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Research about Mesa Verde National Park

Source-linked reports with geographic coverage including Mesa Verde National Park.

7 recordsLinked to original sources
USGS2025

Fungi, fire, and feedbacks: Grasses and wildfire interact to alter ectomycorrhizal fungal communities and decrease tree seedling growth

Wildfire and its effects, including changes to soil biota and the introduction of invasive or seeded grasses, can cause long-term shifts in ecological communities. Post-wildfire establishment of long-lived trees and shrubs is a critical bottleneck to recovering native plant communities. Ectomycorrhizal fungi (EMF) can improve plant responses to stressors and influence seedling establishment following wildfire, but little is known about how introduced grasses alter plant-fungal relationships and influence woody plant recovery. We investigated how piñon pine ( Pinus edulis ) EMF colonization and growth responded to soil wildfire history and novel grasses. Piñon seedlings were grown in soils from areas that burned in a stand-replacing fire nearly two decades prior or in soils from unburned piñon-juniper woodlands. Each piñon was grown with an invasive grass ( Bromus tectorum ), a native rhizomatous grass ( Pascopyrum smithii ) or another piñon seedling. Even ∼20 years after fire, EMF community composition in burned areas differed from that of unburned woodlands. Fire history and plant neighbor identity interacted to affect EMF abundance. Piñon seedling biomass was positively associated with EMF abundance in unburned woodland soils, but not in post-burn soils, suggesting that the EMF community in unburned woodlands is more beneficial. Importantly, the presence of either an invasive or native grass had a negative effect on seedling growth and EMF abundance, resulting in an average 61.4 % drop in EMF abundance and altered EMF community composition. Our findings suggest that plant species interactions, long-term effects of fire on soil, and EMF may determine the trajectory of woodland recovery following wildfire.

Colorado↗
USGS2024

Trajectories and tipping points of piñon–juniper woodlands after fire and thinning

Piñon–juniper (PJ) woodlands are a dominant community type across the Intermountain West, comprising over a million acres and experiencing critical effects from increasing wildfire. Large PJ mortality and regeneration failure after catastrophic wildfire have elevated concerns about the long-term viability of PJ woodlands. Thinning is increasingly used to safeguard forests from fire and in an attempt to increase climate resilience. We have only a limited understanding of how fire and thinning will affect the structure and function of PJ ecosystems. Here, we examined vegetation structure, microclimate conditions, and PJ regeneration dynamics following ~20 years post-fire and thinning treatments. We found that burned areas had undergone a state shift that did not show signs of returning to their previous state. This shift was characterized by (1) distinct plant community composition dominated by grasses; (2) a lack of PJ recruitment; (3) a decrease in the sizes of interspaces in between plants; (4) lower abundance of late successional biological soil crusts; (5) lower mean and minimum daily soil moisture values; (6) lower minimum daily vapor pressure deficit; and (7) higher photosynthetically active radiation. Thinning created distinct plant communities and served as an intermediate between intact and burned communities. More intensive thinning decreased PJ recruitment and late successional biocrust cover. Our results indicate that fire has the potential to create drier and more stressful microsite conditions, and that, in the absence of active management following fire, there may be shifts to persistent ecological states dominated by grasses. Additionally, more intensive thinning had a larger impact on community structure and recruitment than less intensive thinning, suggesting that careful consideration of goals could help avoid unintended consequences. While our results indicate the vulnerability of PJ ecosystems to fire, they also highlight management actions that could be adapted to create conditions that promote PJ re-establishment.

Colorado↗
USGS2012

Surficial Geologic Map of Mesa Verde National Park, Montezuma County, Colorado

Mesa Verde National Park in southwestern Colorado was established in 1906 to preserve and protect the artifacts and dwelling sites, including the famous cliff dwellings, of the Ancestral Puebloan people who lived in the area from about A.D. 550 to A.D. 1300. In 1978, the United Nations designated the park as a World Heritage Site. The geology of the park played a key role in the lives of these ancient people. For example, the numerous (approximately 600) cliff dwellings are closely associated with the Cliff House Sandstone of Late Cretaceous age, which weathers to form deep alcoves. In addition, the ancient people farmed the thick, red loess (wind-blown dust) deposits on the mesa tops, which because of its particle size distribution has good moisture retention properties. The soil in this loess cover and the seasonal rains allowed these people to grow their crops (corn, beans, and squash) on the broad mesa tops. Today, geology is still an important concern in the Mesa Verde area because the landscape is susceptible to various forms of mass movement (landslides, debris flows, rockfalls), swelling soils, and flash floods that affect the park's archeological sites and its infrastructure (roads, septic systems, utilities, and building sites). The map, which encompasses an area of about 100 mi 2 (260 km 2 ), includes all of Mesa Verde National Park, a small part of the Ute Mountain Indian Reservation that borders the park on its southern and western sides, and some Bureau of Land Management and privately owned land to the north and east. Surficial deposits depicted on the map include: artificial fills, alluvium of small ephemeral streams, alluvium deposited by the Mancos River, residual gravel on high mesas, a combination of alluvial and colluvial deposits, fan deposits, colluvial deposits derived from the Menefee Formation, colluvial deposits derived from the Mancos Shale, rockfall deposits, debris flow deposits, earthflow deposits, translational and rotational landslide deposits, rock rubble deposits, and loess. Bedrock units depicted on the map include the Cliff House Sandstone, Menefee Formation, Point Lookout Sandstone, and Mancos Shale all of Late Cretaceous age. In addition, minette dikes, of Oligocene age, found at several locations in the park are depicted on the map. Descriptions, including associated hazards and resources as used by the Ancestral Puebloans, are given for all map units.

Colorado↗
USGS2011

Bats of Mesa Verde National Park, Colorado: Composition, reproduction, and roosting habits

We determined the bat fauna at Mesa Verde National Park (Mesa Verde) in 2006 and 2007, characterized bat elevational distribution and reproduction, and investigated roosting habits of selected species. We captured 1996 bats of 15 species in mist nets set over water during 120 nights of sampling and recorded echolocation calls of an additional species. The bat fauna at Mesa Verde included every species of bat known west of the Great Plains in Colorado, except the little brown bat ( Myotis lucifugus ). Some species showed skewed sex ratios, primarily due to a preponderance of males. Thirteen species of bats reproduced at Mesa Verde. Major differences in spring precipitation between the 2 years of our study were associated with differences in reproductive rates and, in some species, with numbers of juveniles captured. Reduced reproductive effort during spring drought will have a greater impact on bat populations with the forecasted increase in aridity in much of western North America by models of global climate change. We radiotracked 46 bats of 5 species to roosts and describe the first-known maternity colonies of spotted bats ( Euderma maculatum ) in Colorado. All 5 species that we tracked to diurnal roosts relied almost exclusively on rock crevices rather than trees or snags, despite the presence of mature forests at Mesa Verde and the use of trees for roosts in similar forests elsewhere by some of these species. Comparisons with past bat surveys at Mesa Verde and in surrounding areas suggest no dramatic evidence for effects of recent stand-replacing fires on the composition of the bat community.

Colorado↗
USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗