Modeling endemic bark beetle populations in southwestern

Transcription

1 Modeling endemic bark beetle populations in southwestern ponderosa pine forests Christopher Garza 1, Barbara Bentz 2, Andrew Birt 1, Robert Coulson 1, Diana Doan-Crider 1 1 Knowledge Engineering Lab, Texas A&M University 2 USFS Rocky Mountain Research Station

2 Study Organisms

3 Pine Beetle Dynamics Pine beetles phase between outbreak and endemic population levels Outbreaks have economic, ecological, and social impacts Epidemic populations or post-epidemic conditions are studied most often Endemic bark beetle populations are understudied but could provide insight to the cause of outbreaks (Bentz et al. 1993)

4 Endemic bark beetle dispersal Advantages Disadvantages Advantages Disadvantages High number of beetles for a mass attack Nearby trees are not likely to be susceptible Increased likelihood of finding an weak tree Lower density of beetles for a mass attack Many opportunities for finding a mate Genes stay within the population Opportunity to spread genes Chance of not finding a mate A short flight is safer than a long flight High density of beetles could attract predators Lower density may attract fewer predators Dangers and caloric cost of a long flight

5 Bark beetle dispersal paradox Probab Beet tle bility Density of at (# ttack #/m 2 ) Beetle Density with Movement Tree Health and Probability of Attack Damaged Susceptible Resistant Number Distance of From beetles Host Tree (m) Distance (m) Density (#/m 2 )

6 Goal and Objectives To estimate the distribution of endemic populations across a landscape and to study how the populations persist through time 1. Analyze endemic bark beetle attack data and forest/tree health conditions Develop a model that allows us to estimate the probability of a beetle attacking a tree based on the tree and stand conditions 1. Use remotely sensed data and ground truth data to create a simulated arena with information about the configuration and condition of each individual tree 2. Project the spatial and temporal patterns of endemic bark beetles across a landscape and, given the life-history of the insect, study the connectivity i of susceptible trees

7 Goal and Objectives

8 Study Area Bark beetle attack data 45 sites on the Colorado Plateau Sites established in the early 90 s Both beetle and forest health data collected

9 Numb ber of Atta acks Field Data Bark beetle attack data 20 years of data from study plots Forest data Tree species, diameter at breast height, basal area, height, growth, and health conditions Successful Bark Beetle Attacks 1993 attack rate: attack rate: Beetle Data Beetle species and kind of attack (pitchout, strip, kill) Spatial and temporal data Year

10 Field Data Analysis Bark beetle attack data Number of trees Number of trees Attacks per DBH Tree Count Attack rate 1992 Attack rate DBH (in) Attacks per DBH Tree Count Attack rate 1994 Attack rate DBH (in) Attack rate Attack rate

11 Spatio-temporal p data of hosts Aerial Imagery NDVI Reclassified Image

12 Conclusion and future work Endemic bark beetle populations are understudied Endemic bark beetle research contributes to our knowledge of triggers that cause epidemic populations Barbara Bentz had the foresight to collect endemic bark beetle data which has provided us with an opportunity to study these populations Analysis of bark beetle attack data can provide a model to predict attack rates of trees Although the bark beetle attack data is at discrete locations within landscape, remote sensing and ground truthing can allow is to estimate continuous information about tree conditions across the landscape By measuring spatial patterns and relating those patterns to stand characteristics, the conditions of trees within those stands can be estimated With information about the configuration and condition of trees in a landscape and the ability to predict attack rates for those trees, we can simulate bark beetles es to try to understand d their population o dynamics and how they can persist through time

13 References Bentz, B.J., Amman, G.D., Logan, J.A., A critical assessment of risk classification systems for the mountain pine beetle. For. Ecol. Manage. 61, Chojnacky, D.C., Bentz, B.J., Logan, J.A., Mountain pine beetle attack in ponderosa pine: comparing methods for rating susceptibility. Research Paper RMRS-26. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, 10 pp.