The Topographic Relative Moisture Index: An Approach to Soil-Moisture Assessment in Mountain Terrain

Parker, Albert

doi:10.1080/02723646.1982.10642224

Cited by 222 publications

(144 citation statements)

References 22 publications

(25 reference statements)

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“…: TM = 5.68-A + 3.32 + 4.42"e -°'°°Sl*sl°p~, where A = 1.73 for ridge tops, 1.49 for upper third of slopes, 0.7 for middle third of slopes and benches, 0.25 for draws, 0.07 for lower third of slopes, 0.03 for toe slopes, and 0 for valley bottoms). This index decreases with slope and drier topographic positions, and although similar to Parker's (1982) index, variables are combined differently, and the regional index was much more significant in the analyses. Climatic variables were extracted by geographic overlay of plot coordinates with maps created by the PRISM model, which uses elevation and coarse-scale aspect to interpolate data from climate stations (Daly et al, 1994).…”

Section: Discussionmentioning

confidence: 79%

Eight nonnative plants in western Oregon forests: Associations with environment and management

Gray

2005

Environ Monit Assess

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Abstract. Nonnative plants have tremendous ecological and economic impacts on plant communities globally, but comprehensive data on the distribution and ecological relationships of individual species is often scarce or nonexistent. The objective of this study was to assess the influence of vegetation type, climate, topography, and management history on the distribution and abundance of eight selected nonnative plant taxa in forests in western Oregon. These eight taxa were selected as being reliably detected by a multi-resource inventory of 1127 systematically-placed plots on nonfederal forest lands from 1995 to 1997 by the USFS Forest Inventory and Analysis (FIA) program. One or more of the eight nonnative taxa studied were found on 20% of the sampled subplots in the study area, but relatively few stands were dominated by them. Overall abundance of nonnative taxa was likely much greater, because few composites and graminoids were identified to species in this general-purpose inventory. Distribution of most taxa was more closely associated with low density of overstory trees than with climate. Nonnative taxa were significantly more abundant in stands that had been recently clearcut or thinned than in stands that had not. Frequencies of several taxa decreased with elevation, which may reflect proximity to source populations and intensive land use rather than any climatic constraints. Although the greatest potential for displacement of native forest species appears to be in early-successional communities, the potential for spread of some shade-tolerant evergreen shrubs also seems high.

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Section: Discussionmentioning

confidence: 79%

Eight nonnative plants in western Oregon forests: Associations with environment and management

Gray

2005

Environ Monit Assess

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“…Raster datasets for slope, aspect, and curvature were generated using Spatial Analyst tools in ArcMap 10.1. Aspect was classified so that values ranged from 0 (xeric) to 20 (mesic) (Parker 1982). Pixels were categorized by four topographic position index (TPI) classes (valley bottom, gentle slope, steep slope, ridgetop) using the CorridorDesigner toolbox (Majka et al 2007).…”

Section: Discussionmentioning

confidence: 99%

Historical and current landscape‐scale ponderosa pine and mixed conifer forest structure in the Southern Sierra Nevada

et al. 2015

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Abstract. Many managers today are tasked with restoring forests to mitigate the potential for uncharacteristically severe fire. One challenge to this mandate is the lack of large-scale reference information on forest structure prior to impacts from Euro-American settlement. We used a robust 1911 historical dataset that covers a large geographic extent (.10,000 ha) and has unbiased sampling locations to compare past and current forest conditions for ponderosa pine and mixed conifer forests in the southern Sierra Nevada. The 1911 dataset contained records from 18,052 trees in 378 sampled transects, totaling just over 300 ha in transect area. Forest structure was highly variable in 1911 and shrubs were found in 54% of transects. Total tree basal area ranged from 1 to 60 m 2 ha À1 and tree density from 2 to 170 ha À1 (based on trees .30 cm dbh). K-means cluster analysis divided transects into four groups: mixed conifer-high basal area (MC High BA), mixed conifer-average basal area (MC Ave BA), mixed conifer-average basal area-high shrubs (MC Ave BA Shrubs), and ponderosa pine (Pond Pine). The percentage of this 1911 landscape that experienced high severity fire was low and varied from 1-3% in mixed conifer forests and 4-6% in ponderosa pine forests. Comparing forest inventory data from 1911 to the present indicates that current forests have changed drastically, particularly in tree density, canopy cover, the density of large trees, dominance of white fir in mixed conifer forests, and the similarity of tree basal area in contemporary ponderosa pine and mixed conifer forests. Average forest canopy cover increased from 25-49% in mixed conifer forests, and from 12-49% in ponderosa pine forests from 1911 to the present; canopy cover in current forest types is similar but in 1911 mixed conifer forests had twice the canopy cover as ponderosa pine forests. Current forest restoration goals in the southern Sierra Nevada are often skewed toward the higher range of these historical values, which will limit the effectiveness of these treatments if the objective is to produce resilient forest ecosystems into the future.

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“…Some biophysical and demographic variables shown to be strongly correlated with forest cover dynamics in previous spatially explicit models (Southworth and Tucker 2001;Nagendra et al 2003;McConnell et al 2004;Southworth et al 2004) were selected for use as predictor variables in these logistic regression models. These included elevation, slope, and aspect [converted into soil moisture classes (Parker 1982)], all derived from a digital elevation model acquired by the Shuttle Radar Topography Mission (SRTM) (Berry et al 2007), together with distance to the nearest forest edge in 1994 and human population density. The latter was calculated as the density of human settlements (Fig.…”

Section: Influence Of Conservation Policies On Forest Cover Dynamicsmentioning

confidence: 99%

“…This could be explained by the fact that forest areas in higher elevations were harvested during the 1990s while at lower elevations, which had been harvested earlier (i.e., during the 1970s and 1980s), forest recovery took place during the 1990s (He et al 2009). Aspect, which was converted into soil moisture classes (Parker 1982), was negatively related to the probability of forest loss and positively related with the probability of forest recovery. As this relative scalar is associated in temperate regions with soil moisture in response to differences in solar illumination (Parker 1982), this result suggests that the probability of forest recovery is higher in mesic areas (e.g., north-facing slopes) while the probability of forest loss was higher in drier/sunnier areas (e.g., south-facing slopes).…”

Section: Influence Of Conservation Policies On Forest Cover Dynamicsmentioning

confidence: 99%

“…Aspect, which was converted into soil moisture classes (Parker 1982), was negatively related to the probability of forest loss and positively related with the probability of forest recovery. As this relative scalar is associated in temperate regions with soil moisture in response to differences in solar illumination (Parker 1982), this result suggests that the probability of forest recovery is higher in mesic areas (e.g., north-facing slopes) while the probability of forest loss was higher in drier/sunnier areas (e.g., south-facing slopes). Human population density was positively related with the probability of forest loss while negatively related with the probability of forest recovery.…”

Section: Influence Of Conservation Policies On Forest Cover Dynamicsmentioning

confidence: 99%

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Effects of Natural Disasters on Conservation Policies: The Case of the 2008 Wenchuan Earthquake, China

Viña

Chen

McConnell

et al. 2010

AMBIO

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Conservation policies are increasing in response to human-induced ecosystem degradation, but little is known about their interplay with natural disasters. Through an analysis of satellite imagery and field data we evaluated the impacts of a devastating earthquake on forest recovery and avoided forest loss estimated to have been obtained by two of the largest conservation programs in the world. Results show that more than 10% of the forests in Wenchuan County, Sichuan province, China were immediately affected by the 2008 earthquake, offsetting some gains in forest cover observed since the enactment of the conservation programs. But without the enactment of these conservation programs, the combined effects of human disturbance and earthquake-induced landslides could have severely reduced the region's forest cover. The continuation-and enhancement-of incentives for participation in conservation programs will be important for reducing the environmental impacts of the combined effects of human disturbance and natural hazards not only in the study area but also in many disaster-prone regions around the world.

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The Topographic Relative Moisture Index: An Approach to Soil-Moisture Assessment in Mountain Terrain

Cited by 222 publications

References 22 publications

Eight nonnative plants in western Oregon forests: Associations with environment and management

Eight nonnative plants in western Oregon forests: Associations with environment and management

Historical and current landscape‐scale ponderosa pine and mixed conifer forest structure in the Southern Sierra Nevada

Effects of Natural Disasters on Conservation Policies: The Case of the 2008 Wenchuan Earthquake, China

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