Exam 1 Flashcards
(168 cards)
1
Q
Sampling issues: sample size
A
May be difficult to get enough sample size to make good/reliable decisions
2
Q
Sampling issues: spatial heterogeneity
A
Most populations are not evenly distributed
3
Q
Sampling issues: temporal heterogeneity
A
Populations change over time
4
Q
Sampling issues: sampling variability
A
Two random samples of the same population might yield slightly different results
5
Q
The number of times a treatment is repeated
A
Replication
6
Q
The standard of comparison (no treatments applied)
A
Controls
7
Q
Every individual or sample unit has equal chance of being sampled from the population
Ensure samples are not biased
Protects against unrecognized influences
A
Randomization
8
Q
Types of data: nominal or discrete or categorical
A
Age, status
9
Q
Types of data: ordinal or rank
A
Abundance, wind speed
10
Q
Types of data: continuous
A
Body mass, rainfall
11
Q
Basic sampling designs: every sample unit/animal in the population has equal chance of inclusion
One of the most commonly used
Ensure randomly selected
A
Simple random
12
Q
Simple random with replacement probably best used when you have ____ samples to work with
A
Smaller
13
Q
Basic sampling designs: subpopulations identifies and sampled
Use when you potentially have differences in densities
A
Stratified random
14
Q
Basic sampling designs: units/animals sampled at regular intervals
Randomly selected starting points
A
Simple systematic
15
Q
Basic sampling designs: form of other sampling methods, but units are clustered for sampling due to similarity in habits or clusters of animals
A
Cluster sampling
16
Q
Basic sampling designs: similar to cluster sampling, but you don’t cluster before sampling, cluster after finding animal or plant
A
Adaptive sampling
17
Q
Adaptive sampling is primarily used for ____/___________ animals
A
Rare/uncommon
18
Q
Null is true—> reject null
A
Type 1 error
19
Q
Null is true —-> do not reject null
A
Correct decision
20
Q
Null is false —> reject null
A
Correct decision
21
Q
Null is false —> do not reject null
A
Type 2 error
22
Q
Which type of error is worse?
A
Type 1 —> created false new knowledge
23
Q
The ability to reject the null when you should
A
Power
24
Q
How do you get more power?
A
- Increase sample size —> best way
- Change alpha
- Effect size
25
Set our alpha level at P =
0.05
26
Between 2 means
T-tests
27
Multiple means
Analysis of variance
28
The probability under a specified statistical model that a statistical summary of the data would be equal to or more extreme than it’s observed value
P-value
29
If P<0.05, we
Reject the null - there is evidence of a difference
30
P=0.20 - what error?
Type 1 error
31
A random variable; an unknown quantity or constant characterizing a population
Parameter
32
A numerical approximation of a true population parameter
Estimate
33
Mathematical formula used to compute a estimate
Estimator
34
The closeness of a measured or estimated value to its true value
Accuracy
35
Estimation goal
To have our estimate to be the same value as the parameter, to be accurate and precise
36
Precision leads to
Accuracy
37
The closeness of repeated measurements of the same quantity
Precision
38
Cannot control
Accuracy
39
Can control
Precision
40
Get us thinking beyond just the null and alternative
Multiple hypotheses
41
Approximation of reality
Models
42
Akaike’s information criterion (AIC)
AIC = -2ln(L) + 2q
43
L in the AIC formula =
Likelihood
44
Q in the AIC formula =
Number of parameters
45
4 parameters
Compex
46
3 parameters
Middle
47
2 parameters
Simple
48
Select the model for which AIC is _____
Minimum
49
AIC if done correctly results in
The selection of the best approximating model
50
Given equal explanatory value, we select the simplest explanation
Parismony
51
AIC score: ______ is best
Lower
52
AIC : substantial support for second-ranked model
AIC = 0-2
53
AIC: considerably less support for Model 2
AIC = 4-7
54
AIC: essentially no support for model 2
AIC = >10
55
Indices (index) —>
Active, passive
56
Estimates/counts —>
Surveys, mark/recapture
57
A measurable, correlate of abundance of a population, but not a population estimator
Indices
58
North American breeding bird survey is a prime example of large, annual _____
Index
59
Indices active examples
Spotlight surveys, pellet counts, call-back surveys
60
Indices passive examples
Scent stations, camera taps, harvest indices
61
A count or an estimate from a sample of a population or portions of a population
Estimates/counts
62
A total count of animals in a population
Rare among wildlife populations
Census
63
Census problems
No guarantee that some animals are not missed
Cannot assess his or precision of survey
64
Strip counts equation
N=C/p
65
Transect (Strip) Counts - Fixed Width equation
N = A£x/2Lwn^s
66
Strip/Transect counts can be done by
Ground or aerial surveys
67
Point Counts - Fixed Radius
N = A£x/npir^2
68
The problem with counting
Your count rarely will equal the population size in the area that you sampled
69
Correcting the problems with counting
Reduce/use same observers
Establish survey protocol
Sampling design to account for other variation
70
The fraction of population that could be sampled
Alpha
71
The fraction of the individuals within the possible, available sample that are detected
Beta
72
Obtain counts from plots or points a “rapid” method, then sub sample same plots/points intensively
Double sampling
73
Double sampling equation
Beta = y/u
74
Double sampling advantage
Better representation of study area and population
75
Double sampling assumptions
Intensive method is accurate and reflects annual density of su sample
Counts done simultaneously, sampling same population
76
2 observers conduct counts at same time
Double observer
77
Double observer assumptions
Population is closed during survey
All animals have equal probability of being detected
No identification errors
78
The sampled population where births, deaths, emigration and immigration do not occur during sampling period
Closed population
79
2 observers conduct survey independently at same point at same time
Independent observer approach
80
Independent and simultaneous surveys; can be represented as a mark-recapture experiment
Provides an estimate of detection probabilities
Independent double-observer
81
Independent observer count: x11
Animals detected by both observers
82
Independent observer count: x10
Additional animals detected by observer 1 but not by observer 2
83
Independent observer count: x01
Additional animals detected by observer 2 but not by observer 1
84
Observers alternate primary and secondary roles
Dependent observers
85
Communicates individuals seen/heard to secondary observer
Dependent primary observer
86
Records individuals detected by primary observer and addiction individuals they detect
Secondary dependent observer
87
Sparsely distributed population for which sampling needs to be efficient
Populations that occur in well-defined clusters, and at low or medium density
Populations that are detected through a flushing response
Line transects
88
Patchily distributed populations
Populations that occur in difficult terrain, or with problematic access
Not as effective at low densities
Point transects
89
Distance sampling key assumptions
Animals are randomly distributed in space
Transect lines are randomly placed
Animals on transfer line/point are detected with certainty
Animals are detected at their initial location
Measurements from transect/point are exact
Sightings of indictable are independent events
Detectability decreases as distance from transect increases
90
Survey by yourself or you and technician must be apart use
Distance sampling
91
If you have multiple observers conducting surveys
Fixed width surveys
Use
Double observer
92
Why passive instead of active?
Less Effort
Need Expertise
Hazardous terrain, remote
Not as Time consuming
Minimizes Human interference
93
Types of passive monitoring
Remote photography
Radar
Sensors/sound recordings
Searches for sign
94
Flocks of birds, prairie-dog colonies
Remote locations, spook or flush animals
Hard to obtain accurate count
Aerial/satellite photography
95
Visual, thermal, and multi-spectral
FAA involved- need to get proper clearances, licenses
UAV photography/surveying
96
High energy bean directed outwards
Radio detention and ranging
Animals not aware they are being monitored
Does not reveal type of animal or how many
Radar and wildlife
97
Initially started prior to world war 1
Sophisticated as technology approved at end of world war 2
Radar
98
Used primarily in the fields of engineering, military science, forensic science, archaeology, and environmental remediation
Detect flying objects, clouds, etc
Ground penetrating radar
99
Track stations to detect animal tracks
Track surveys or plates
Scent stations
Surveys of sign
100
Find tracks along transect
Track survey
101
Cover glass of metal coated with soot, place and let animals walk on it
Track plates
102
Individuals come to investigate scent, step on ground or track plate
Construct scent bait station
103
Track stations limitations
Rain, wind can alter
May need a lot of stations
104
Surveys of sign
Track station, hair traps, scat/pellet counts
105
Recording and identifying sounds
Ideal for night surveys and long-term monitoring
Remote sensors
106
Recording more than just presence/absence, recording activity peaks/behavior l
Acoustic monitors
107
Digital camera set to take photos periodically, or via sensor
Active infrared and passive infrared
Remote cameras
108
Beam-break sensors are tripped
Active infrared
109
Detect movement or heat radiation emitted by animals
Passive infrared
110
Used primarily with rare or elusive species
Focus more on a species or species group, not so much the population
Occupancy models
111
The true state of existence of a species in an area that is hidden or concealed from the biologist
Latent staye
112
The proportion of points at which the species is documented
Naive occupancy
113
Perfect detection =
0.80
114
Assumptions of occupancy
Sites are closed to changes in state of occupancy during sampling
Occupancy is constant across sites
Detection probability is constant across sites
Species never detected falsely when absent
Surveys and sites are independent
115
Compared to domestic animals, wildlife nutritional ecology is
Way behind
116
Why should we know about wildlife nutritional ecology?
Wildlife need food
117
A measure of how accessible the food is
What’s out there for an animal to eat
Food availability
118
Assessing the quantity habitat or food resources easier for
Herbivores because plants don’t move m
119
Measuring diet composition
1. Direct observation
2. Post-ingestion samples
3. Post-digestion samples
4. Post-assimilation samples
5. Remains at feeding sites
120
Generally described as a greater liking for one food item over another
Diet preference
121
Offer food simultaneously in same amounts and see which is eaten first or more. Probably not going to work for most predators
Cafeteria trails
122
Measure of what animals choose given what they have available
Diet deleftion
123
Rate of ingestion of energy, protein, and nutrients over a period of time
Nutrition
124
The state of the body components that develop over a period time, and may influence an animal’s future fitness
Nutritional condition
125
The contribution an individual makes to the gene pool of the next generation, relative to the contributions of other individuals in the population
Fitness
126
Animals are made of 4 basic components
Fat, protein, minerals, and water
127
Only direct measure of nutritional condition
Requires collecting and grinding animal for analysis
Whole body composition
128
Laboratory techniques that can provide indices of lipids, water
Hard to do infield and on large animals
High tech equipment
Chemical, electrical, x-ray, and imaging indices
129
Body mass and/or measurements of animals
Easy, low tech equipment, can do in field
Morphometric indices
130
Measures of fat storage on animals
Some easy to do in field, low tech equipment
Need validation
Fat indices
131
Measurements of muscle tissue
Easy, low tech equipment, an use already dead animals
Protein and lean mass indices
132
Take samples from live animals
Measurement of metabolites
Easy, low tech equipment, can do in field
Can’t do on dead animals
Blood and urine indices
133
How a population is affected by nutrition
Not individual condition
Performance measures
134
A common trait(s) or characteristic(s) of the experimental units, samples, or participants in an experiment - including both controls and treatments - that may affect the outcome of a study
Covariates
135
Covariates examples
Age, body mass, habitat type
136
Sample sizes greater than or equal to ___ are often considered sufficient for the CLT to hold
30
137
Organisms that lack a backbone and can be seen with the naked eye
Macro invertebrates
138
Invertebrate fauna retained by 500 um mesh net or sieve
Macro
139
___% of known species are invertebrates
95
140
Feeds on coarse, dead organic matter, breaking it into finer material that is released in their feces
Stonefly nymphs, caddisfly larvae, cranefly larvae
Shredder
141
Feeds on fine, dead organic matter
Black fly larvae, mayfly nymphs, mussels, beetles
Collector
142
Grazes on algae growing on rocks in the substrate or on vegetation
Snails, water pennies
Scraper/grazer
143
Feeds on other invertebrates or small fish
dragonflies and damselflies
Predator
144
Present: caddisfly, mayfly, stonefly, water penny
Good water quality
145
Present: alder fly larva, cranefly larva, dragonfly nymph, water snipe fly larva
Fair water wuality
146
Present: black fly larva, leeches, midge larva, pouch snail
Poor water quality
147
Area along the edge of water body consisting of overhanging bank vegetation
Vegetative margins
148
Shallow area of a steam in which water flows rapidly over a rocky or gravelly stream bed, oxygenated waters - macros have gills
Substrate - riffles
149
Area is stream with coarse substrate
Substrate - sand/rock/gravel streambed
150
Decomposing vegetation that is submerged in the water
Organic matter - Leaf packs
151
Decomposing trees, roots, or branches that are submerged in the water
Organic matter - woody debris
152
Seasons optimal to sample
Spring and fall
153
3 pairs of legs with single hook at end
2-3 tail filaments
Gills attached to abdomen
Movements: swimmers, clingers, crawlers, borrowers
Mayflies
154
3 pairs of legs with two hooks at end
2 tail filaments
No gills attached to abdomen
Some may have gills
Stoneflies
155
3 pies of legs
Large eyes
Long spoon like jaws
No tails on abdomen
Dragonflies and damselflies
156
3 pairs of legs with large pinching jaws
8 pairs of filaments attached to abdomen
Fish flies and alder flies
157
Grub like soft body and hard head
3 pies of legs
Small and forked tail
Gills on underside of abdomen
Case-building caddisflies
158
Segmented body
Only aquatic insect without fully developed legs in larval stage
True flies
159
Bowling pen shape body
Brushes on head
Ring of hooks on abdomen
Black fly larva
160
3 pairs of legs
Body covered by hard exoskeleton
Beetles
161
5 ours of legs - first 2 have large claws
Large flipper at end of abdomen
Crayfish
162
7 pairs of legs - first 2 claw like
Body higher than wide
Usually swims sideways
Scud/sideswimmer
163
7 pairs of legs - first 3 claw like
Very long antenna
Body wider than high
Aquatic sowbug
164
Fleshy body enclosed between 2 hinged shells
Mussel and clams
165
Fleshy body enclosed by single shell
Usually coiled in upward spiral
Snails
166
Long body with numerous segments
aquatic worms
167
Long body, thin, slightly widened
34 segments
Leeches
168
Soft elongate body without segment
Head triangular shaped with eyes on top
Flatworms
