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Kenneth G. Gerow

Publications and source records attributed to Kenneth G. Gerow.

4 recordsLinked to original sources

The relative influence of road characteristics and habitat on adjacent lizard populations in arid shrublands

As road networks continue to expand globally, indirect impacts to adjacent wildlife populations remain largely unknown. Simultaneously, reptile populations are declining worldwide and anthropogenic habitat loss and fragmentation are frequently cited causes. We evaluated the relative influence of three different road characteristics (surface treatment, width, and traffic volume) and habitat features on adjacent populations of Northern Sagebrush Lizards ( Sceloporus graciosus graciosus ), Plateau Fence Lizards ( S. tristichus ), and Greater Short-Horned Lizards ( Phrynosoma hernandesi) in mixed arid shrubland habitats in southwest Wyoming. Neither odds of lizard presence nor relative abundance was significantly related to any of the assessed road characteristics, although there was a trend for higher Sceloporus spp. abundance adjacent to paved roads. Sceloporus spp. relative abundance did not vary systematically with distance to the nearest road. Rather, both Sceloporus spp. and Greater Short-Horned Lizards were associated strongly with particular habitat characteristics adjacent to roads. Sceloporus spp. presence and relative abundance increased with rock cover, relative abundance was associated positively with shrub cover, and presence was associated negatively with grass cover. Greater Short-Horned Lizard presence increased with bare ground and decreased marginally with shrub cover. Our results suggest that habitat attributes are stronger correlates of lizard presence and relative abundance than individual characteristics of adjacent roads, at least in our system. Therefore, an effective conservation approach for these species may be to consider the landscape through which new roads and their associated development would occur, and the impact that placement could have on fragment size and key habitat elements.

Wyoming

Estimating the hatchery fraction of a natural population: a Bayesian approach

There is strong and growing interest in estimating the proportion of hatchery fish that are in a natural population (the hatchery fraction). In a sample of fish from the relevant population, some are observed to be marked, indicating their origin as hatchery fish. The observed proportion of marked fish is usually less than the actual hatchery fraction, since the observed proportion is determined by the proportion originally marked, differential survival (usually lower) of marked fish relative to unmarked hatchery fish, and rates of mark retention and detection. Bayesian methods can work well in a setting such as this, in which empirical data are limited but for which there may be considerable expert judgment regarding these values. We explored a Bayesian estimation of the hatchery fraction using Monte Carlo–Markov chain methods. Based on our findings, we created an interactive Excel tool to implement the algorithm, which we have made available for free.

North American Journal of Fisheries Management

Estimation of potential maximum biomass of trout in Wyoming streams to assist management decisions

Fishery managers can benefit from knowledge of the potential maximum biomass (PMB) of trout in streams when making decisions on the allocation of resources to improve fisheries. Resources are most likely to be expended on streams with high PMB and with large differences between PMB and currently measured biomass. We developed and tested a model that uses four easily measured habitat variables to estimate PMB (upper 90th percentile of predicted mean biomass) of trout ( Oncorhynchus spp., Salmo trutta , and Salvelinus fontinalis ) in Wyoming streams. The habitat variables were proportion of cover, elevation, wetted width, and channel gradient. The PMB model was constructed from data on 166 stream reaches throughout Wyoming and validated on an independent data set of 50 stream reaches. Prediction of PMB in combination with estimation of current biomass and information on habitat quality can provide managers with insight into the extent to which management actions may enhance trout biomass.

Wyoming

Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica

The most important requirements for large-area environmental modeling are a tight integration between models and data, and a close match of the spatial scale at which the model is developed with the scale at which the model is to be applied. To better match the scale of data with that of the model, we propose a set of principles for the development of stochastic modeling systems based on linkage of deterministic models with GIS data. For modeling purposes, a region is usually rasterized into cells and the environmental conditions of those cells are specified by ranges or classes using GIS data layers. It is not necessary to simulate each and every GIS cell in the study area because many cells may have similar environmental conditions and can be grouped together to form cohorts. We define a cohort as the assembly of the cells sharing a unique combination of environmental conditions within the study region. Multiple model simulations can be performed for any given cohort. For each simulation, some of the parameter values can be randomly generated within the specified environmental conditions of the cohort according to a certain statistical distribution which, in turn, can be specified by GIS data layers. By this method the variance and covariance of environmental variables in space and time are integrated into the simulation processes with these modeling systems to make full use of the available data and to assess the uncertainties of the simulated results. An integrated simulation system between CENTURY model and GIS was developed to demonstrate the value of the concepts imbedded in stochastic simulation systems for large area studies.

Conference Paper