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Mount Rushmore National Memorial in the Black Hills of South Dakota is known worldwide for its massive sculpture of four of the United States' most respected presidents. The Memorial landscape also is covered by extensive ponderosa pine (Pinus ponderosa) forest that has not burned in over a century. We compiled dendroecological and forest structural data from 29 plots across the 517-ha Memorial and used fire behavior modeling to reconstruct the historical fire regime and forest structure and compare them to current conditions. The historical fire regime is best characterized as one of low-severity surface fires with occasional (> 100 years) patches (< 100 ha) of passive crown fire. We estimate that only approximately 3.3% of the landscape burned as crown fire during 22 landscape fire years (recorded at > or = 25% of plots) between 1529 and 1893. The last landscape fire was in 1893. Mean fire intervals before 1893 varied depending on spatial scale, from 34 years based on scar-to-scar intervals on individual trees to 16 years between landscape fire years. Modal fire intervals were 11-15 years and did not vary with scale. Fire rotation (the time to burn an area the size of the study area) was estimated to be 30 years for surface fire and 800+ years for crown fire. The current forest is denser and contains more small trees, fewer large trees, lower canopy base heights, and greater canopy bulk density than a reconstructed historical (1870) forest. Fire behavior modeling using the NEXUS program suggests that surface fires would have dominated fire behavior in the 1870 forest during both moderate and severe weather conditions, while crown fire would dominate in the current forest especially under severe weather. Changes in the fire regime and forest structure at Mount Rushmore parallel those seen in ponderosa pine forests from the southwestern United States. Shifts from historical to current forest structure and the increased likelihood of crown fire justify the need for forest restoration before a catastrophic wildfire occurs and adversely impacts the ecological and aesthetic setting of the Mount Rushmore sculpture.

Government agencies are subject to increasing public scrutiny of land management practices. Consequently, rigorous, yet efficient, monitoring protocols are needed to provide defensible quantitative data on the status and trends of rangeland vegetation. Rigor requires precise, repeatable measures, whereas efficiency requires the greatest possible information content for the amount of resources spent acquiring the information. We compared two methods-point frequency and visual estimate-of measuring canopy cover of individual plant species and groups of species (forbs vs. graminoids, native vs. nonnative) and plant species richness. These methods were compared in a variety of grassland vegetation types of the northern Great Plains for their precision, repeatability, and efficiency. Absolute precision of estimates was similar, but values generally differed between the two sampling methods. The point-frequency method yielded significantly higher values than the visual-estimate method for cover by individual species, graminoid cover, and total cover, and yielded significantly lower values for broadleaf (forb + shrub) cover and species richness. Differences in values derived by different sampling teams using the same method were similar between methods and within precision levels for many variables. Species richness and median species cover were the major exceptions; for these, the point-frequency method was far less repeatable. As performed in this study, the visual-estimate method required approximately twice the time as did the point-frequency method, but the former captured 55% more species. Overall, the visual-estimate method of measuring plant cover was more consistent among observers than anticipated, because of strong training, and captured considerably more species. However, its greater sampling time could reduce the number of samples and, therefore, reduce the statistical power of a sampling design if time is a limiting factor. Resumen Las agencias de gobierno están sujetas a incrementar el escrutinio público de las prácticas de administración de suelos. Por consiguiente, los protocolos de monitoreos rigurosos, pero eficientes, son necesarios para proveer datos cuantitativos defendibles sobre el estado y tendencias de los pastizales. El rigor requiere medidas repetibles y precisas, mientras que la eficiencia requiere el mayor contenido informativo por la cantidad de recursos utilizados para adquirir la información. Nosotros comparamos dos métodos-frecuencia de puntos y estimado visual-de medición de cobertura de dosel de especies de plantas individuales y grupos de especies (arbustos vs. gramíneas, nativas vs. no nativas), tan bien como la riqueza de especies de plantas. Estos métodos fueron comparados en una variedad de tipos de pastizales en las grandes llanuras del norte para su precisión, repetibilidad y eficiencia. La precisión absoluta de estimaciones fue similar, pero los valores generalmente difirieron entre los dos métodos de muestreos. El método de frecuencia de puntos produjo valores significativame...

Plot and Quadrat/Point: Unique plot ID, and if applicable, quadrat number (m distance along transect) or point-intercept point (including transect letter). Indicate whether number refers to quadrat or point number. Note that point number is not the same as the distance of the point from the transect anchor. Examples: PCM5-B38 (quad) = monitoring site 5, transect B, quadrat 38 PCM5-B38 (point) = monitoring site 5, transect B, point # 38 Date: Include month (mm) / day (dd) / year (yy) Unknown Code: A unique code referring to the plant's form (e.g., grass, sedge, succulent), taxon (genus, family), or some other distinguishing characteristic.Plant type and General Description: Circle the appropriate category and provide a detailed description of the overall appearance Most Salient Feature: The feature that identifies this plant from all others; a unique characteristic Leaf Characteristics: Describe the leaf type, leaf margin, leaf surface, petiole, etc.Stem Characteristics: Describe the shape, pubescence, markings, and color of the stem, as well as the bud characteristics.Flower Characteristics: Describe the floral formula, location (axillary or terminal), habit (indeterminate or determinate), pubescence, and color. General and Microhabitat Characteristics:List other species located in the general vicinity, selecting the more conservative species in the area. Describe the microhabitat in which it was found.Collected: Circle yes or no, whether a specimen was collected.Best Guess: Preliminary guess about species in field.Confirmed to be: After consultation of reference books and/or herbarium, the species determined.

A new decision support tool for collaborative adaptive vegetation management in northern Great Plains national parks activities; invasive plants, animals, and diseases have continued to spread to wildlands; and extreme weather events are becoming more frequent as the earth continues to warm. Although the traditional NPS approach of trying to maintain ecosystems within their historic range of variability may no longer be relevant, national