Monitoring Approaches – Part III ψ Ecological MethodologyLEC-06 Althoff.

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Presentation transcript:

Monitoring Approaches – Part III ψ Ecological MethodologyLEC-06 Althoff

Occupancy Estimation Fundamental goal: model detection (i.e.,  = detection probability) and occupancy (  ) Recall: need ________ sampling efforts within the specified timeframe In ________ form, the data is collected by one individual, in one habitat type, under uniform weather conditions, with identical presence/influence of other species (plants or animals or both) from survey site to survey site, etc.

Occupancy Estimation….but when not “uniform” sampling/survey conditions: Observers can impact vary in their ability to detect the target species Weather conditions can alter one’s ability to detect species from site to site Habitat: structure and plant species composition can alter detection rates and occupancy Presence (or absence) of other animal species can alter detection rates and occupancy How do we “__________” or “_______” our estimates (i.e., models of occupancy estimation when these Conditions exists…because they will always exist….?

Accounting for / Adjusting for varying situations during surveys: Determine ___________________ These are factors (i.e., effects) that help explain possible _____________ in the raw data--even if densities are equal between two areas. The covariate data can be “__________” to account for the influence of these factors to provide more reliable estimates of occupancy

Example: Mountain Plovers and Burrowing Owls Tipton, H.C., V. J. Dreitz, and P.F. Doherty, Jr Occupancy of mountain plover and burrowing owl in Colorado. Journal of Wildlife Management 72(4): Mountain Plovers: Hypothesized the occupancy would be higher on prairie dog colony and dryland agricultural plots than on grassland plots Burrowing Owls: Hypothesized the occupancy would be higher on active prairie dog colony and non-active plots and grassland and dryland agricultural plots

Field Method Selected plots using an ArcGIS design called spatially balanced sampling (SBS). Surveyed 282 plots: 90 in prairie dog colonies 92 in dryland agriculture 100 in grasslands Each plot was 500m x 500m Each plot was surveyed 2-4 times each (most surveyed). The model used for occupancy accommodates unequal number of surveys Used visual and auditory cues

500 m 125 m 500 m Begin survey Plot layout & travel path for observers 125 m

“Suspected” covariate (i.e., factor) ____________ was a factor that would affect detectability of each species: prairie dog colony vs. grassland vs. dryland agriculture

MOUNTAIN PLOVER

BURROWING OWL Prairie dog colony

Yes…other “factors” matter in occupancy estimation, so adjust accordingly In this study, habitat type mattered Higher probability of occupancy for burrowing owls on active vs. inactive prairie dog towns…and both were higher than grassland or dryland ag sites For mountain plovers, prairie dog towns (active or inactive) had higher probability of occupancy than dryland ag sites, which had slightly higher than grassland sites. Important info for _________ monitoring protocols and “________” occupancy estimation models !!

Sampling Schemes _________________: incorporating a random, stratified, and/or systematic sampling design to avoid bias ________________ design….cannot with good conscience come up with estimate of precision because __________-based assumptions are usually violated vs.

Probability-based designs (survey “points” = ) Random Stratified Systematic

Convenience sampling design ( survey “points”= ) _______ roads, trails, contours of a hill or mountain, etc. Assumes that what is “near” these easy-to- travel routes (i.e., transects?) is the _______ throughout the survey site

Bottomline…. The past….most sampling efforts were based on “convenience”-based designs. Still used today for various reasons (cheaper, match long-term data sets, etc.) but require _____________________ about how precise the resulting estimates and/or indices are The future….more and more sampling efforts will be based on probability-based designs because they minimize biased estimates and allow for statistical analysis—usually without violation of major assumptions– to make ____________________ __________. For occupancy estimates that would be 