CS 380 Lab 3: Species Distribution Modeling using
MaxEnt (Part II)
In the second part of the MaxEnt lab, we will build predictive models
that combine information from multiple climate parameters to make
Look at the response curves for each of your two new models. Note
that the top and bottom rows of response curves look different even
though they represent the same climate variables. The bottom curves
represent what each response curve would look like if it were the only
variable used to predict the probability of species presence. The top
curves show the actual relationships between all climate variables and
species presence in your new model. The multivariate model may
indicate a wider response range for a variable than was discovered
using that variable alone.
- For each of your two species, now use multiple climate parameters
to run a new model. Use your original two choices and any other climate
variables that you identified in the last question from Part I.
When re-running your model,
also check the box on the MaxEnt screen labeled “Do jackknife to
measure variable importance.” Be sure to create two new output folders
within your working directory.
- Re-evaluate the two new maps of predicted species presence. Label
and paste them into your lab write-up. Did incorporating more climate
variables improve the model's performance? If so, where and why? Where
does the model still seem to be inaccurate? Why do you think this is?
Pick the single species and distribution model that interest you the
Label and paste all response curves (top and bottom) from that new
model into your lab write-up.
- What do the response curves from your chosen model tell you about
the climate constraints on your species?
- Do any of the variables
function very differently in this multi-variable model than they would
alone (are any top curves very different than their counterparts on the
bottom)? Why do you think this is?
Examining the Effects of Climate Change on Species Distributions
Much of the western United States became warmer during the 1900s. This
warming is expected to continue for many years to come as a result of
an increase in the amount of long-wave radiation emitted towards the
ground by greenhouse gas molecules like CO2, CH3, and H2O. This is
likely to affect forests substantially. Species living in hot, dry
regions are likely to suffer as evapotranspiration rates (and thus
drought) increase. Species living in cold regions may benefit as warmer
temperatures may allow for photosynthesis earlier in the spring and
later in the fall.
These changes are likely to impact forests most substantially at their
boundaries, where trees stand on the front lines of a constant battle
between survival and death. If temperatures warm, new seedlings and
mature trees growing at the upper elevation tree line in the Sierra
Nevadas will die less often and the upper tree line will rise. If
evapotranspiration increases, new seedlings and mature trees growing on
the lower elevation tree line between alpine forest above and desert
scrub below will die more often and the lower tree line will also rise.
This is how the edges of populations move when climate changes.
In this section you will use the last multivariable model that you
created above, and apply it to new climate data that assume a
hypothetical change of 4°C. While real temperature change will be
spatially, seasonally, and diurnally variable (warming should be most
substantial near poles, during winter, and at night), this hypothetical
temperature change is applied everywhere at all times. So, we are
assuming that diurnal temperature range and annual temperature range
are unchanged. We also assume that rainfall is unchanged.
Place your lab write-up (just one per group, please!) in hardcopy into
the submission box outside my office (Park 249) by Tuesday, Oct. 5th
at 2:30pm (class time) or submit it in-class then.
- Set up MaxEnt to run the same model as the last multi-variable
model you created above. However, before running the model, use
the Browse button next to “Projection layers directory/file” to
environmentIncrTemp folder described in the
- Run the model, remembering to create a new output folder.
- Open the .html file in your output folder and scroll to the maps.
The top map should be identical to the map produced by your last model
run. Check to make sure it is. The bottom map shows the probabilities
for species presence given the hypothetical warming of 4°C.
this map in your lab write-up, placing it side-by-side with a map of
the predictions for the current temperature. Label each map
- How do your predictions of species presence in a warmer climate
differ from those in the current climate? Where are the regions where
your species is no longer predicted to grow? Why do you think this is?
- Are there areas where the probability of species presence has
increased? Where are they and why do you think this happened?
This lab is based on the Species
Distribution Modeling assignment developed by Park Williams, UCSB