Land Condition Trend Analysis Research Articles

Plant community and bare ground trends on Fort Riley, Kansas: Implications for monitoring of a highly disturbed landscape

The Land Condition Trend Analysis (LCTA) program was developed by the US Army and implemented on Fort Riley, Kansas, to monitor trends in plant communities so that managers could maintain quality training lands without the loss of ecological diversity. As a standard protocol, vegetation surveys using the point-intercept method were conducted from 1994–2001. Presence of bare ground, soil erosion, and military vehicle traffic were also recorded. At the community level, species richness usually fluctuated < 10% annually and declined 6% from 1994–2001. Species richness per plot increased from 1994 to 2001 by 6.5% as compared to the 1994 estimate. Annual species richness of noxious plants ranged from 18–26 species; noxious species per plot averaged 1.0–2.4 species annually with higher estimates usually observed in grassland (vs. woodland) habitats. Modest year-to-year changes were noted at the species level for the most frequently observed species based on an index of relative difference. Two noxious plant species, sericea lespedeza (Lespedeza cuneata) and Johnsongrass (Sorghum halepense), first detected during the second year of monitoring, expanded their distribution considerably on the fort. This expansion may have resulted when mechanized training facilitated transport of seed on vehicles from one training area to another. The patterns of expansion (both on a plot and on a training area basis) by these two noxious species revealed that our analysis approach may be useful for detecting early stages of infestations on this highly disturbed landscape. Bare ground conditions increased on an average of 1.5% per year, but may not be completely attributable to military training activities. Because there appears to be little year-to-year fluctuation in the diversity of the plant communities and trends for most individual plant species monitored on Fort Riley, we recommend detailed plant surveys not be conducted annually. An exception would be monitoring of noxious plant species with a method other than the point-intercept technique, which is extremely time-consuming.

Assessing and predicting changes in vegetation cover associated with military land use activities using field monitoring data at Fort Hood, Texas

We assessed short-term impacts of changes in military training load on vegetative cover at Fort Hood, TX. From 1989 to 1995, permanent field transects were monitored for vegetative cover and land use disturbance using standard army monitoring methods [Land Condition Trend Analysis (LCTA)]. Land use intensity (training load) was quantified and used to develop a model to predict future vegetation cover values. We found that standard Army monitoring methods detected changes in installation resources associated with changes in training load. Increased training loads were associated with increased measures of disturbance, decreased ground cover, and decreased aerial vegetative cover. We found that the spatial pattern of disturbance and vegetation cover remained relatively constant over the study period despite large variations in overall training load. Our model used the consistency in spatial cover patterns over time and the strong relationship between training load and vegetation cover to predict the impact of future training loads on vegetation.

A Comprehensive Approach to Identifying Monitoring Priorities of Small Landbirds on Military Installations

Military installations provide important native habitat for songbirds, including many species that have experienced population declines in recent decades. As part of the Land Condition Trend Analysis (LCTA) program to monitor animal populations on military lands, we surveyed small (<250 g) breeding landbirds on 60 permanent plots on the Fort Riley Military Installation in northeastern Kansas from 1991 to 2002. During this period, species richness averaged 39.0 species (SE 0.9)/year and mean species richness per plot ranged from 3.6 species (SE = 0.2)/plot (1999) to 7.5 species (SE = 0.3)/plot (1992). Turnover (the appearance and disappearance of species on all plots from one year to the next) ranged from 5 species (2000-2001) to 16 species (1992-1993) and was driven primarily by turnover of woodland species. We developed an index of relative difference (C) to evaluate relative trends of local populations and found that 25 species declined, 15 species increased, and 7 did not change. Based on migration assemblages, more resident species (6 of 10) and more short-distant migrants (9 of 12) decreased than long-distance migrants (10 vs. 11). Our analysis of major vegetation communities on plots showed few changes in the quantity of habitats (grassland vs. woodlands) during the study. Our results indicate that Fort Riley provides important habitats for many landbirds, particularly those that require grasslands for breeding. Several species exhibited local declines when compared to the regional Breeding Bird Survey routes. We offer an approach that evaluates population changes of small landbirds and provides objective inputs for conservation directives. These can be adopted easily for use on military installations (that use LCTA), parks, and wildlife refuges that have data from annual breeding bird surveys.

Comparison of 2 Techniques for Monitoring Vegetation on Military Lands

The U.S. Army is responsible for preparing a well-trained combat force while maintaining the ecological diversity and integrity of the lands it manages. The ability to efficiently collect data that accurately capture plant community diversity and percent composition is imperative to proper monitoring and land management of military lands. To ensure that the dual goals of military training and land stewardship are met on an army-wide basis, the U.S. Army Land Condition-Trend Analysis (LCTA) Program was developed. The LCTA Program specifies the Army's standard methodology for the collection, analysis, and reporting of natural resource data used for land inventory and monitoring. However, the LCTA sampling technique was developed in Colorado and Texas and little information is available on whether these methods are suitable for vegetation inventory and monitoring in other grassland ecosystems. This study compares LCTA measures of species richness and composition with quadrat sampling in the transitional area between the tall- and mixed-grass prairies of Camp Gilbert C. Grafton (South Unit) in North Dakota. Species richness was 67% higher when sampling with quadrats than using the LCTA technique, suggesting that LCTA samples did not detect a third of the plants present. Compared with the quadrat technique, LCTA samples overestimated the community contribution of Bouteloua gracilis (H.B.K.) Lag. ex Steud. (blue grama) and underestimated proportions of forbs and sedges. Moreover, LCTA samples are labor intensive and time consuming to collect. Other sampling methods may be needed to detect shifts in species composition towards a less desirable plant community or decreases in biodiversity that may be due to land-use. Thus, it is important for Camp Gilbert C. Grafton (South Unit) to re-evaluate the current standard methodology for monitoring the impacts of military training. Since military installations are located in many different ecosystems, it may be necessary for other installations to likewise examine the usefulness of LCTA techniques in their ecosystems. DOI:10.2458/azu_jrm_v56i5_prosser

Comparison of 2 techniques for monitoring vegetation on military lands

The U.S. Army is responsible for preparing a well-trained combat force while maintaining the ecological diversity and integrity of the lands it manages. The ability to efficiently collect data that accurately capture plant community diversity and percent composition is imperative to proper monitoring and land management of military lands. To ensure that the dual goals of military training and land stewardship are met on an army-wide basis, the U.S. Army Land Condition-Trend Analysis (LCTA) Program was developed. The LCTA Program specifies the Army's standard methodology for the collection, analysis, and reporting of natural resource data used for land inventory and monitoring. However, the LCTA sampling technique was developed in Colorado and Texas and little information is available on whether these methods are suitable for vegetation inventory and monitoring in other grassland ecosystems. This study compares LCTA measures of species richness and composition with quadrat sampling in the transitional area between the tall- and mixed-grass prairies of Camp Gilbert C. Grafton (South Unit) in North Dakota. Species richness was 67% higher when sampling with quadrats than using the LCTA technique, suggesting that LCTA samples did not detect a third of the plants present. Compared with the quadrat technique, LCTA samples overestimated the community contribution of Bouteloua gracilis (H.B.K.) Lag. ex Steud. (blue grama) and underestimated proportions of forbs and sedges. Moreover, LCTA samples are labor intensive and time consuming to collect. Other sampling methods may be needed to detect shifts in species composition towards a less desirable plant community or decreases in biodiversity that may be due to land-use. Thus, it is important for Camp Gilbert C. Grafton (South Unit) to re-evaluate the current standard methodology for monitoring the impacts of military training. Since military installations are located in many different ecosystems, it may be necessary for other installations to likewise examine the usefulness of LCTA techniques in their ecosystems.

Detecting changes in natural resources using Land Condition Trend Analysis data.

The Land Condition Trend Analysis (LCTA) program is the US Army's standard for land inventory and monitoring, employing standardized methods of natural resources data collection, analyses, and reporting designed to meet multiple goals and objectives. Critical to using LCTA data in natural resources management decisions is the ability of the LCTA protocols to detect changes in natural resources. To quantify the ability of LCTA protocols to detect resource changes, power analysis techniques were used to estimate minimum detectable effect sizes (MDES) for selected primary and secondary management variables for three Army installations. MDES for a subset of primary variables were estimated using data from 27 installation LCTA programs. MDES for primary and secondary variables varied widely. However, LCTA programs implemented at larger installations with lower sampling intensities detected changes in installation resources as well as programs implemented at smaller more intensively sampled installations. As a national monitoring program that is implemented at individual installations, LCTA protocols provide relatively consistent monitoring data to detect changes in resources despite diverse resource characteristics and implementation constraints.

Evaluation of Land Condition Trend Analysis for Birds on a Kansas Military Training Site

/ Land condition trend analysis (LCTA) is a long-term monitoring program used on military training lands to identify ecological changes that result from training and management activities. We initiated LCTA at the Kansas Army National Guard Training Facility (KANGTF) in Saline County, Kansas, in March 1998. This paper evaluates the LCTA methodology for birds by comparing LCTA results with a modified methodology designed to place sampling transects in field-identified rather than satellite-identified land-cover types. In the satellite-identified land-cover types developed at the site, grassland habitats included a large component of woody vegetation, which resulted in poor resolution of bird assemblages associated with the different land-cover types. Using these cover classes, mixed grass prairie included five grass/forb (g/f) and 10 woody-dependent species; old-field included four g/f and four woody-dependent species; and riparian included one g/f and six woody-dependent species. LCTA sampling was too limited in the ecologically important riparian woodland habitat with the result that bird species were not adequately sampled there. In the alternate sampling strategy, we identified three land-cover classes (grassland, hedgerow, and riparian woodland) by field reconnaissance and increased sampling in the riparian woodland. Grassland included six g/f and three woody-dependent species; hedgerow included six g/f and 20 woody-dependent species, and riparian included two g/f and 19 woody-dependent species. The modifications greatly improved the resolution of bird assemblages associated with land-cover classes at the KANGTF. Use of the alternative sampling method should improve the ability to detect long-term trends in the bird communities.

Effects of Temporal Variability in Ground Data Collection on Classification Accuracy

This research tested whether the timing of ground data collection can significantly impact the accuracy of land cover classification. Ft. Riley Military Reservation, Kansas, USA was used to test this hypothesis. The U.S. Army's Land Condition Trend Analysis (LCTA) data annually collected at military bases was used to ground truth disturbance patterns. Ground data collected over an entire growing season and data collected one year after the imagery had a kappa statistic of 0.33. When using ground data from only within two weeks of image acquisition the kappa statistic improved to 0.55. Potential sources of this discrepancy are identified. These data demonstrate that there can be significant amounts of land cover change within a narrow time window on military reservations. To accurately conduct land cover classification at military reservations, ground data need to be collected in as narrow a window of time as possible and be closely synchronized with the date of the satellite imagery.

Multi-dimensional sphere model and instantaneous vegetation trend analysis

The Multi-Dimensional Sphere Model (MDSM), a new method for multivariate instantaneous trend analysis, is introduced. The model handles three subscript data, Z ( i, j, k) , e.g., for vegetation analysis, i, j and k are species, quadrats and time, respectively. The MDSM uses species, or species groups, as dimensions of a multi-dimensional space, and quadrats as points (vectors) in the space. The quadrats are standardized to 1.0 by division by their vector length, i.e., the square root of the sum of the squares of the components of a quadrat, q (i) = q (i) √[Σ q 2 (i)] . All quadrats are projected onto the unit hypersphere. This maintains the composition information of each species for every quadrat in the data set, and makes all quadrats comparable because their vector lengths equal 1.0. The MDSM synthesizes the quadrats into state vectors representing the vegetation, z′ ( i) = Σ q′ ( i, j) . When performing trend analysis, the MDSM defines the quotient of components of previous ( k − 1) and present ( k) state vectors as an instantaneous trend at a given time. This is referred to as a trend vector, and describes vegetation composition change over time, t (k) = z′ (k) z′ (k − 1) The components of a trend vector (here called the t-value of the species) carry information from both previous and present states for species and community. This trend can then be extended to predict future states of the vegetation, p (k + 1) = z (k) ∗ t (k) . The MDSM combines correlation analysis, cluster analysis, trend analysis, and prediction of future vegetation states, making it a powerful and promising multivariate analysis method. The model was tested with data from the Land Condition Trend Analysis program at Fort Carson in southeastern Colorado. The model shows promising results for vegetation trend analysis; however, geometric meaning of the vector quotient is not yet clear. To improve our understanding, comparison with an additive model and a validation analysis are needed.

Correlation of rangeland cover measures to satellite‐imagery‐derived vegetation indices

Abstract Using field data from the U.S. Army's land inventory and monitoring program, a study was conducted to examine the utility in estimating the quantity of vegetation cover with satellite imagery across a large and complex rangeland. The study area used for this investigation was the U.S. Army's Yakima Training Center in central Washington. The Land Condition‐Trend Analysis (LCTA) program at Yakima Training Center has 202 permanent plots located in a randomly stratified manner across the installation. The principle measures taken along the transects were canopy cover and ground cover. Landsat Thematic Mapper imagery collected in May and August of 1992 was used in the analyses. The satellite data coincided with the beginning and end of the field data collection period and were used to derive various vegetation indices including Ratio, TVI, SAVI, and MSAVI. Analysis of correlation of rangeland cover measures and satellite imagery derived vegetation indices were performed. Correlation between the vegeta...

US army land condition-trend analysis (LCTA) program

The US Army Land Condition-Trend Analysis (LCTA) program is a standardized method of data collection, analysis, and reporting designed to meet multiple goals and objectives. The method utilizes vascular plant inventories, permanent field plot data, and wildlife inventories. Vascular plant inventories are used for environmental documentation, training of personnel, species identification during LCTA implementation, and as a survey for state and federal endangered or threatened species. The permanent field plot data documents the vegetational, edaphic, topographic, and disturbance characteristics of the installation. Inventory plots are allocated in a stratified random fashion across the installation utilizing a geographic information system that integrates satellite imagery and soil survey information. Ground cover, canopy cover, woody plant density, slope length, slope gradient, soil information, and disturbance data are collected at each plot. Plot data are used to: (1) describe plant communities, (2) characterize wildlife and threatened and endangered species habitat, (3) document amount and kind of military and nonmilitary disturbance, (4) determine the impact of military training on vegetation and soil resources, (5) estimate soil erosion potential, (6) classify land as to the kind and amount of use it can support, (7) determine allowable use estimates for tracked vehicle training, (8) document concealment resources, (9) identify lands that require restoration and evaluate the effectiveness of restorative techniques, and (10) evaluate potential acquisition property. Wildlife inventories survey small and midsize mammals, birds, bats, amphibians, and reptiles. Data from these surveys can be used for environmental documentation, to identify state and federal endangered and threatened species, and to evaluate the impact of military activities on wildlife populations. Short- and long-term monitoring of permanent field plots is used to evaluate and adjust land management decisions.