Quantitative Wildlife Ecology Thinking Quantitatively Fear of mathematics Uncertainty & the art Sampling, experimental design, & analyses Presentation & communication
Quantitative Wildlife Ecology Thinking Quantitatively Gaining reliable knowledge Logical Creative Organized May not require statistics, calculus, or other advanced math» Graphical analyses, observations, information theory, etc.
Quantitative Wildlife Ecology Have no fear! It s all modeling (i.e., understanding relationships) Graphical Observational Calculus Population ecology Most is simple math +, -, x,
Quantitative Wildlife Ecology Uncertainty must be recognized Best guess Art or science? No substitute for experience Statistics vs. biological reality Do no be fooled! The object is to teach the student to see the land, to understand what he sees and enjoy what he understands--aldo Leopold
Quantitative Wildlife Ecology 2 parts Sampling & Experimental Design Analyses Graphical Traditional stats Other techniques Which is More important? Least understood & taught?
Quantitative Wildlife Ecology Worthless without proper presentation Technical writing & presentation Recognize uncertainty/variability
What Why How
If no one knows or understands what you have done, what good is it! Present it as clearly & simply as possible!
Know the reader/audience Popular Magazine Field & Stream Semi-technical Trade journal Rangelands Technical Scientific journal Journal of Wildlife Management
Every publication & scientific journal is different Content & focus Style Format For this course: Journal of Wildlife Management CBE Style Manual
In general Clear, concise, & focused Well-organized Uniform units Do not change Metric Active voice Proper tense Review it!
Typical sections Title Abstract Introduction Methods Study Area Results Discussion Literature cited Other
Title Short Indicative of manuscript content
Abstract Summary Problem studied and/or hypothesis tested Pertinent methods Important results & conclusions Utility of results Length restrictions 3%
Introduction Literature review v. justification State the problem or issue Justify the importance of the problem & need for study State the study objectives How you will solve the problem or address the issue Most difficult section to write!
Study area Separate from or part of Methods Where did you do the study What was it composed of?
Methods Enough detail so your study can be repeated exactly Dates, sampling scheme, duration, experimental design, & analyses Common methods can be cited Relate to objectives Addressed Order
Results Clear, simple, concise, & organized Follow objectives & methods Often very dry Sometimes combined with Discussion (not in JWM!)
Results Do not explain analyses (Methods) or discuss results (Discussion) Describe magnitude of biological effects as well as statistical results Do not say The regression analyses found. Do not omit negative or no differences results
Results Do not repeat information found in tables & figures (which are part of the Results section, but found at the end of the manuscript) Use tables and/or figures only when they allow results to be presented more clearly & concisely than text
Results Reference tables & figures in text (Table 1) not (see Table 1) or Table 1 shows. Tables & figures must stand alone Include date & location
Discussion tell the story what did you learn! Interpret data Do data support hypotheses? Make comparisons to literature Do not repeat results Comment on only the most important results Limit speculation & presentation of new hypotheses Be synthetic & relate your findings to overall objectives & hypotheses May end with a summary (usually not in JWM!)
Management Implications (JWM) Explain issues important to management & conservation derived directly from your results Thing s a manager can use & apply Do not restate Results or Discussion
Literature cited Formats vary Primary literature* Internet Textbooks Popular articles Reports & gray literature Unpublished data Personal communications
Acknowledgments Straight forward People Funding & support
Other See guidelines
Data Presentation What How Why
Data Presentation Clear & concise Measure of uncertainty/variability or fit ± SE r 2
Data Presentation Always provide units 10 ± 2 deer/ha (mean ± SE) Know the audience Layperson, manager, scientist
Data Presentation Text Presentation outline v. manuscript Tables & Figures Stand alone Presentation v. manuscript