Ecology
Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/44
The department's teaching and research addresses critical ecological and natural resources issues for Montana, but also tackles fundamental and applied questions around the globe.
Undergraduate programs within the department include Fish & Wildlife Management and Ecology, Conservation Biology and Ecology, Organismal Biology, and Biology Teaching. Graduate programs (M.S. and P.hD.) include Fish & Wildlife Management or Biology and Biological Sciences and an intercollege PhD in Ecology and Environmental Sciences.
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Item Epidemiological differences between sexes affect management efficacy in simulated chronic wasting disease systems(Wiley, 2022-02) Rogers, Will; Brandell, Ellen E.; Cross, Paul C.Sex-based differences in physiology, behaviour and demography commonly result in differences in disease prevalence. However, sex differences in prevalence may reflect exposure rather than transmission, which could affect disease control programmes. One potential example is chronic wasting disease (CWD), which has been observed at greater prevalence among male than female deer. We used an age- and sex-structured simulation model to explore harvest-based management of CWD under three different transmission scenarios that all generate higher male prevalence: (1) increased male susceptibility, (2) high male-to-male transmission or (3) high female-to-male transmission. Both female and male harvests were required to limit CWD epidemics across all transmission scenarios (approximated by R0), though invasion was more likely under high female-to-male transmission. In simulations, heavily male-biased harvests controlled CWD epidemics and maintained large host populations under high male-to-male transmission and increased male susceptibility scenarios. However, male-biased harvests were ineffective under high female-to-male transmission. Instead, female-biased harvests were able to limit disease transmission under high female-to-male transmission but incurred a trade-off with smaller population sizes. Synthesis and applications. Higher disease prevalence in a sex or age group may be due to higher exposure or susceptibility but does not necessarily indicate if that group is responsible for more disease transmission. We showed that multiple processes can result in the pattern of higher male prevalence, but that population-level management interventions must focus on the sex responsible for disease transmission, not just those that are most exposed.Item Limitations to estimating bacterial cross-species transmission using genetic and genomic markers: inferences from simulation modelling(2014-07) Benavides, Julio A.; Cross, Paul C.; Luikart, Gordon; Creel, ScottCross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.Item Female elk contacts are neither frequency nor density dependent(2013-09) Cross, Paul C.; Creech, Tyler G.; Ebinger, Michael R.; Manlove, Kezia R.; Irvine, K.; Henningsen, J.; Rogerson, J.; Scurlock, Brandon M.; Creel, ScottIdentifying drivers of contact rates among individuals is critical to understanding disease dynamics and implementing targeted control measures. We studied the interaction patterns of 149 female elk (Cervus canadensis) distributed across five different regions of western Wyoming over three years, defining a contact as an approach within one body length (∼2 m). Using hierarchical models that account for correlations within individuals, pairs, and groups, we found that pairwise contact rates within a group declined by a factor of three as group sizes increased 33-fold. Per capita contact rates, however, increased with group size according to a power function, such that female elk contact rates fell in between the predictions of density- or frequency-dependent disease models. We found similar patterns for the duration of contacts. Our results suggest that larger elk groups are likely to play a disproportionate role in the disease dynamics of directly transmitted infections in elk. Supplemental feeding of elk had a limited impact on pairwise interaction rates and durations, but per capita rates were more than two times higher on feeding grounds. Our statistical approach decomposes the variation in contact rate into individual, dyadic, and environmental effects, and provides insight into factors that may be targeted by disease control programs. In particular, female elk contact patterns were driven more by environmental factors such as group size than by either individual or dyad effects.Item Limitations to estimating bacterial cross‐species transmission using genetic and genomic markers: inferences from simulation modeling(Wiley-Blackwell, 2014) Benavides, Julio A.; Cross, Paul C.; Luikart, Gordon; Creel, ScottCross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological sce-narios. We used a simulation model with two host species and known transmis-sion rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phy-logeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.