Mortality behaviors
In this document:
Mortality parameters
Adult Self Thinning
Adult Stochastic Mortality
Aggregated Mortality
BC Mortality
Browsed Stochastic Mortality
Competition Mortality
Density Self-Thinning Mortality
Exponential Growth and Resource-Based Mortality
GMF Mortality
Gompertz Density Self Thinning
Growth and Resource-Based Mortality
Height-GLI Weibull Mortality with Browse
Juvenile Self Thinning
Juvenile Stochastic Mortality
Logistic Bi-Level Mortality
NCI Mortality
Post Harvest Skidding Mortality
Senescence
Stochastic Bi-Level Mortality
Temperature dependent neighborhood survival
Weibull Climate Survival
Weibull Snag Mortality
The mortality behaviors cause tree death due to natural life cycle causes and competition. Tree death due to disturbance is covered by other behaviors.
Mortality behaviors do not actually remove dead trees from memory. They set a flag which marks trees as dead. This is because some other behaviors, such as the Substrate group, have specific interest in dead trees. Dead trees are eventually removed from memory by the Dead tree remover behavior. It is important to include this behavior in your run to avoid incorrect results in behaviors that use dead trees and unacceptably slow model run times.
Mortality parameters
- Adult Background Mortality Rate The proportion of trees that die each year, as a value between 0 and 1. Used by the Adult stochastic mortality behavior.
- Adult Self-Thinning Intercept Intercept of the adult self-thinning linear function. Used by the Adult self-thinning behavior.
- Adult Self-Thinning Slope Slope of the adult self-thinning linear function. Used by the Adult self-thinning behavior.
- Competition Mortality Maximum Parameter (max) The maximum relative increment of growth subject to mortality. Used by the Competition Mortality behavior.
- Aggregated Mortality Annual Kill Amount (0-1) The annual mortality rate for a mortality episode, as a proportion between 0 and 1. Used by the Aggregated Mortality behavior.
- Aggregated Mortality Clump Size Whether the size of a clump of trees to kill is deterministic or chosen from a negative binomial probability distribution. Used by the Aggregated Mortality behavior.
- Aggregated Mortality Clumping Parameter If the size of tree clumps to kill is drawn from a negative binomial probability distribution, this is the clumping parameter for the distribution. This is not required if a deterministic clump size is used. Used by the Aggregated Mortality behavior.
- Aggregated Mortality Number of Trees To Aggregate Determines the size of the clumps of trees killed. If the clump size is deterministic, all clumps will be this size. If the size is to be drawn from a negative binomial probability distribution, then this is the mean clump size. Used by the Aggregated Mortality behavior.
- Aggregated Mortality Return Interval (years) The return interval for mortality episodes. Used by the Aggregated Mortality behavior.
- Browsed Juvenile Background Mortality Rate The proportion of browsed trees that die each year, as a value between 0 and 1. Used by the Browsed Stochastic Mortality behavior.
- Competition Mortality Shape Parameter (Z) Determines the shape of the mortality function. Used by the Competition Mortality behavior.
- DBH at Onset of Senescence, in cm DBH at which senescence takes effect. Used by the Senescence behavior.
- DBH of Maximum Senescence Mortality Rate, as an integer in cm The DBH at which maximum mortality occurs. Trees with a DBH greater than this value experience no further increase in the mortality rate. Used by the Senescence behavior.
- Density Self-Thinning Asymptote (A) The asymptote of the density self-thinning function. Used by the Density Self-Thinning Mortality behavior.
- Density Self-Thinning Density Effect (S) The parameter controlling the density effect of the density self-thinning function. Used by the Density Self-Thinning Mortality behavior.
- Density Self-Thinning Diameter Effect (C) The parameter controlling the effect of neighbor mean diameter of the density self-thinning function. Used by the Density Self-Thinning Mortality behavior.
- Density Self-Thinning Minimum Density for Mortality (#/ha) The minimum density of neighbors, in stems/ha, for density self-thinning mortality. A tree with a lower density of neighbors than this value will not die. Used by the Density Self-Thinning Mortality behavior.
- Density Self-Thinning Neighborhood Radius, in m The maximum radius, in m, within which to search for neighbors to calculate neighbor density for density self-thinning. Used by the Density Self-Thinning Mortality behavior.
- Exponential Growth-Resource - a The mortality at zero growth scaled as a function of the resource. Used by the Exponential Growth and Resource-Based Mortality behavior.
- Exponential Growth-Resource - b The light-dependent mortality parameter. Used by the Exponential Growth and Resource-Based Mortality behavior.
- Exponential Growth-Resource - c The resource-dependent mortality parameter. Used by the Exponential Growth and Resource-Based Mortality behavior.
- Exponential Growth-Resource - d Used by the Exponential Growth and Resource-Based Mortality behavior.
- Gompertz Density Self Thinning - G G in the function for probability of mortality. Used by the Gompertz Density Self Thinning behavior.
- Gompertz Density Self Thinning - H H in the function for probability of mortality. Used by the Gompertz Density Self Thinning behavior.
- Gompertz Density Self Thinning - I I in the function for probability of mortality. Used by the Gompertz Density Self Thinning behavior.
- Gompertz Density Self Thinning - Min Neighbor Height (m) Minimum height for conspecific neighbors to be counted towards density. Used by the Gompertz Density Self Thinning behavior.
- Gompertz Density Self Thinning - Neighbor Search Radius (m) Radius for which to search for conspecific neighbors. Used by the Gompertz Density Self Thinning behavior.
- Growth/Resource - Scaling Factor (rho) Scaling factor to reduce survival at the mode of the survival probability function. Used by the Growth and Resource-Based Mortality behavior.
- Growth/Resource - Function Mode (mu) Determines the mode of the function along a gradient of the resource R (the mode is the optimal niche of a species). Used by the Growth and Resource-Based Mortality behavior.
- Growth/Resource - Survival Increase with Growth (delta) Specifies the increase in survival caused by amount of growth. Used by the Growth and Resource-Based Mortality behavior.
- Growth/Resource - Low-Growth Survival Parameter (sigma) Affects the shape of the survival probability distribution in low-growth conditions. Used by the Growth and Resource-Based Mortality behavior.
- Height-GLI Weibull - a The "a" parameter in the Weibull function for calculating annual mortality. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - b The "b" parameter in the Weibull function for calculating annual mortality. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - c The "c" parameter in the Weibull function for calculating annual mortality. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - d The "d" parameter in the Weibull function for calculating annual mortality. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - Max Mortality (0 - 1) The maximum mortality probability for a species, expressed as a proportion between 0 and 1. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - Browsed a The "a" parameter in the Weibull function for calculating annual mortality for a browsed tree. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - Browsed b The "b" parameter in the Weibull function for calculating annual mortality for a browsed tree. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - Browsed c The "c" parameter in the Weibull function for calculating annual mortality for a browsed tree. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - Browsed d The "d" parameter in the Weibull function for calculating annual mortality for a browsed tree. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Height-GLI Weibull - Browsed Max Mortality (0 - 1) The maximum mortality probability for a browsed tree, expressed as a proportion between 0 and 1. Used by the Height-GLI Weibull Mortality with Browse behavior.
- Include Snags in NCI Calculations Whether or not to include snags when finding competitive neighbors for NCI. Used in the NCI mortality behavior.
- Juvenile Background Mortality Rate The proportion of trees that die each year, as a value between 0 and 1. Used by the Juvenile Stochastic Mortality and Browsed Stochastic Mortality behaviors.
- Juvenile Self-Thinning Intercept Intercept of the juvenile self-thinning linear function. Used by the Juvenile self-thinning behavior.
- Juvenile Self-Thinning Slope Slope of the juvenile self-thinning linear function. Used by the Juvenile self-thinning behavior.
- Light-Dependent Mortality Light-dependent mortality. Used by the GMF mortality and BC morality behaviors.
- Logistic Bi-Level - Low-Light "a" The "a" parameter used in low-light conditions. Used by the Logistic Bi-Level Mortality behavior.
- Logistic Bi-Level - Low-Light "b" The "b" parameter used in low-light conditions. Used by the Logistic Bi-Level Mortality behavior.
- Logistic Bi-Level - High-Light "a" The "a" parameter used in high-light conditions. Used by the Logistic Bi-Level Mortality behavior.
- Logistic Bi-Level - High-Light "b" The "b" parameter used in high-light conditions. Used by the Logistic Bi-Level Mortality behavior.
- Logistic Bi-Level - High-Light Mortality Threshold (0-100) The threshold between low-light and high-light parameters, as a value between 0 and 100. Used by the Logistic Bi-Level Mortality behavior.
- Maximum DBH for Adult Self-Thinning Maximum DBH at which adult self-thinning applies. Above this value, no mortality occurs. Used by the Adult self-thinning behavior.
- Mortality at Zero Growth Mortality rate at zero growth. Used by the GMF mortality and BC morality behaviors.
- NCI Crowding Effect Slope (C) The slope of the curve for neighbor effects. Used in the NCI mortality behavior.
- NCI Crowding Effect Steepness (D) The steepness of the curve for neighbor effects. Used in the NCI mortality behavior.
- NCI Max Radius of Crowding Neighbors, in m The maximum distance from a target tree at which neighbors can have a competitive effect. Used in the NCI mortality behavior.
- NCI Max Survival Probability (0-1) The maximum annual probability of survival, as a value between 0 and 1. Used in the NCI mortality behavior.
- NCI Minimum Neighbor DBH, in cm The minimum DBH for trees of that species to compete as neighbors. Used for all neighbor species, not just those using NCI mortality. Used in the NCI mortality behavior.
- NCI Neighbor DBH Effect (alpha) The effect of the DBH of a neighbor tree on its competitiveness for a target species. Used in the NCI mortality behavior.
- NCI Neighbor Distance Effect (beta) The effect of the distance of a neighbor tree on its competitiveness for a target species. Used in the NCI mortality behavior.
- NCI Neighbor Storm Damage (eta) - Complete (0-1) The fraction to which a neighbor's competitive effect is reduced when the neighbor has sustained complete storm damage. Used in the NCI mortality behavior.
- NCI Neighbor Storm Damage (eta) - Medium (0-1) The fraction to which a neighbor's competitive effect is reduced when the neighbor has sustained medium storm damage. Used in the NCI mortality behavior.
- NCI Shading Effect Coefficient (m) The coefficient in the shading effect equation. Set this value to 0 if you do not wish to use shading. Used in the NCI mortality behavior.
- NCI Shading Effect Exponent (n) The exponent in the shading effect equation. If you set the NCI Shading Effect Coefficient (m) parameter to 0, this value is ignored. Used in the NCI mortality behavior.
- NCI Size Effect Mode, in cm The mode of the size effect curve. Used in the NCI mortality behavior.
- NCI Size Effect Variance, in cm The variance of the size effect curve. Used in the NCI mortality behavior.
- NCI Size Sensitivity to NCI (gamma) The sensitivity of a tree's survival probability to its DBH. Used in the NCI mortality behavior.
- NCI Storm Effect - Complete Damage (0-1) The fraction by which a tree's survival probability is reduced when it has sustained complete storm damage. Used in the NCI mortality behavior.
- NCI Storm Effect - Medium Damage (0-1) The fraction by which a tree's survival probability is reduced when it has sustained medium storm damage. Used in the NCI mortality behavior.
- Species i NCI Lambda The scale of the competitive effect of a neighbor tree's species on the target tree's species. Used in the NCI mortality behavior.
- Post Harvest Skid Mort - Crowding Effect Radius Maximum distance, in m, for neighbors to have a competitive effect. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Pre-Harvest Background Mort Rate Annual mortality rate, 0-1, if no harvest has occurred this run. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Snag Recruitment Background Prob Annual postharvest risk of standing death after harvest effects have completely tapered off. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Snag Recruitment Basic Prob Basic probability of standing death after harvest. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Snag Recruitment Crowding Effect The effect of neighborhood basal area on standing death probability. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Snag Recruitment Rate Param Determines how quickly the effects of harvesting on standing death probability taper off. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Snag Recruitment Skidding Effect Effect of harvest intensity on postharvest probability of standing death. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Windthrow Background Prob Annual postharvest risk of windthrow after harvest effects have completely tapered off. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Windthrow Crowding Effect The effect of neighborhood basal area on windthrow probability. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Windthrow Harvest Basic Prob Basic annual probability for windthrow after a harvest. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Windthrow Harvest Rate Param Determines how quickly the effects of harvesting on windthrow probability taper off. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Windthrow Intensity Effect Intensity effect parameter used for determining risk of windthrow. Used by the
Post Harvest Skidding Mortality behavior.
- Post Harvest Skid Mort - Windthrow Size Effect Size effect term when determining risk of windthrow. Used by the
Post Harvest Skidding Mortality behavior.
- Senescence Mortality Alpha Controls the senescence mortality rate. Used by the Senescence behavior.
- Senescence Mortality Beta Controls the senescence mortality rate. Used by the Senescence behavior.
- Stochastic Bi-Level - High-Light Mortality Probability (0-1) The annual probability of mortality under high-light conditions, as a proportion between 0 and 1. Used by the Stochastic Bi-Level Mortality behavior.
- Stochastic Bi-Level - High-Light Mortality Threshold (0-100) The threshold between low-light and high-light mortality rates, as a value between 0 and 100. Used by the Stochastic Bi-Level Mortality behavior.
- Stochastic Bi-Level - Low-Light Mortality Probability (0-1) The annual probability of mortality under low-light conditions, as a proportion between 0 and 1. Used by the Stochastic Bi-Level Mortality behavior.
- Temp Dependent Neighborhood Surv - A A in the survival function. Used by the Temperature dependent neighborhood survival behavior.
- Temp Dependent Neighborhood Surv - B B in the survival function. Used by the Temperature dependent neighborhood survival behavior.
- Temp Dependent Neighborhood Surv - M M in the survival function. Used by the Temperature dependent neighborhood survival behavior.
- Temp Dependent Neighborhood Surv - N N in the survival function. Used by the Temperature dependent neighborhood survival behavior.
- Temp Dependent Neighborhood Surv - Neigh Search Radius (m) Maximum radius to search for crowding neighbors, in meters. Used by the Temperature dependent neighborhood survival behavior.
- Weibull Annual "a" Parameter for Snag Size Class 1 Mortality Weibull annual "a" parameter for those trees whose DBH is less than or equal to the value in "Upper DBH of snag size class 1". Used by the Weibull snag mortality behavior.
- Weibull Annual "a" Parameter for Snag Size Class 2 Mortality Weibull annual "a" parameter for those trees whose DBH is greater than the value in "Upper DBH of snag size class 1" but less than or equal to the value in "Upper DBH of snag size class 2". Used by the Weibull snag mortality behavior.
- Weibull Annual "a" Parameter for Snag Size Class 3 Mortality Weibull annual "a" parameter for those trees whose DBH is greater than the value in "Upper DBH of snag size class 2". Used by the Weibull snag mortality behavior.
- Weibull Annual "b" Parameter for Snag Size Class 1 Mortality Weibull annual "b" parameter for those trees whose DBH is less than or equal to the value in "Upper DBH of snag size class 1". Used by the Weibull snag mortality behavior.
- Weibull Annual "b" Parameter for Snag Size Class 2 Mortality Weibull annual "b" parameter for those trees whose DBH is greater than the value in "Upper DBH of snag size class 1" but less than or equal to the value in "Upper DBH of snag size class 2". Used by the Weibull snag mortality behavior.
- Weibull Annual "b" Parameter for Snag Size Class 3 Mortality Weibull annual "b" parameter for those trees whose DBH is greater than the value in "Upper DBH of snag size class 2". Used by the Weibull snag mortality behavior.
- Weibull Upper DBH of Snag Size Class 1 The upper DBH value of trees in size class 1. Used by the Weibull snag mortality behavior.
- Weibull Upper DBH of Snag Size Class 2 The upper DBH value of trees in size class 2. Trees with a value greater than this are considered to be in size class 3. Used by the Weibull snag mortality behavior.
- Weibull Climate Survival - Adult Competition Effect "C" The C parameter for the competition effect when the target tree is an adult. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Competition Effect "D" The D parameter for the competition effect when the target tree is an adult. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Competition Gamma The gamma parameter for the competition effect when the target tree is an adult. This controls the response of a target tree to competition as a function of its size. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Max Survival Prob (0-1) The maximum possible annual probability of survival for an adult target tree, expressed as a probability between 0 and 1. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Precip Effect "A" The A parameter for the precipitation effect when the target tree is an adult. Units of precipitation are millimeters per year. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Precip Effect "B" The B parameter for the precipitation effect when the target tree is an adult. Units of precipitation are millimeters per year. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Precip Effect "C" The C parameter for the precipitation effect when the target tree is an adult. Units of precipitation are millimeters per year. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Size Effect X0 The mode of the size effect curve when the target tree is an adult. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Size Effect Xb The variance of the size effect curve when the target tree is an adult. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Temp Effect "A" The A parameter for the temperature effect when the target tree is an adult. The effect is based on mean annual temperature in degrees Celsius. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Temp Effect "B" The B parameter for the temperature effect when the target tree is an adult. The effect is based on mean annual temperature in degrees Celsius. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Adult Temp Effect "C" The C parameter for the temperature effect when the target tree is an adult. The effect is based on mean annual temperature in degrees Celsius. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Competition Effect "C" The C parameter for the competition effect when the target tree is a juvenile. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Competition Effect "D" The D parameter for the competition effect when the target tree is a juvenile. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Competition Gamma The gamma parameter for the competition effect when the target tree is a juvenile. This controls the response of a target tree to competition as a function of its size. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juv Max Survival Prob (0-1) The maximum possible annual probability of survival for a juvenile target tree, expressed as a probability between 0 and 1. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Precip Effect "A" The A parameter for the precipitation effect when the target tree is a juvenile. Units of precipitation are millimeters per year. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Precip Effect "B" The B parameter for the precipitation effect when the target tree is a juvenile. Units of precipitation are millimeters per year. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Precip Effect "C" The C parameter for the precipitation effect when the target tree is a juvenile. Units of precipitation are millimeters per year. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Size Effect X0 The mode of the size effect curve when the target tree is a juvenile. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Size Effect Xb The variance of the size effect curve when the target tree is a juvenile. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Temp Effect "A" The A parameter for the temperature effect when the target tree is a juvenile. The effect is based on mean annual temperature in degrees Celsius. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Temp Effect "B" The B parameter for the temperature effect when the target tree is a juvenile. The effect is based on mean annual temperature in degrees Celsius. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Juvenile Temp Effect "C" The C parameter for the temperature effect when the target tree is a juvenile. The effect is based on mean annual temperature in degrees Celsius. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Max Neighbor Search Radius (m) The maximum distance, in m, at which a neighboring tree has competitive effects on a target tree. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Minimum Neighbor DBH (cm) The minimum DBH for trees of that species to compete as neighbors. Used for all species, not just those using Weibull Climate growth. Used by the Weibull Climate Survival behavior.
- Weibull Climate Survival - Size Effect Minimum DBH The minimum possible DBH for size effect. Trees with a DBH less than this value will use this value in the size effect calculation instead. Used by the Weibull Climate Survival behavior.
Adult self thinning
Self-thinning is a behavior that uses a pseudo-density dependent function designed to increase the death rate in dense uniform-age stands. You specify a maximum DBH at which to apply it - above this DBH a tree will not die. There is nothing in this behavior which makes it specifically for adult trees - the name is to match existing SORTIE conventions.
How it works
Self-thinning uses a simple linear function of probability of mortality as a function of DBH, assuming the tree is below the maximum DBH at which to apply self-thinning. After evaluating this function for a tree, it uses a random number to determine whether the tree dies.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species.
Behavior reference string: adultselfthin
Adult stochastic mortality
This behavior produces a background mortality rate. Individuals within the pool of trees to which this behavior applies are randomly selected to die. There is nothing about this behavior which makes it only applicable to adults. The name conforms to old SORTIE standards and allows it to be
distinguished from the Juvenile stochastic mortality behavior, so that two different rates can be applied to two different groups of trees.
How it works
For each tree, a random number is compared to that species's Adult Background Mortality Rate parameter to determine if it falls in the pool of trees that die.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species.
Behavior reference string: adultstochasticmort
Aggregated Mortality
Aggregated Mortality is similar to the Adult Stochastic Mortality behavior in that it kills trees randomly to match a predetermined mortality rate. However, Aggregated Mortality clumps together the deaths in both time and space.
How it works
Mortality occurs in discrete episodes, which have an average return interval. For any timestep, the probability that a mortality episode will occur is T/RI, where T is the number of years per timestep and RI is the Aggregated Mortality Return Interval (years) parameter. Each timestep, this behavior uses a random number to decide if a mortality episode occurs. Between mortality episodes, this behavior does not kill any trees.
If a mortality episode occurs, this behavior kills some of the total pool of trees to which it has been applied. The base annual mortality rate proportion is given in the Aggregated Mortality Annual Kill Amount (0-1) parameter. Since the parameter gives an annual rate, the actual mortality rate is 1-(1-AD)T, where AD is the annual amount to kill and T is the number of years per timestep.
During a mortality episode, this behavior kills the trees in discrete clumps. The behavior uses a random number with each tree in its pool of eligible trees to decide if that tree dies. If it dies, the behavior also kills the trees closest to it. Only trees to which this behavior has been applied are killed; other neighbors are left alone. The size of these clumps of dead trees can either be deterministic or drawn from a negative binomial probability distribution. This option is set in the Aggregated Mortality Clump Size parameter. If the size is deterministic, the size of all clumps is given in the Aggregated Mortality Number of Trees To Aggregate parameter. If the size is from a negative binomial distribution, that parameter gives the mean, u, for the function
where k, the clumping parameter, is the Aggregated Mortality Clumping Parameter parameter.
If the Aggregated Mortality Return Interval (years) and Aggregated Mortality Number of Trees To Aggregate parameters are both set to 1, then this behavior functions exactly like the Adult Stochastic Mortality behavior.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. Only those trees to which this behavior has been applied will be killed. This behavior can be combined with other mortality behaviors, but for best results, it should be the first one to occur.
Behavior reference string: Aggregated Mortality
BC mortality
BC mortality is a growth-based mortality behavior.
How it works
The BC mortality model evaluates the following function to determine the probability of a tree's mortality:
where:
- m is the probability of mortality
- T is the number of years per timestep
- m1 is the Mortality at Zero Growth parameter
- m2 is the Light-Dependent Mortality parameter
- G is amount of radial growth, in mm/yr, added to the tree's diameter
during T
BC mortality is described in Kobe and Coates 1997.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. Any tree species/type combination to which it is applied must also have a growth behavior applied.
Behavior reference string: bcmortality
Browsed Stochastic Mortality
This simulates the effects of herbivory by allowing different background mortality rates for browsed and unbrowsed trees.
How it works
Whether or not a tree is browsed is determined by the Random browse behavior. For each tree, if it has not been browsed, that species's Juvenile Background Mortality Rate parameter is used; if it has been browsed, the species's Browsed Juvenile Background Mortality Rate parameter is used. A random number is compared to the appropriate rate to decide if the tree dies.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. Any tree species/type combination to which it is applied must also have the Random browse behavior applied.
Behavior reference string: Browsed Stochastic Mortality
Exponential Growth and Resource-Based Mortality
This behavior calculates probability of mortality as a function of growth and some second resource. The identity of the second resource is unimportant and could be anything, from exchangeable calcium levels to soil moisture.
How it works
The probability of mortality for a tree is calculated with the following equation:
Prob = (d + a * R) * exp( -( b + c * R) * G)
where:
- Prob is the annual probability of mortality, as a value between 0 and 1
- R is the amount of the second resource
- G is the amount of radial growth, in mm/yr
- a is the Exponential Growth-Resource - a parameter - the mortality at zero growth scaled as a function of the resource R
- b is the Exponential Growth-Resource - b parameter - the light dependent mortality
- c is the Exponential Growth-Resource - c parameter - the resource dependent mortality
- d is the Exponential Growth-Resource - d parameter
The amount of the second resource is captured in a grid object called Resource. Currently it is up to you to enter a map of the values for this resource grid; for instructions on how to do this, see the Grid Setup Window topic. This behavior does not in any way alter the values in this grid.
The mortality probability as calculated above is an annual probability. For multi-year timesteps, the timestep probability is 1 - (1 - AP)X, where AP is the annual probability and X is the number of years per timestep. Once a tree's timestep survival probability has been calculated, it is compared to a random number to determine whether the tree lives or dies.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. Any tree species/type combination to which it is applied must also
have a growth behavior applied. You must also enter a map of second resource values into the Resource grid.
Behavior reference string: Exponential growth resource mortality
GMF mortality
GMF mortality is a growth-based mortality behavior.
How it works
The GMF mortality model evaluates the following function to determine the probability of a tree's mortality:
m = m1*e-m2G
where:
- m is the probability of mortality
- m1 is the Mortality at Zero Growth parameter, for mortality over 2.5 years (see Kobe et al 1995)
- m2 is the Light-Dependent Mortality parameter, for mortality over 2.5 years (see Kobe et al 1995)
- G is amount of radial growth, in mm/yr, added to the tree's diameter
this timestep
The GMF mortality equation is for a 5 year timestep. The mortality parameters are for a 2.5 year probability of mortality. To calculate the 5 year probability of mortality, SORTIE uses p' = 1 - (1 - p)2.
Once the probability of mortality is calculated for a tree, SORTIE generates a random number to which to compare it to determine whether the tree will live or die.
This model was originally described in Kobe et al 1995.
How to apply it
The GMF mortality function assumes a timestep length of five years, so that must be your timestep length in order to use this behavior. This behavior can be applied to seedlings, saplings, and adults of any species. Any tree species/type combination to which it is applied must also
have a growth behavior applied.
Behavior reference string: gmfmortality
Growth and Resource-Based Mortality
This behavior calculates probability of survival as a function of growth and some second resource. The identity of the second resource is unimportant and could be anything, from exchangeable calcium levels to soil moisture.
How it works
The probability of survival for a tree is calculated with the following equation:
where:
- Prob is the annual probability of survival, as a value between 0 and 1
- R is the amount of the second resource
- G is the amount of radial growth, in mm/yr
- ρ is the Growth/Resource - Scaling Factor (rho) parameter, which is a scaling factor to reduce survival at the mode of the survival probability function
- μ is the Growth/Resource - Function Mode (mu) parameter, which determines the mode of the function along a gradient of the resource R (this corresponds to the optimal niche of a species, meaning where it is the top competitor, the absolute winner of competition)
- δ is the Growth/Resource - Survival Increase with Growth (delta) parameter, which specifies the increase in survival caused by amount of growth
- σ is the Growth/Resource - Low-Growth Survival Parameter (sigma) parameter, which affects the shape of the survival probability distribution in low-growth conditions
The amount of the second resource is captured in a grid object called Resource. Currently it is up to you to enter a map of the values for this resource grid; for instructions on how to do this, see the Grid Setup Window topic. This behavior does not in any way alter the values in this grid.
The survival probability as calculated above is an annual probability. For multi-year timesteps, the timestep probability is APX, where AP is the annual probability and X is the number of years per timestep. Once a tree's timestep survival probability has been calculated, it is compared to a random number to determine whether the tree lives or dies.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. Any tree species/type combination to which it is applied must also
have a growth behavior applied. You must also enter a map of second resource values into the Resource grid.
Behavior reference string: Growth resource mortality
Juvenile self thinning
Self-thinning is a behavior that uses a pseudo-density dependent function designed to increase the death rate in dense uniform-age stands. Unlike adult self-thinning, there is no upper DBH limit applied. There is nothing in this behavior which makes it specifically for juvenile trees - the name is to match existing SORTIE conventions.
How it works
Self-thinning uses a simple linear function of probability of mortality as a function of DBH. After evaluating this function for a tree, it uses a random number to determine whether the tree dies.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species.
Behavior reference string: juvselfthin
Juvenile stochastic mortality
This behavior produces a background mortality rate. Individuals within the pool of trees to which this behavior applies are randomly selected to die. There is nothing about this behavior which makes it only applicable to juveniles. The name conforms to old SORTIE standards and allows it to be distinguished from the Adult stochastic mortality behavior, so that two different rates can be applied to two different groups of trees.
How it works
For each tree, a random number is compared to that species's Juvenile Background Mortality Rate parameter to determine if it falls in the pool of trees that die.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species.
Behavior reference string: juvstochasticmort
Senescence
Senescence mortality provides for an uptick in mortality rates. It is meant to slightly increase the death rate among large adult trees.
How it works
All trees to which senescence is applied are evaluated for senescence mortality. In practice, trees below the onset of senescence DBH very rarely die. The probability of death rises with DBH until the DBH of maximum senescence rate is reached, at which point it levels off.
To assess whether a tree will die due to senescence, the following function is evaluated:
where:
- ms is the probability of mortality
- α (Senescence Mortality Alpha parameter) and β (Senescence Mortality Beta parameter) control the magnitude of the uptick
- DBH is the tree's DBH, in cm
- DBHs is the DBH at Onset of Senescence, in cm parameter
The probability is compared to a random number to determine whether the individual tree will die.
How to apply it
Senescence may be applied to saplings and adults of any species. It cannot be applied to seedlings.
Behavior reference string: senescence
Weibull snag mortality behavior
This behavior controls snag fall. Snags are standing dead trees. Obviously, they can't die again, so the word "mortality" is a bit of a misnomer. We call the behavior a mortality behavior because it functionally fits in this behavior class.
Snags that are "killed" by this behavior are considered to have fallen over. If Substrate behaviors are enabled, then these fallen trees are available to become new fresh log substrate. Any that are not picked up by substrate will be dealt with by the Dead tree remover behavior.
How it works
The behavior uses a Weibull function to determine the number of snags of a certain age left standing at a given time. The equation is:
where:
- S is proportion of snags still standing, between 0 and 1
- a and b are Weibull parameters (Weibull Annual "a" Parameter for Snag Size Class X Mortality parameter and Weibull Annual "b" Parameter for Snag Size Class X Mortality parameter)
- T is the snag age in years
Different sizes of snags fall at different rates. This behavior allows you to define three snag size classes and enter different "a" and "b" parameters for each.
A random number is used against this equation for a given tree to determine if it falls in the current timestep.
How to apply it
This behavior can be applied to snags of any species.
Behavior reference string: weibull snag mortality
NCI mortality
This behavior uses the effects of neighbor competitiveness to influence tree survival ("NCI" stands for neighborhood competition index). A tree's maximum potential probability of survival is reduced due to competitiveness and several other possible factors. You can use certain parameter values to turn these influences on and off to reflect the conditions appropriate for your run.
How it works
For a tree, the annual probability of survival is calculated as:
Prob. Survival = Max Survival * Size Effect * Shading Effect * Crowding Effect * Storm Effect
Max Survival is the NCI Max Survival Probability (0-1) parameter. Storm Effect, Shading Effect, Size Effect, and Crowding Effect are all optional factors which act to reduce the maximum survival probability and will vary depending on the conditions a tree is in. All values are bounded between 0 and 1.
Size Effect is calculated as:
where:
- DBH is of the target tree, in cm
- X0 is the NCI Size Effect Mode, in cm parameter
- Xb is the NCI Size Effect Variance, in cm
Shading Effect is calculated as:
where:
- m is the NCI Shading Effect Coefficient (m) parameter
- n is the NCI Shading Effect Exponent (n) parameter
- S is the amount of shade cast by neighbors, from 0 (no shade) to 1 (full shade). This value should come from the Sail light behavior.
This effect is not required. To omit the Shading Effect, set the NCI Shading Effect Coefficient (m) parameter to 0.
Crowding Effect is calculated as:
where:
- C is the NCI Crowding Effect Slope (C) parameter
- D is the NCI Crowding Effect Steepness (D) parameter
- DBH is of the target tree, in cm
- γ is the NCI Size Sensitivity to NCI (gamma) parameter for the target tree's species
- NCI is this tree's NCI value (equation below)
The NCI value sums up the competitive effect of all neighbors with a DBH at least that of the NCI Minimum Neighbor DBH, in cm parameter, out to a maximum distance set in the NCI Max Radius of Crowding Neighbors, in m parameter. The competitiveness of a neighbor increases with the neighbor's size and decreases with distance and storm damage to the neighbor (optional). The neighbor's species also matters; the effect depends on the relationship between the target species and the neighbor species. Seedlings never compete. You set whether or not snags compete in the Include Snags in NCI Calculations parameter.
The crowding effect is optional. You can omit it by setting either the NCI Crowding Effect Slope (C) or NCI Max Radius of Crowding Neighbors, in m parameters to 0.
NCI is calculated as:
where:
- the calculation sums over j = 1...S species and k = 1...N neighbors of each species of at least a DBH of NCI Minimum Neighbor DBH, in cm, out to a distance of NCI Max Radius of Crowding Neighbors, in m
- ηk is the storm damage parameter of the kth neighbor, depending on the damage status (optional). If the neighbor is undamaged, the value is 1. If the neighbor has medium damage, the value is the NCI Neighbor Storm Damage (eta) - Medium (0-1) parameter for the target species. If the neighbor has complete damage, the value is the NCI Neighbor Storm Damage (eta) - Complete (0-1) parameter for the target species. To omit the storm damage term, set all values for the above two parameters to 1.
- α is the NCI Alpha parameter for the target tree's species
- β is the NCI Beta parameter for the target tree's species
- DBHjk is the DBH of the kth neighbor, in cm
- q is the NCI DBH Divisor (q) parameter. Set this to a value greater than 1 to rescale the competitive effects of neighbors
- λik is the Species j NCI Lambda parameter for the target species relative to the kth neighbor's species
- distanceik is distance from target to neighbor, in m
The value of Damage Effect is optional. If you elect not to use storms in your run, set all values in the NCI Damage Effect - Medium Storm Damage (0-1) and NCI Damage Effect - Complete Storm Damage (0-1) parameters to 1. If you are using storms, then the value of Damage Effect depends on the tree's damage category. If the tree is undamaged, Damage Effect equals 1. If the tree has medium storm damage, the value is the NCI Damage Effect - Medium Storm Damage (0-1) parameter. If the tree has complete storm damage, the value is the NCI Damage Effect - Complete Storm Damage (0-1) parameter.
The survival probability as calculated above is an annual probability. For multi-year timesteps, the timestep probability is APX, where AP is the annual probability and X is the number of years per timestep. Once a tree's timestep survival probability has been calculated, it is compared to a random number to determine whether the tree lives or dies.
How to apply it
This behavior can be applied to saplings and adults of any species. It cannot be applied to seedlings.
If the Shading Effect term is activated in the growth equation, then the trees to which this behavior is applied must also have a light behavior applied - the Sail light behavior is the one designed to work with the NCI behavior. The use of any other light behavior is at your own risk.
If any storm damage parameters are set to anything other than 1, it is recommended (but not required) that you have the Storm damage applier behavior applied.
Behavior reference string: NCI Mortality
Competition Mortality
Competition mortality is a growth-based mortality behavior. It uses the results of the NCI growth behavior.
How it works
NCI growth in SORTIE is calculated in the following way:
Growth = Max Growth * Size Effect * Shading Effect * Crowding Effect * Damage Effect
Max Growth is the maximum diameter growth the tree can attain, in cm/yr, entered in the NCI Maximum Potential Growth, cm/yr parameter. Size Effect, Shading Effect, Crowding Effect, and Damage Effect are all factors which act to reduce the maximum growth rate and will vary depending on the conditions a tree is in. Each of these effects is a value between 0 and 1.
In the Competition mortality behavior, the following measure is used as predictor variable for probability of mortality:
Relative increment = Growth / PG
The relative increment is the ratio between the growth for an individual tree and the maximum growth possible for that tree. The Growth is the tree's growth for the previous timestep. PG is calculated as follows:
PG = Max Growth * SE
where Max Growth is the NCI growth parameter NCI Maximum Potential Growth, cm/yr, and SE is the Size Effect. Size Effect is calculated as follows:
where:
- DBH is of the target tree, in cm
- X0 is the NCI Size Effect Mode, in cm (X0) NCI growth parameter
- Xb is the NCI Size Effect Variance, in cm (Xb) NCI growth parameter
Once the relative increment for an individual tree has been calculated, the probability of mortality for that individual is calculated in the following way:
Prob = Z relative increment / max
where:
- Prob is the probability of mortality
- Z is the Competition Mortality Shape Parameter (Z) parameter
- max is the Competition Mortality Maximum Parameter (max) parameter, which indicates the maximum relative increment subject to mortality
-
All trees with a relative increment greater than or equal to max will live.
How to apply it
This behavior can be applied to saplings and adults of any species. It cannot be applied to seedlings. Any tree species/type combination to which it is applied must also have NCI growth. This behavior can only be applied with a one year timestep.
Behavior reference string: NCI Mortality
Density Self-Thinning Mortality
This behavior calculates the probability of mortality of an individual juvenile tree as a function of the density and mean diameter of the neighborhood trees. Only neighborhood seedlings and saplings are taken into account in this behavior.
How it works
The probability of mortality is calculated with a double Michaelis-Menton function:
where:
- Pm is the probability of mortality for an individual tree
- density is the density of neighboring seedlings and saplings, in stems/ha, within a radius defined in the Density Self-Thinning Neighborhood Radius, in m parameter
- diam m is the mean diameter of neighbors, measured 10 cm above root collar in cm
- A is the Density Self-Thinning Asymptote (A) parameter
- C is the Density Self-Thinning Diameter Effect (C) parameter
- S is the Density Self-Thinning Density Effect (S) parameter
If the value of density is less than the value in the Density Self-Thinning Minimum Density for Mortality (#/ha) parameter, the tree does not die.
How to apply it
This behavior can be applied to seedlings and saplings of any species. It cannot be applied to adults. This behavior can only be applied with a one year timestep.
Behavior reference string: densityselfthinning
Gompertz Density Self Thinning Mortality
This behavior calculates the probability of mortality of an individual tree as a function of the density of conspecific neighborhood trees.
How it works
The density of conspecific neighbors is the number of stems per square meter of trees above the height set in the Conspecific Tree Minimum Neighbor Height (m) parameter, within the radius from the target tree's location set in the Conspecific Tree Search Radius (m) parameter.
The probability of mortality is calculated as follows:
Pm = G * exp(-exp(H - I * Den))
where:
- Pm is the probability of mortality for an individual tree
- Den is the density of conspecific neighbor trees, stems/m2
- G is the Gompertz Density Self Thinning - G parameter
- H is the Gompertz Density Self Thinning - H parameter
- I is the Gompertz Density Self Thinning - I parameter
How to apply it
This behavior can be applied to trees of any species.
Logistic bi-level mortality
This behavior calculates the probability of survival according to a logistic equation, with the possibility of two sets of parameters for each species: one for high-light conditions and one for low-light conditions. This can also be used alone without the light levels.
How it works
The equation used by this behavior to calculate survival probability is:

where
- p - annual probability of survival
- a - in high-light conditions, this is the Logistic Bi-Level - High-Light "a" parameter; in low-light conditions, this is the Logistic Bi-Level - Low-Light "a" parameter
- b - in high-light conditions, this is the Logistic Bi-Level - High-Light "b" parameter; in low-light conditions, this is the Logistic Bi-Level - Low-Light "b" parameter
- D - tree diam, in cm; diam10 for seedlings, DBH for others
If the timestep length is not one year, the actual probability of survival for the timestep is calculated as p' = p T, where p is the annual probability of survival, p' is the timestep probability of survival, and T is the number of years per timestep. Once the survival probability for the timestep is known for a tree, then a random number is compared to this probability to determine if the tree lives or dies.
Light levels come from the Storm Light grid produced by the Storm Light behavior. The threshold between the use of high-light and low-light parameters is set in the Logistic Bi-Level - High-Light Mortality Threshold (0-100) parameter.
This behavior can also be used without Storm Light. In this case, only the low-light mortality parameters are used.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. If you wish to use the light-level parameter switch, also use the Storm Light behavior.
Behavior reference string: Logistic Bi-Level Mortality
Stochastic bi-level mortality
This behavior applies a constant rate of mortality to trees, with different rates for high-light and low-light conditions.
How it works
Light levels come from the Storm Light grid produced by the Storm Light behavior. The threshold between the use of high-light and low-light parameters is set in the Stochastic Bi-Level - High-Light Mortality Threshold (0-100) parameter.
For each tree, a random number is compared to that species's probability of mortality to determine if it dies. If light levels qualify as high light, the probability of mortality is the value in the Stochastic Bi-Level - High-Light Mortality Probability (0-1) parameter; if the light levels are low, the probability of mortality is the value in the Stochastic Bi-Level - Low-Light Mortality Probability (0-1) parameter.
If the timestep length is not one year, the probability of mortality is adjusted from an annual mortality probability to a timestep probability.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. You must also use the Storm Light behavior.
Behavior reference string: Stochastic Bi-Level Mortality
Height-GLI Weibull Mortality with Browse
This behavior calculates the probability of mortality using a Weibull function of tree height and GLI (light level). It can also simulate the effects of herbivory by using different parameters for browsed and unbrowsed trees.
How it works
The same function is used to calculate the probability of mortality for both browsed and unbrowsed trees, but the parameters are different. The function is:
p = Mmax * exp(-a * H b - c * GLI d)
where
- p - annual probability of mortality
- Mmax - the Height-GLI Weibull - Max Mortality (0 - 1) or Height-GLI Weibull - Browsed Max Mortality (0 - 1) parameter
- a - the Height-GLI Weibull - a or Height-GLI Weibull - Browsed a parameter
- b - the Height-GLI Weibull - b or Height-GLI Weibull - Browsed b parameter
- c - the Height-GLI Weibull - c or Height-GLI Weibull - Browsed c parameter
- d - the Height-GLI Weibull - d or Height-GLI Weibull - Browsed d parameter
- H - tree height in meters
- GLI - light level, between 0 and 100% of full sun
If the timestep length is not one year, the actual probability of mortality for the timestep is calculated as p' = 1 - (1 - p) T, where p is the annual probability of mortality, p' is the timestep probability of mortality, and T is the number of years per timestep. Once the mortality probability for the timestep is known for a tree, then a random number is compared to this probability to determine if the tree lives or dies.
Light levels can come from any of the light behaviors that directly assign a tree its light level. It is expected that this is a GLI value, from 0 to 100% of full sun.
Whether or not a tree is browsed is determined by the Random browse behavior. If the Random browse behavior does not apply to a tree, or is not present in the run, the unbrowsed parameters are always used. The other parameters can be ignored.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species. You must also use a light behavior. If you wish to include the effects of herbivory, also include the Random browse behavior in the run.
Behavior reference string: Height GLI Weibull Mortality
Post Harvest Skidding Mortality
This mortality behavior simulates an increase in mortality after harvesting attributable to skidding damage or other effects. The increase in mortality tapers off through time. DBH and neighborhood basal area can also affect mortality in this behavior.
Model forms are based on those in Thorpe et al. 2010.
How it works
If no harvest has occurred yet in this run, the probability of dying in a timestep is:
Prob = 1 - (1 - β)t
where:
- Prob is the probability of dying before the end of the timestep
- β is the Post Harvest Skid Mort - Pre-Harvest Background Mort Rate parameter
- t is the number of years per timestep
If a harvest has occurred in the tree's cell during the run, the probability of mortality is:
multiplying over years i = 1...t (number of years per timestep);
Wi=(ρ w + δw * DBH + κw * m - ηw * BA) * exp(-τw * (H * t + i)) + ω
where:
- Wi is the annual post-harvest risk of windthrow
- ρw is the Post Harvest Skid Mort - Windthrow Harvest Basic Prob parameter
- δw is the Post Harvest Skid Mort - Windthrow Size Effect parameter
- DBH is the tree's DBH in cm
- κw is the Post Harvest Skid Mort - Windthrow Intensity Effect parameter
- m is the harvest intensity from the tree's "HarvInten" data member, from the HARP external harvesting program (available for download from the SORTIE web site)
- η w is the Post Harvest Skid Mort - Windthrow Crowding Effect parameter
- BA is the neighborhood basal area, in sq m per ha, within a radius set by the Post Harvest Skid Mort - Crowding Effect Radius parameter
- τ w is the Post Harvest Skid Mort - Windthrow Harvest Rate Param parameter
- H is the number of timesteps since the last harvest in this tree's grid cell
- t is the number of years per timestep
- ω is the Post Harvest Skid Mort - Windthrow Background Prob parameter
and
Si = (ρs + κ s * m + φ s * BA) * exp (-τ s * (H * t + i)) + ς
where:
- Si is the annual postharvest risk of standing death
- ρs is the Post Harvest Skid Mort - Snag Recruitment Basic Prob parameter
- κs is the Post Harvest Skid Mort - Snag Recruitment Skidding Effect parameter
- m is the harvest intensity from the tree's "HarvInten" data member, from the HARP external harvesting program (available for download from the SORTIE web site)
- φs is the Post Harvest Skid Mort - Snag Recruitment Crowding Effect parameter
- BA is the neighborhood basal area, in sq m per ha, within a radius set by the Post Harvest Skid Mort - Crowding Effect Radius parameter
- τs is the Post Harvest Skid Mort - Snag Recruitment Rate Param parameter
- H is the number of timesteps since the last harvest in this tree's grid cell
- t is the number of years per timestep
- ς is the Post Harvest Skid Mort - Snag Recruitment Background Prob parameter
How to apply it
This behavior can be applied to saplings and adults of any species. In order for the harvest intensity term to have an effect, the float data member "HarvInten" must be registered for all species/type combos to which this behavior is applied, by using the HARP external harvesting program along with the Harvest Interface.
Behavior reference string: postharvestskiddingmortality
Weibull Climate Survival
This behavior assesses tree survival as a function of climate and larger neighbor trees. A tree has a maximum potential annual probability of survival that is reduced due to several possible factors. Different parameter values can be used for adults and juveniles (saplings).
How it works
For a tree, the amount of diameter growth per year is calculated as:
Survival Probability = Max Survival Probability * Size Effect * Precipitation Effect * Crowding Effect * Temperature Effect
Max Survival Probability is the maximum possible annual survival probability, entered in either the Weibull Climate Survival - Adult Max Survival Prob (0-1) or Weibull Climate Survival - Juv Max Survival Prob (0-1) parameter. Size Effect, Precipitation Effect, Crowding Effect, and Temperature Effect are all factors which act to reduce the maximum survival probability and will vary depending on the conditions a tree is in. Each of these effects is a value between 0 and 1.
Size Effect is calculated with a lognormal function, as follows:
where:
- DBH is of the target tree, in cm
- X0 is either the Weibull Climate Survival - Adult Size Effect X0 parameter or the Weibull Climate Survival - Juvenile Size Effect X0 parameter, depending on whether the tree is a sapling or an adult; this is the mode of the function, expressed in cm
- Xb is either the Weibull Climate Survival - Adult Size Effect Xb parameter or the Weibull Climate Survival - Juvenile Size Effect Xb parameter, depending on whether the tree is a sapling or an adult; this is the variance of the function, expressed in cm
You can set a minimum DBH for the size effect in the Weibull Climate Survival - Size Effect Minimum DBH parameter. Any target tree whose DBH is less than this value will get a size effect based on the minimum DBH instead. This allows you to avoid problems with very small trees that can occur because of the shape of the lognormal function.
Precipitation Effect is calculated as:
PE =
where:
- A is either the Weibull Climate Survival - Adult Precip Effect "A" parameter or the Weibull Climate Survival - Juvenile Precip Effect "A" parameter, depending on whether the tree is a sapling or an adult
- B is either the Weibull Climate Survival - Adult Precip Effect "B" parameter or the Weibull Climate Survival - Juvenile Precip Effect "B" parameter, depending on whether the tree is a sapling or an adult
- C is either the Weibull Climate Survival - Adult Precip Effect "C" parameter or the Weibull Climate Survival - Juvenile Precip Effect "C" parameter, depending on whether the tree is a sapling or an adult
- P is the plot's annual precipitation, in millimeters, as entered for the Plot
Temperature Effect is calculated as:
TE =
where:
- A is either the Weibull Climate Survival - Adult Temp Effect "A" parameter or the Weibull Climate Survival - Juvenile Temp Effect "A" parameter, depending on whether the tree is a sapling or an adult
- B is either the Weibull Climate Survival - Adult Temp Effect "B" parameter or the Weibull Climate Survival - Juvenile Temp Effect "B" parameter, depending on whether the tree is a sapling or an adult
- C is either the Weibull Climate Survival - Adult Temp Effect "C" parameter or the Weibull Climate Survival - Juvenile Temp Effect "C" parameter, depending on whether the tree is a sapling or an adult
- T is the plot's annual mean temperature, in degrees Celsius, as entered for the Plot
Crowding Effect is calculated as:
where:
- C is either the Weibull Climate Survival - Juvenile Competition Effect "C" parameter or the Weibull Climate Survival - Juvenile Competition Effect "C" parameter, depending on whether the tree is a sapling or an adult
- DBH is of the target tree, in cm
- γ is the Weibull Climate Survival - Juvenile Competition Effect gamma parameter or the Weibull Climate Survival - Juvenile Competition Effect gamma parameter, depending on whether the tree is a sapling or an adult
- D is the Weibull Climate Survival - Juvenile Competition Effect "D" parameter or the Weibull Climate Survival - Juvenile Competition Effect "D" parameter, depending on whether the tree is a sapling or an adult
- ND is the number of neighbors with a DBH greater than the target tree's DBH
The ND value is a count of all larger neighbors with a DBH at least that of the Weibull Climate Survival - Minimum Neighbor DBH, in cm parameter, out to a maximum distance set in the Weibull Climate Survival - Max Neighbor Search Radius (m) parameter. The value is a straight count - it is not scaled or relativized in any way. Seedlings never compete.
The probability of survival is for a single year. For multi-year timesteps, the timestep survival probability is the annual probability raised to the power of the number of years per timestep. Once the probability has been calculated, a random number is used to determine whether a tree lives or dies.
How to apply it
This behavior can be applied to saplings and adults of any species. It cannot be applied to seedlings.
Temperature dependent neighborhood survival
This behavior assesses trees survival as a function of mean annual temperature and neighbor adult basal area. For efficiency, it calculates survival rates for cells in a grid and assigns trees the survival probability of the grid cell in which they are found.
How it works
This behavior uses the Temperature Dependent Neighborhood Survival grid to keep track of survival rates. The annual probability of survival for a given species and given grid cell is calculated as:
where:
- Surv is the annual probability of survival
- A is the Temp Dependent Neighborhood Surv - A parameter
- B is the Temp Dependent Neighborhood Surv - B parameter
- M is the Temp Dependent Neighborhood Surv - M parameter
- N is the Temp Dependent Neighborhood Surv - N parameter
- T is the mean annual temperature in degrees Celsius as entered in the Plot
- BAT is the adult total basal area in the neighborhood, in square meters
BAT is the basal area of all adults within the distance from the center of the grid cell set in the Temp Dependent Neighborhood Surv - Neigh Search Radius (m) parameter.
The probability of survival is for a single year. For multi-year timesteps, the timestep survival probability is the annual probability raised to the power of the number of years per timestep.
Trees receive the survival probability calculated for the grid cell in which they are found. A random number is used to determine whether a tree lives or dies.
How to apply it
This behavior can be applied to seedlings, saplings, and adults of any species.
Last updated: 07-Oct-2010 01:50 PM