Browsing UA Faculty Research by Journal
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burnr : Fire history analysis and graphics in RWe developed a new software package, burnr, for fire history analysis and plotting in the R statistical programming environment. It was developed for tree-ring fire-scar analysis, but is broadly applicable to other event analyses (e.g., avalanches, frost rings, or culturally modified trees). Our new package can read, write, and manipulate standard tree-ring fire history FHX files, produce fire-demography charts, calculate fire frequency and seasonality statistics, and run superposed epoch analysis (SEA). A key benefit of burnr is that it enables automation of analyses and plotting, especially for large data sets. The package also facilitates creative plotting, mapping, and analyses when combined with the thousands of packages available in R. In this paper, we describe the basic functionality of burnr and introduce users to fire history analyses in R.
Dendroclimatic analysis of Pinus peuce Griseb. at subalpine and treeline locations in Pirin Mountains, BulgariaTree rings are a natural archive containing valuable information about environmental changes. Among the most sensitive ecosystems to such changes are high-mountain forests. Tree-ring series from such locations are exceptionally valuable both for climate reconstructions and for studying the effects of climate changes on forest ecosystems. The objective of our study is to present new long tree-ring width chronologies of Pinus peuce Griseb. from several locations at Pirin Mountains in southwestern Bulgaria, to explore their correlation with monthly temperatures and precipitation in the research area and to assess their potential for climate reconstruction. We built three long-term index chronologies for the radial increment of P. peuce from treeline locations in the study region. The longest chronology spans 675 years. We studied the impact of monthly air temperature and precipitation on its growth for the past 86 years using multiple regression analysis. Our analysis shows that P. peuce growth is positively influenced by high temperatures at the end of the previous growing season, especially at the two sites in Banderitsa valley until the middle of the 1970s, and negatively affected by cold winters. In some of the sample plots its growth was also positively correlated with high summer temperatures. However, even at these high altitudes in some of the locations on steep slopes P. peuce showed signs of negative impact of drought during the hottest summer months (especially in August). Our chronologies contribute to the paleoclimatic record for southwestern Bulgaria, which could provide baseline information about past climate variability and improve our understanding of current and future environmental changes.
dfoliatR: An R package for detection and analysis of insect defoliation signals in tree ringsWe present a new R package to provide dendroecologists with tools to infer, quantify, analyze, and visualize growth suppression events in tree rings. dfoliatR is based on the OUTBREAK program and builds on existing resources in the R computing environment and the well-used dp1R package. It is designed to aid research in the ecology of insect defoliation events and to reconstruct defoliator outbreak chronologies, but can be applied to other studies where host-non-host comparisons are useful. dfoliatR performs an indexing procedure to remove climatic signals in the host-tree series that are represented in the non-host chronology, or other annually-resolved climate series. It then infers defoliation events in individual trees based on user-specified thresholds. Site-level analyses identify outbreak events that synchronously affect user-defined numbers or proportions of involved host trees. Functions are provided for summary statistics and graphics of tree- and site-level series. We evaluated dfoliatR against OUTBREAK, using eight datasets including 222 host-trees, and found that dfoliatR improves on OUTBREAK with greater user control, identification of defoliation events, computing capacity, and both the statistical summary and graphical outputs. We provide two example data sets and script to enable users to gain familiarity with the package and its capabilities. The source code is available in the Comprehensive R Archive Network (CRAN) and on GitHub.
Seasonal and synoptic climatic drivers of tree growth in the Bighorn Mountains, WY, USA (1654–1983 CE)In the United States' (US) Northern Rockies, synoptic pressure systems and atmospheric circulation drive interannual variation in seasonal temperature and precipitation. The radial growth of high-elevation trees in this semi-arid region captures this temperature and precipitation variability and provides long time series to contextualize instrumental-era variability in synoptic-scale climate patterns. Such variability in climate patterns can trigger extreme climate events, such as droughts, floods, and forest fires, which have a damaging impact on human and natural systems. We developed 11 tree-ring width (TRW) chronologies from multiple species and sites to investigate the seasonal climatic drivers of tree growth in the Bighorn Mountains, WY. A principal component analysis of the chronologies identified 54% of shared common variance (1894-2014). Tree growth (expressed by PC1) was driven by multiple seasonal climate variables: previous October and current July temperatures, as well as previous December and current April precipitation, had a positive influence on growth, whereas growth was limited by July precipitation. These seasonal growth-climate relationships corresponded to circulation patterns at higher atmospheric levels over the Bighorn Mountains. Tree growth was enhanced when the winter jet stream was in a northward position, which led to warmer winters, and when the spring jet stream was further south, which led to wetter springs. The second principal component, explaining 19% of the variance, clustered sites by elevation and was strongly related to summer temperature. We leverage this summer temperature signal in our TRW chronologies by combining it with an existing maximum latewood density (MXD) chronology in a nested approach. This allowed us to reconstruct Bighorn Mountains summer (June, July, and August) temperature (BMST) back to 1654, thus extending the instrumental temperature record by 250 years. Our BMST reconstruction explains 39-53% of the variance in regional summer temperature variability. The 1830s were the relatively coolest decade and the 1930s were the warmest decade over the reconstructed period (1654-1983 CE) - which excludes the most recent 3 decades. Our results contextualize recent drivers and trends of climate variability in the US Northern Rockies, which contributes to the information that managers of human and natural systems need in order to prepare for potential future variability.