class: center, top, title-slide .title[ #
Population Ecology II: Limits on Population Growth
] .subtitle[ ## .white[EFB 390: Wildlife Ecology and Management] ] .author[ ###
Dr. Elie Gurarie
] .date[ ### October 29, 2024 ] --- <!-- https://bookdown.org/yihui/rmarkdown/xaringan-format.html --> .pull-left-70[ --- ## As populations grow ... ### they always hit **Limits to growth** .content-box-blue.large[ - Space limits - Resource limitations - Competition - Predation - Disease *All of these can interact * ] ] .pull-right-30[ ![](images/limits.jpg) ] --- ## Fundamental population equation `$$\huge \Delta N = B - D + I - E$$` .large[ Exponential growth assumes these (especially .red[**Birth**] & .red[**Death**]) are proportional to .red[**N**]. But at high N ... B can fall, or D can rise, or I can decrease or E can increase. ] ### Density dependence .large[ Means that the *rate* of a parameter(e.g. `\(b = {B\over N}\)` or `\(d = {D\over N}\)` is: - (a) NOT constant - (b) dependent on total population (or density) `\(N\)`. ] --- .pull-left-50[ ## Example: Wolf populations - Dispersal into new area, mainly wolf mating pairs. - Highly territorial! - Wolves produce up to 4 pups per litter that survive - If there are no neighbors, wolves will disperse to found new packs - Pack with 8 adults or 2 adults, still produces (about) 4 pups per litter - If there are lots of neighbors, packs become larger (more individuals) in smaller territories. <img src='images/WI_WolfTerritorySize.png' width='80%'/> ] .pull-right-50[ **Expansion of Wisconsin Wolves, 1970's to 2000's** ![](images/WI_WolfTerritories.png) ] --- ## Human-wolf experiment model .pull-left-60[ ### basics of model - 8 possible territories - 1 initial dispersing wolf (female) ### each season ... - One female / pack gives birth to 2 offspring - Offspring can choose whether to disperse or not - 1/4 of all wolves die each year ] .pull-right-40[ ![](images/wolfmother.jpg) ] Enter data [here](https://docs.google.com/spreadsheets/d/15j2b3FCfbtrPkAlRb6QE6s55aRqggeSDi5YU6OBh7Yc/edit?usp=sharing) --- class: inverse ## Results of Human Wolf Experiment .center[![](images/PackPopulationOverTime.png) Looks a lot like initial exponential growth stabilizes around 20 ind as die-offs balance out births. ] --- .pull-left[ # Modeling wolf population Population equation: `$$N_t = (1 + b - d) \times N_{t-1}$$` Death rate is constant: `\(d = 0.25\)` Birth rate is high when population is low: `\(b_0 = 2\)` Birth rate is small when population is high: - `\(N = 1\)`; `\(B = 2\)`; `\(b = 2\)` - `\(N = 8\)`; `\(B = 16\)`; `\(b = 2\)` But it hits an absolute maximum of 16 total. So if: - `\(N = 32\)`; `\(B = 16\)`; `\(b = 1/2\)` - `\(N = 64\)`; `\(B = 16\)`; `\(b = 1/4\)` ] .pull-right-40[ ![](Lecture_PopulationEcology_PartII_files/figure-html/WolfLogisticGrowth-1.png)<!-- --> ] --- .pull-left-60[ ## Some Concepts - Natural populations are always eventually limited - The "cap" on a population is called the .darkred[***Carrying Capacity*** ] (symbol: **K**). This is - When population rates (*b*, *d*, also *i*, *e*) depend on the **total population**, this is called: .darkred[***Density Dependence***]. - The maximum growth rate (max `\(b-d\)`) is called the .darkred[**intrinsic growth rate**]. ] .pull-right-40[ ![](Lecture_PopulationEcology_PartII_files/figure-html/WolfLogisticGrowth_II-1.png)<!-- --> ] --- .pull-left[ # Logistic growth .darkred[***Logistic growth***] is a specific kind of .darkred[Density Dependent] growth where the relationship between ***r*** and ***N*** is .darkred[**linear**]. The formula is: `$$r = r_0 (1 - N/K)$$` <img src="Lecture_PopulationEcology_PartII_files/figure-html/unnamed-chunk-3-1.png" width="100%" /> ] .pull-right[ ![](Lecture_PopulationEcology_PartII_files/figure-html/logisticcurves-1.png)<!-- --> - At `\(N=0\)` - growth = 0 - At `\(N\)` slightly above 0 - growth maximum `\(\approx r_0\)` - At `\(N = K\)` - growth = `\(0\)` - At `\(N > K\)` - growth < `\(0\)` ] --- .pull-left-40[ ## Intrinsic growth rates Strong Relationships with body size: .large[ `$$\large r_0 = 1.5 \, W^{-0.36}$$` ] `\(W\)` is live weight in kilograms **Q. Why would this be the case?** ] .pull-right-60[ ![](images/IntrinsicGrowthRates.png) .center[Fryxell chapter 6] ] --- ## Different models of density dependence .pull-left-30[ **What is it that depends on density?** Is it birth? Is it death? Is it linear? Is it curvy? ] .pull-right-70[ ![](images/DensityDependence.png) .center[Fryxell chapter 8.] ] --- ## Density dependent mortality & fecundity .pull-left-30[ - Calf / pup / juvenile mortality is highest when densities are highest. - **Fecundity** (# of offspring per female) falls at high densities. - This effect mainly kicks in at very high numbers (not linear). ] .pull-right-70[ ![](images/FowlerExample.png) .center[Fowler (1981)] ] --- .pull.left[ ## Concave curves: Butterflies ] .pull-right[Note that the **density dependent effects** kick in when populations are **small** rather than **large**.] ![](images/butterfly.png) .center[(Nowicki et al. 2009)] --- ## Carrying capacity .pull-left[ **Ecological carrying capacity** Basically - *K* of a logistic growth Limited (almost always) by: - resources: - food - shelter - breeding **habitat** - space - interactions (predation / parasites / disease) ] .pull-right[ > For the **Howework assignment** you will explore different ways in which **Carrying Capacity** is estimated, and why it is an important question for wildlife ecologists to ask. ] --- ## Some references .small[ - Benton, T. G., A. Grant, and T. H. Clutton-Brock. 1995. Does environmental stochasticity matter? Analysis of red deer life-histories on Rum. Evolutionary Ecology 9:559–574. - Chapman, E. J., and C. J. Byron. 2018. The flexible application of carrying capacity in ecology. Global Ecology and Conservation 13:e00365. - Fowler, C. W. 1981. Density Dependence as Related to Life History Strategy. Ecology 62:602–610. - Laidre, K. L., R. J. Jameson, S. J. Jeffries, R. C. Hobbs, C. E. Bowlby, and G. R. VanBlaricom. 2002. Estimates of carrying capacity for sea otters in Washington state. Wildlife Society Bulletin:1172–1181. - McClelland, C. J. R., C. K. Denny, T. A. Larsen, G. B. Stenhouse, and S. E. Nielsen. 2021. Landscape estimates of carrying capacity for grizzly bears using nutritional energy supply for management and conservation planning. Journal for Nature Conservation 62:126018. - Nowicki, P., S. Bonelli, F. Barbero, and E. Balletto. 2009. Relative importance of density-dependent regulation and environmental stochasticity for butterfly population dynamics. Oecologia 161:227–239. - Potvin, F., and J. Huot. 1983. Estimating Carrying Capacity of a White-Tailed Deer Wintering Area in Quebec. The Journal of Wildlife Management 47:463. - Sibly, R. M., D. Barker, M. C. Denham, J. Hone, and M. Pagel. 2005. On the Regulation of Populations of Mammals, Birds, Fish, and Insects. Science 309:607–610. - Thébault, J., T. S. Schraga, J. E. Cloern, and E. G. Dunlavey. 2008. Primary production and carrying capacity of former salt ponds after reconnection to San Francisco Bay. Wetlands 28:841–851. - Wydeven, A. P., T. R. Van Deelen, and E. J. Heske, editors. 2009. Recovery of Gray Wolves in the Great Lakes Region of the United States: An Endangered Species Success Story. Springer New York, New York, NY. ]