon-juniper woodlands in areas of high mortality throughout the MRGB.

Problem Statements

Problem 1. Compare ecosystem characteristics in areas of significant pinyon-juniper mortality and nearby unaffected areas.
Intensively studied sites were established in three areas, the Jemez Mountains (northern region), Sandia Mountains (central region), and Manzano Mountains (southern region), which created a latitudinal gradient within the MRGB. These plots contained two sites, one which contained high mortality and one which had low mortality of the canopy. Because mortality varied throughout the MRGB, high and low mortality was relative to the area.

We measured key biotic and abiotic factors that were (1) most likely to be affected by drought related mortality of dominant trees and (2) also have important implications for ecosystem function. Specific variables measured included basal trunk diameter, crown characteristics, standing dead diameter and height, and downed wood volume for pinyons, junipers, and major shrub species. We also measured fuel loads using a modified Brown (1974) transect. We assessed the abundance and diversity of three indicator taxa that we expect will be responsive to ecological changes due to mortality. These focus groups were understory and intercanopy vegetation, as well as the ground-dwelling arthropods. Regarding these indicator species we proposed the following major working hypotheses.

Hypothesis 1. Canopy habitats under standing dead trees will be more likely to harbor invasive species compared to live-tree under-canopies and intercanopy habitats.
Hypothesis 2. Canopy habitats under standing dead trees will have greater diversity and abundance of herbaceous plants and ground-dwelling arthropods compared to live-tree under-canopies and intercanopy habitats.
Hypothesis 3. High-mortality areas will exhibit higher abundance and diversity in herbaceous plants and arthropods compared to other areas.
Hypothesis 4. Herbaceous plants will be the most responsive to drought-induced mortality, followed by arthropods.

Problem 2. Assess and verify the change woodland stand structure and the extent of drought-related mortality.
Resolving problem 2 allows us to map mortality areas and how stand structure has changed. This portion of the study will therefore provide a sense of the spatial variability in stand structure changes. We cannot scale up precisely from our plot-level studies, because they will not represent the entire spectrum of drought impacts that occurred over the heterogeneous landscape of the MRGB. We can provide a course but meaningful assessment of the regional ecosystem impacts through extrapolation. Each site was GPSed to sub-meter accuracy and incorporated into an ArcMap project along with other environmental layers. We did not have specific hypotheses with this problem statement, as our goal was to provide a regional picture of variation in stand-structure as a result of tree mortality. With these data we examined environmental predictors of mortality using available GIS data (e.g., elevation, soils, climate, land ownership, vegetation, and human activities such as roads).

Last Updated: 05/12/08
Northern Arizona UniversityMerriam-Powell Center for Environmental Researchsouthwest information node