Geology topics

Jason Sibold

Publications and source records attributed to Jason Sibold.

4 recordsLinked to original sources

USGS2016

Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem

Drought has long been recognized as a driving mechanism in the forests of western North America and drought-induced mortality has been documented across genera in recent years. Given the frequency of these events are expected to increase in the future, understanding patterns of mortality and plant response to severe drought is important to resource managers. Drought can affect the functional, physiological, structural, and demographic properties of forest ecosystems. Remote sensing studies have documented changes in forest properties due to direct and indirect effects of drought; however, few studies have addressed this at local scales needed to characterize highly heterogeneous ecosystems in the forest-shrubland ecotone. We analyzed a 22-year Landsat time series (1985–2012) to determine changes in forest in an area that experienced a relatively dry decade punctuated by two years of extreme drought. We assessed the relationship between several vegetation indices and field measured characteristics (e.g. plant area index and canopy gap fraction) and applied these indices to trend analysis to uncover the location, direction and timing of change. Finally, we assessed the interaction of climate and topography by forest functional type. The Normalized Difference Moisture Index (NDMI), a measure of canopy water content, had the strongest correlation with short-term field measures of plant area index ( R 2 = 0.64) and canopy gap fraction ( R 2 = 0.65). Over the entire time period, 25% of the forested area experienced a significant ( p -value < 0.05) negative trend in NDMI, compared to less than 10% in a positive trend. Coniferous forests were more likely to be associated with a negative NDMI trend than deciduous forest. Forests on southern aspects were least likely to exhibit a negative trend while north aspects were most prevalent. Field plots with a negative trend had a lower live density, and higher amounts of standing dead and down trees compared to plots with no trend. Our analysis identifies spatially explicit patterns of long-term trends anchored with ground based evidence to highlight areas of forest that are resistant, persistent or vulnerable to severe drought. The results provide a long-term perspective for the resource management of this area and can be applied to similar ecosystems throughout western North America.

Colorado, Utah, Wyoming↗

USGS2015

Mapping forest functional type in a forest-shrubland ecotone using SPOT imagery and predictive habitat distribution modelling

The availability of land cover data at local scales is an important component in forest management and monitoring efforts. Regional land cover data seldom provide detailed information needed to support local management needs. Here we present a transferable framework to model forest cover by major plant functional type using aerial photos, multi-date Système Pour l’Observation de la Terre (SPOT) imagery, and topographic variables. We developed probability of occurrence models for deciduous broad-leaved forest and needle-leaved evergreen forest using logistic regression in the southern portion of the Wyoming Basin Ecoregion. The model outputs were combined into a synthesis map depicting deciduous and coniferous forest cover type. We evaluated the models and synthesis map using a field-validated, independent data source. Results showed strong relationships between forest cover and model variables, and the synthesis map was accurate with an overall correct classification rate of 0.87 and Cohen’s kappa value of 0.81. The results suggest our method adequately captures the functional type, size, and distribution pattern of forest cover in a spatially heterogeneous landscape.

Colorado, Utah, Wyoming↗

USGS2014

Modeling a historical mountain pine beetle outbreak using Landsat MSS and multiple lines of evidence

Mountain pine beetles are significant forest disturbance agents, capable of inducing widespread mortality in coniferous forests in western North America. Various remote sensing approaches have assessed the impacts of beetle outbreaks over the last two decades. However, few studies have addressed the impacts of historical mountain pine beetle outbreaks, including the 1970s event that impacted Glacier National Park. The lack of spatially explicit data on this disturbance represents both a major data gap and a critical research challenge in that wildfire has removed some of the evidence from the landscape. We utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We incorporate historical aerial and landscape photos, aerial detection survey data, a nine-year collection of satellite imagery and abiotic data. This study presents a remote sensing based framework to (1) relate measurements of canopy mortality from fine-scale aerial photography to coarse-scale multispectral imagery and (2) classify the severity of mountain pine beetle affected areas using a temporal sequence of Landsat data and other landscape variables. We sampled canopy mortality in 261 plots from aerial photos and found that insect effects on mortality were evident in changes to the Normalized Difference Vegetation Index (NDVI) over time. We tested multiple spectral indices and found that a combination of NDVI and the green band resulted in the strongest model. We report a two-step process where we utilize a generalized least squares model to account for the large-scale variability in the data and a binary regression tree to describe the small-scale variability. The final model had a root mean square error estimate of 9.8% canopy mortality, a mean absolute error of 7.6% and an R 2 of 0.82. The results demonstrate that a model of percent canopy mortality as a continuous variable can be developed to identify a gradient of mountain pine beetle severity on the landscape.

Montana↗

USGS2013

Modeling mountain pine beetle disturbance in Glacier National Park using multiple lines of evidence

Temperate forest ecosystems are subject to various disturbances which contribute to ecological legacies that can have profound effects on the structure of the ecosystem. Impacts of disturbance can vary widely in extent, duration and severity over space and time. Given that global climate change is expected to increase rates of forest disturbance, an understanding of these events are critical in the interpretation of contemporary forest patterns and those of the near future. We seek to understand the impact of the 1970s mountain pine beetle outbreak on the landscape of Glacier National Park and investigate any connection between this event and subsequent decades of extensive wildfire. The lack of spatially explicit data on the mountain pine beetle disturbance represents a major data gap and inhibits our ability to test for correlations between outbreak severity and fire severity. To overcome this challenge, we utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We used historical aerial and landscape photos, reports, aerial survey data, a six year collection of Landsat imagery and abiotic data in combination with regression analysis. The use of remotely sensed data is critical in large areas where subsequent disturbance (fire) has erased some of the evidence from the landscape. Results indicate that this method is successful in capturing the spatial heterogeneity of the outbreak in a topographically complex landscape. Furthermore, this study provides an example on the use of existing data to reduce levels of uncertainty associated with an historic disturbance.

Conference Paper↗