Annotated and Abbreviated Core Presentation Tree-ring reconstructions of streamflow and climate and their application to water management An annotated slide presentation - updated June 2010 In this presentation, we will cover the following: How tree-ring reconstructions of streamflow are developed--from the sampling of trees in the field to statistical modeling, What the reconstructions tell us about past hydrologic variability, and How the reconstructions are being used in the planning and management of water resources. This presentation has been adapted from the ones we have given at our technical workshops to water managers and stakeholders around the West. Please visit the TreeFlow Workshops page (http://treeflow.info/workshops.html) for information about those workshops, including presentations more specific to particular basins around the western US. Also, while the presentation is oriented towards the western US, the principles explained here also apply to other locations. The TreeFlow web pages (http://treeflow.info) also provide access to the streamflow reconstruction data (http://treeflow.info/basins.html) and information about specific applications of the data (http://treeflow.info/applications.html). Jeff Lukas Western Water Assessment, University of Colorado Connie Woodhouse University of Arizona & Climate Assessment for the Southwest (CLIMAS)

Dendrochronology: Main products: the science that deals with the dating and study of annual growth layers in wood Fritts 1976 Main products: - Reconstructions of past conditions; continuous time-series of environmental variables (e.g., climate, hydrology) Dates of environmental and human events (e.g., fires, infestations, prehistoric settlement) Tree-ring reconstructions of streamflow (dendrohydrology) constitute a branch of the larger science of dendrochronology, which uses annual tree rings to examine a wide range of past conditions and events.

Tree-ring science and streamflow reconstructions are not new 1900s - Douglass links tree growth and climate in Southwest 1930s - First studies relating tree growth to runoff 1940s - Schulman investigates history of Colorado River flow using tree rings 1960s - Fritts develops modern statistical methods for climate reconstruction 1976 - Stockton and Jacoby reconstruction of Lees Ferry streamflow 1980s – Further refinement of analytical techniques 1990s 2000s – Many new flow reconstructions for western US; major increase in applications to water management Douglass Modern dendrochronology began about 100 years ago, with the work of A. E. Douglass at the University of Arizona. One of the early applications of tree-ring science was the assessment of past hydrologic variability, and by the 1940s, quantitatively derived indices of streamflow for the Colorado River were developed by Edmund Schulman. The conceptual foundations of Schulman’s work are still used today, with major advances in statistical techniques, computing power, and collection of tree-ring data leading to the robust reconstructions of streamflow now available. The “Colorado River Streamflow: A Paleo Perspective” pages (http://treeflow.info/lees/) provide more background on the evolution of streamflow reconstructions for the Colorado River, including the work of Schulman and Stockton and Jacoby. Schulman

How tree rings record climate information Now we explore the nature of the climate signal recorded in the tree-rings, and how it can be interpreted.

Across much of the western US, annual tree growth is limited by moisture availability So: – a dry year leads to a narrow growth ring – a wet year leads to a wide growth ring 1977 1983 Douglas-fir, south-central CO Across the western US, with the exception of the wet coastal regions and the higher mountains, climates are generally arid or semi-arid, and so moisture is the main factor limiting tree growth. Thus, a dry year leads to a narrow growth ring, and a wet year leads to a wide growth ring. Shown here is an image of annual tree rings from 1973-1984 from a Douglas-fir tree growing at about 8000’ in south-central Colorado. The range in ring widths reflects the annual moisture variability, with 1977 being an extremely dry year locally and across the region, and 1983 being an exceptionally wet year. While it varies somewhat by tree species and the region of the West (the northern and northwestern parts of the western US are somewhat different), tree growth usually reflects the antecedent moisture from the fall, winter and spring prior to the summer growing season. Growth also responds to summer precipitation, but it is a less efficient source of moisture for the trees. In other words, the annual ring-width is typically an integrative measure of moisture over a roughly year-long period, corresponding closely to the October-September water year.

The moisture signal recorded by trees in the interior West is particularly strong As suggested by the examples of 1977 and 1983 in the previous slide, individual trees in the West are often remarkably accurate recorders of moisture variability. Here, we show a record of annual (August-July) precipitation across western Colorado in blue, plotted against the measured ring widths for a single pinyon pine tree sampled in western Colorado, in green. The correlation between the two time series over a 70-year period is almost 0.8. This robust moisture signal as recorded in individual trees is the basis for reliable reconstructions of streamflow and climate. We use sampling and data processing techniques designed to enhance the signal. Here, the annual ring widths from one tree are closely correlated to the annual basin precipitation (r = 0.78) from 1930-2002 Our goal is to capture and enhance the moisture signal, and reduce noise, through careful sampling and data processing

Main moisture-sensitive trees in the western US Of all of the tree species that grow in the intermountain western US, three have proven the most useful in reconstructing streamflow and other moisture-related variables: Douglas-fir, ponderosa pine, and pinyon pine. All three are widespread, with Douglas-fir and ponderosa pine occurring in every western state, with pinyon pine occurring in all states from Utah and Colorado south to Mexico. All three are very long-lived, with old trees typically 400-700 years in age, and maximum ages from 900-1300 years. Other tree species in the West can contain useful moisture signals, including limber pine, bigcone Douglas-fir, western juniper, and blue oak. Douglas-fir Ponderosa Pine Pinyon Pine

Stressful sites produce ring series with a stronger moisture signal A ponderosa pine tree growing on a moist site with a high water table and thick soils (shown at left) will not be very responsive to the year-to-year variations in moisture availability, since moisture will be truly limiting to growth in only the driest years, and will tend to have “complacent” ring-width series. The moisture signal captured by the tree rings is relatively weak. A ponderosa pine growing on a dry, or stressful, site with thin soils, rapid runoff, and greater surface heating (i.e., south-facing slope), as shown at left, will have its growth more strongly limited by the moisture conditions that occur each year, and so it will have “sensitive” ring-width series, with a strong moisture signal. from Fritts 1976

Regional scale of moisture variability = regional coherence in the moisture signal In areas where climate is regionally homogeneous over seasonal to annual time scales, the same ring pattern, particularly the narrow rings, will be consistent throughout the trees in this region. In other words, the tree-ring data can capture not only the temporal characteristics of past climate variability but also the spatial characteristics. Here, tree-ring records in Colorado, Arizona, and New Mexico show the years 1748, 1750, and 1752 to have consistently narrow rings, indicating regional drought years. Fire-scar histories from different tree-ring records in this region show widespread fire occurrence in all three years across the Southwest, independently confirming that these three years were indeed dry. Image courtesy of K. Kipfmueller (U. MN) and T. Swetnam (U. AZ)

This moisture signal in tree rings can serve as a proxy for multiple moisture-related variables Annual (water-year) or cool season precipitation Drought indices (e.g., summer PDSI) Snow-water equivalent (SWE) Annual (water-year) streamflow These variables are closely correlated in much of the western US, and trees whose ring widths are a good proxy for one tend to be good proxies for all of them Because the moisture signal in tree rings in the western US integrates weather conditions occurring over the course of several months to a year, that signal can be used to reconstruct different variables that reflect moisture conditions on seasonal to annual timescales. For example, summer PDSI (Palmer Drought Severity Index) is calculated using precipitation and temperature information from the previous 9-12 months, making it a good match for the moisture signal as captured by tree rings.

Ring-width and streamflow - an indirect but robust relationship Like ring width, streamflow integrates the effects of precipitation and evapotranspiration, as mediated by the soil Although it might seem to make sense to sample trees that are growing right next to a river in order to get a record of past streamflow, these trees will not be very sensitive to hydroclimatic variability because their roots tap into water stored in the flood plain. Instead, trees on dry upland slopes are sampled (see previous slide on stressful sites). These trees can be thought of as dipsticks that reflect the overall soil moisture content in a basin—soil moisture which becomes the annual runoff. Again, the water year (October-September), over which annual streamflow is generally calculated, is a good approximation of the months that contribute to annual growth rings. Because streamflow, like ring width, reflects the influence of both precipitation and evapotranspiration, it is usually has higher correlations with ring width than does precipitation alone. In many cases, it is the winter snowpack that is particularly important to both water year streamflow and the antecedent soil conditions upon which tree growth relies. Image courtesy of D. Meko (U. AZ)

Building a tree-ring chronology Part 3: Building a tree-ring chronology In Part 3 we describe how individual trees are sampled, and the samples processed, to build the tree-ring chronology, which is the basic unit of tree-ring data and the building block for streamflow reconstructions. Chronology: time-series of site ring-width variability and “building block” for the reconstruction

1) Sampling the trees Core 10-30+ trees at a site, same species (pinyon, ponderosa, Doug-fir) Goal: maximize the number of samples throughout the chronology (300-800+ years) Can also core or cut cross-sections from dead trees While a single tree can capture a very robust moisture signal by itself, replication further reduces the influence of tree-specific or non-climatic factors (i.e., noise) and enhances the strength of the signal. The main form of replication is the sampling of many trees at one site, to obtain the aggregate or consensus signal from that group of trees. Two cores are generally collected from each tree, to reduce the effects of within-tree variability due to slightly non-concentric rings.

2) Crossdating the samples Because of the common climate signal, the pattern of wide and narrow rings is highly replicated between trees at a site, and between nearby sites This allows crossdating: the assignment of absolute dates to annual rings (not just ring-counting) 1900 1910 1920 1930 Two Douglas-fir trees south of Boulder, CO There are three types of ring anomalies that would make a simple ring-count depart from the true annual sequence of growth: Micro rings: In very unfavorable (dry) years, a tree may grow a very thin layer of new wood, and the resulting ring may be so small and difficult to see that it will be missed during a ring count. Missing or absent rings: In the worst drought years, like 2002, no or virtually no growth will occur, and no annual ring will be seen in a core or cross-section. On the driest and most stressful sites, over 10% of the annual rings in any one tree may be absent, though a more typical figure is 1% to 4%. We will know these rings are missing because they will be present in trees that are growing in more favorable locations at that site. False rings: If there is a very dry period in the middle of the summer growing season (as is typical in Arizona and New Mexico, prior to the monsoon), the tree may begin to shut down its growth processes and form the dark band of latewood which indicates the end of the growing season. Then when the rains return in late summer, the tree will resume “normal” growth, and then finally put on a true latewood band as fall approaches. So the tree forms what at first glance appears to be two annual rings. By crossdating--comparing and matching the ring-width patterns among multiple trees, and multiple sites—we can identify these ring anomalies and ensure that each ring is assigned to the exact calendar year. This is critical if the tree-ring widths are to be calibrated with annual records of streamflow or climate. For an online exercise to practice cross dating, see: http://www.ltrr.arizona.edu/skeletonplot/introcrossdate.htm When cored, the current year of growth is the first ring next to the bark

Crossdating allows the extension of tree-ring records back in time using living and dead wood Crossdating also allows the dating of samples of dead wood (where the outside ring is not previously known) and incorporating those samples into the overall ring-width chronology from a site. In this way, tree-ring records can extend back much further than the maximum lifespans of living trees. Here, wood from an archeological context is shown in “C” being used in the chronology. In practice, such wood is only used for reconstructing climate where it is locally abundant and there is a long history of occupation, mainly the Colorado Plateau, home of ancestral and modern Puebloans. Dead wood in its original setting (as shown by “B”), in the form of upright snags, downed logs, and stumps, is used across the West in streamflow and climate reconstructions. Image courtesy of LTRR (U. AZ)

3) Measuring the samples Computer-assisted measurement system with sliding stage captures position of core to nearest 0.001mm (1 micron) Output from measurement system are ring-width series stage Once all of the samples are crossdated, every ring is measured on a computer-assisted measuring system, in which a knob is turned to slowly move the sample across the microscope’s field of view. When a ring boundary is aligned with the microscope’s crosshairs, the push of a button records the position of the core (and thus the width of the ring) to the nearest 0.001 mm (1 micron). For comparison, typical rings from moisture-sensitive trees are between 0.1 and 1.5 mm wide (100 to 1500 microns), with the smallest “micro” rings being about 0.02 mm (20 microns) wide.

Subset of recently collected chronologies, including many of those used in the latest Colorado River reconstructions Shown here is a subset of the chronologies mapped in the previous slide, plus others collected since 2003, covering Colorado and parts of the surrounding states. These chronologies were all developed by Connie Woodhouse, Jeff Lukas, and colleagues at the University of Colorado - INSTAAR Dendrochronology Lab between 1999 and 2008. Many of these chronologies contribute to the latest streamflow reconstructions for the Colorado River basin, which are described later. Note that all of the chronologies are from Douglas-fir, pinyon pine, or ponderosa pine.