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2016/2017 > BIOL 370 Part II > Flashcards

BIOL 370 Part II Flashcards

1
Q

percent of population persisting vs time

A

-populations less than 100 have low probability of persisting >50 years

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2
Q

negative density dependence

A
  • population growth is negatively effected by its density

- examples: crowding, predators and competition

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3
Q

sources of variation in population growth

A
  • environmental stochasticity

- demographic stochasticity

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4
Q

stochasticity

A
  • model in which parameters vary unpredictably with time

- random, chance events in nature

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5
Q

environmental stochasticity

A
  • unpredictable environmental changes

- NOT: predictable ∆ like seasons; env’t trends

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6
Q

geometric mean

A

(π λ_i) ^ 1/n

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7
Q

incorporating stochasticity into population growth model implication

A
  • makes pop growth slower than expected form constant growth
  • variance in N_t increases w/ time
  • variance in N_t proportional to both mean, variance of r
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8
Q

Extinction from environmental stochasticity likely if

A

var(r) >2r

var(r) is greater than 2r

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9
Q

what does a per capita birth rate of 0.2 mean

A
  • for every z individuals we expect 0.2z new offspring in a year
  • eg. 20 in a pop of 100
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10
Q

P_birth

A

= b/(b+d)

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11
Q

populations with high b and d

A

much higher demographic stochasticity than ones w/ low rates, even for same r

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12
Q

what changes in demographic stochasticity

A

only b and d, r stays same

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13
Q

P_death

A

= d/ (b+d)

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14
Q

P_extinction

A

= (d/b)^No

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15
Q

density dependence

A

birth and death rates are affected by density

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16
Q

the simplest model of density dependence

A

logistic growth

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17
Q

logistic growth assumptions

A
  • linear density dependence in vital rates (b, d)

- decline in per-capita growth as density increases (negative dd)

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18
Q

exponential growth

A

dn/dt = rN_t

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19
Q

intrinsic rate of population increase r

A

r = per capita births b’ - per capita deaths d’

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20
Q

exponential growth with intrinsic pop growth

A

dN/dt = (b’-d’)N_t

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21
Q

exponential vs logistic growth, N vs t

A

exp: exponentially increasing
log: S-shape, increase to asymptote

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22
Q

exponential vs. logistic, dN/Ndt vs N

A

exp: linear (flat)
log: linear decreasing

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23
Q

logistic growth

A

dN/dt = rN_t (1 - (N_t / K)

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24
Q

theta logistic population growth

A

dN/dt = rN(1-(N/K) ^ θ)

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25
Q

θ = 1

A
  • linear effects of density on pop growth rate

- logistic growth

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26
Q

θ > 1

A
  • convex relationship

- density dependence stronger at high density

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27
Q

deterministic factors

A
  • intrinsic (eg. density dependence)

- extrinsic (eg. seasonal ∆ in envt, long-term trends, species interaction)

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28
Q

sample variance

A
  • sampling error

- adds undesired variability in pop. growth beyond true variation

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29
Q

recovery plans and population size

A

less than 50% of record plans include estimate of current pop size, N

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30
Q

why estimating population size is challenging

A
  • expensive
  • time consuming
  • biological challenges
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31
Q

biological challenges to estimating pop size

A
  • detectability
  • mobility
  • wide ranges
  • non-uniform distribution
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32
Q

managing fisheries is like

A

managing a forest of invisible trees that move around

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33
Q

θ less than 1

A
  • concave relationship

- density dependence stronger at low density

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34
Q

all animals are counted

A

census

-perfect detectability

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35
Q

number of individuals

A

abundance

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36
Q

abundance estimate

A

actual estimate, often accounting for detectability

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37
Q

index

A

some measure assumed to be proportional to abundance or density (relative abundance)

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38
Q

random sampling

A
  • unbiased
  • representative
  • can be inaccessible
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39
Q

abundance per unit area

A

density

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40
Q

common wildlife abundance indices

A
  • track count
  • scat
  • vocalizations
  • # captured/observed per day
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41
Q

difficulties with abundance indices

A
  • only reliable if standardized and w/o confounding variables
  • index changes: temporal, spatial, technological, observer
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42
Q

abundance indices temporal changes

A

-diurnal vs nocturnal
-seasonal
temporal ∆ doesn’t necessarily mean a pop. ∆

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43
Q

abundance indices spatial changes

A
  • schooling
  • depth
  • range contraction
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44
Q

estimating abundance w/ detectability

A 
^N= c/ ^p
c = observed count
^p = estimated detectability
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45
Q

common abundance estimation techniques

A
  • distance sampling
  • double sampling
  • multiple observers
  • mark-recapture
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46
Q

Lincoln-Peterson

A 
mark-recapture methods
N = ms/r 
m = number marked
r = # w/ markings on 2nd sampling 
s = total # captured on 2nd sampling
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47
Q

marking individuals

A

radio telemetry, PIT tag, banding, elastomer, photography, genotyping

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48
Q

capturing individuals

A

physical or non-invasive (genetic hair/scat, photography)

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49
Q

Lincoln-Peterson assumptions

A
  • closed population
  • all individuals have equal opportunity of being caught
  • no effect of marking on recapture or survival
  • complete mixing of marked/unmarked
  • marks not lost
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50
Q

sources of variation in population abundance estimates

A
  • deterministic factors
  • process error
  • observation/ measurement error
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51
Q

process error

A

stochasticity

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52
Q

sensitivity

A

how much lambda changes/ change in given vital rate; absolute change

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53
Q

problem w/ sensitivity

A

survival and fecundity are on different scales

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54
Q

elasticity

A

proportional λ∆ in a given vital rate

-how a small, proportional change in rate will affect overall pop growth

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55
Q

sensitivity and elasticity, importance of survival

A
  • survival more important than fecundity

- survival relatively more important in longer-lived organisms

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56
Q

adult survival in long-lived organisms

A
  • highest elasticity

- lowest variability

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57
Q

relative strength of forces driving African cheetah population

A

inside protected areas:

  • lower cub survival due to lion, hyena
  • higher adult survival less human conflict
  • adult survival key for pop. growth
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58
Q

a large increase in a vital rate (eg. 10%) with low elasticity

A

can outweigh a small change in a vital rate w/ high elasticity

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59
Q

viability

A

probability of extinction

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60
Q

PVA

A

population viability analysis

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61
Q

population viability analysis

A

quantitative assessment of probability a pop. will become extinct or quasi-extinct w/i specified time frame

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62
Q

Types of PVA

A
  • count-based
  • demographic
  • metapopulatin
  • spatially-explicit (powerful, but dada hungry)
  • individual-based (computationally intensive)
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63
Q

count-based PVA

A
  • unstructured population

- uses time-series of abundance or density

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64
Q

demographic PVA

A
  • structure population

- uses matrix-models, sensitivity analysis, etc.

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65
Q

quasi-extinction

A

or pseudo-extinction

  • easier to estimate than extinction probability
  • chance that pop. will hit some critical minimum threshold
  • can be used to reflect management options
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66
Q

example of quasi-extinction use

A

-species are listed on SARA if pop. drops below threshold of 50 individuals

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67
Q

PVA goals

A
  • Assess extinction risk (probabilities of single pop., relative risk of multiple pops.)
  • guide management (ID key life stages as management target)
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68
Q

PVA tools

A

population models

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69
Q

simplicity vs realism trade-off

A

simplicity: low data demand, few assumptions, broadly applicable, unrealistic, limited biological insight
realism: high data, many assump., narrowly applicable, realistic, biologically detailed

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70
Q

what can we learn from Number of individuals (N_t) vs time (t), simple unstructured PVA

A
  • range of values pop. is likely to take

- estimated probability of extinction (or pseudo-extinction)

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71
Q

usefulness of PVAs dependent on

A
  • data quality

- assumption that future pop. dynamics will be similar to present

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72
Q

Demographic PVA

A
  • incorporates age/stage structure and age/stage specific vital rates
  • may also include: sex-specific rate, variance/covariance in vital rate, dd, inbreeding depression, allee effects, env’t/demo stochasticity, animal behaviour
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73
Q

Key PVA points

A
  • remain aware of data quantity, quality
  • always show CIs around variability estimate
  • view viability metrics as relative not absolute
  • shorter predictions more realistic
  • keep simple, but be aware of what is left out
  • consider multiple models
  • consider PVAs as work in progress
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74
Q

PVA simple model example

A

breeding pairs owls vs year
-count individuals over time
-estimate trend
project forward

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75
Q

PVA demographic structure example

A
  • add life stages: fledgling, juvenile, sub-adult, adult
  • add competition from other species, barred owl
  • spatial structure: potentially suitable owl habitat
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76
Q

Sumatran orangutan demographic PVA

A

-add year-to-year stochasticity, rare catastrophic events

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77
Q

what can be learned from orangutan PVA

A
  • complexity can always be added (dd, competition, allee, spatial complexity)
  • if there are data it can be modelled
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78
Q

questions to ask about habitat fragmentation

A
  • how many protected areas
  • what configuration
  • how big should each be
  • what shape should each be
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79
Q

landscape ecology

A

-study of how spatial patterning of landscapes affects behaviour, populations, diversity of organisms, as well as the functioning of ecosystems

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80
Q

IBT equilibrium theory

A

equilibrium where colonization = extinction

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81
Q

which type of islands will have greatest equilibrium number of species under IBT

A

large, near source population

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82
Q

why IBT is important for designing protected areas

A

-extinction rate increases for small fragments isolated from source pop.

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83
Q

faunal relaxation

A

reduction in diversity following a reduction in habitat area or creation of habitat island within formerly continuous habitat

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84
Q

faunal relaxation in national parks

A

extinctions after park establishment vs area of park

  • larger parks = less extinctions
  • most parks are not large enough to support MVP
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85
Q

SLOSS

A
  • single large or several small

- depends on overlap

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86
Q

nested diversity

A

-collection of species found in a given small area overlaps extensively w/ other areas and large areas contain these species plus more

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87
Q

edge effects

A
  • more light, wind

- could result in dessication

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88
Q

habitat lost to edge effect, shape and size

A
  • too small and all of core habitat is lost

- shapes that maximize SA:V minimize core habitat, i.e. long slender rectangle

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89
Q

metapopulation

A
  • set of spatially isolated pop.’s of same species that interact on some level
  • small subpops w/i fragments
  • prone to local extinction
  • connected by dispersal
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90
Q

metapopulation regional persistence

A

extinctions must be balanced by colonizations

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91
Q

Theoretical spatial ecology

A
  • homogenous space

- focus on population dynamics

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92
Q

metapopulation spatial ecology

A
  • habitat is suitable on a patch basis

- consider only patch sub populations

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93
Q

landscape spatial ecology

A
  • landscapes is a complex mosaic varying in suitability, area, isolation, shape
  • less emphasis on modelling pop dynamics
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94
Q

example of meta population with regional persistence

A
  • Glanville fritillary, butterfly
  • small populations of specialists
  • high local extinction and colonization
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95
Q

habitat suitability

A
  • not all patches are equal

- source-sink metapopulations

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96
Q

source-sink metapopulations

A

maintained only by dispersal from elsewhere

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97
Q

turnover of patch occupancy

A
  • some habitat patches newly colonized, some extinctions, emmigration, immigration
  • fraction colonized changing
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98
Q

key metapopulation concepts

A
  • unoccupied, suitable habitat can be very important
  • reduced dispersal success can result in extinction
  • critical threshold for habitat destruction
  • patch arrangement and connectivity just as important as absolute #
  • local events depend on regional context
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99
Q

critical threshold for habitat destruction

A

-metapop can become extinct long before all habitat patches are destroyed

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100
Q

aiding patch colonization

A

dispersal corridors

eg. wildlife overpass

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101
Q

corridor experiment results

A

corridor increased SR in native species but not exotics

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102
Q

potential problems with corridors

A
  • straight edge effect (long thin rectangle)

- increased exposure, predation

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103
Q

SLOSS Hawaii, Galapagos

A
  • rank islands from smallest-largest and largest-smallest
  • plot cumulative species vs. cumulative area
  • find more species for less area in both s-l lines
  • lots of small patches probably better
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104
Q

conservation genetics can

A
  • ID unique evolutionary lineages
  • monitor dispersal, movements
  • estimate pop. size
  • trace genetic changes through t
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105
Q

evolutionary change in population is a function of

A

amount of genetic diversity available

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106
Q

genetic issues in conservational biology

A
  • deleterious effects of inbreeding
  • loss of genetic div. and ability to evolve
  • fragmentation, reduction in gene flow
  • genetic drift overriding natural selection
  • accumulation of deleterious mutations
  • adaptation to captivity
  • resolving taxonomic uncertainties
  • defining management issues
  • outbreeding depression
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107
Q

problems with genetic adaptation to captavity

A

adverse effects on reintroduction success

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108
Q

primary level of biodiversity

A

diversity measured at the level of genes, or quantitative genetic traits

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109
Q

reduced genetic diversity causes

A

lower ability to withstand extremes

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110
Q

genetic variation depends on

A
  • the species/population
  • genome/ chrmosome region
  • part of the gene
  • whether sequence/ nucleotide codes for anything
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111
Q

Theodosius Dobzhansky

A

Nothing in biology makes sense except in the light of evolution

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112
Q

adaptive radiation

A
  • morphological and genetic diversity from founder species (ancestor)
  • diversification of a group of organisms into forms filling different ecological niches
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113
Q

types of genetic markers

A
  • allozymes
  • microsatellite DNA
  • single nucleotide polymorphisms
  • direct DNA sequencing
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114
Q

allonymes

A
  • protein variants
  • grind up organism, liberate DNA, gel electrophoresis, compare protein differences
  • indirect way of looking at DNA changes w/o examining DNA
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115
Q

microsatellite DNA

A
  • genetic variants in a section of b.p.’s
  • short repeated sequences = microsatellite
  • examine size of microsatellite w/ PCR
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116
Q

single nucleotide polymorphisms

A
  • SNPs
  • single bp change
  • many thousands per individual
  • used for individual-tailored medical treatments
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117
Q

DNA sequencing improvements

A
  • large scale high throughput
  • lower cost/b.p.
  • lower cost/genome
  • single molecule sequencing
  • portable sequencer
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118
Q

cost of getting genome sequenced

A

ca. $1000 US

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119
Q

Hardy-Weinberg assumptions

A
  • diploid organism
  • sexual reproduction
  • nonoverlapping generations
  • identical allele frequencies in both sexes
  • random mating
  • large pop
  • no migration, mutation, selection
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120
Q

frequency of heterozygotes

A

2pq

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121
Q

frequency of homozygotes

A

q^2
or
p^2

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122
Q

frequency of heterozygotes maximum when

A

p = q = 1/2

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123
Q

forces that effect allele frequencies

A
  • migration
  • mutation
  • drift
  • selection
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124
Q

raw material of diversity and evolution

A

mutations

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125
Q

vast majority of mutations

A

deleterious

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126
Q

germ cell vs somatic cell

A
  • gametes arise from germ cells

- somatic cells are all other cells besides reproductive

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127
Q

polymorphism rate

A
  • much lower in nature than we expect

- mutations are rare

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128
Q

fate of a mutation

A
  • die out or persist, quickly or slowly
  • depends on factors that enhance or downgrade mutation effect (drift, mutation, selection, etc)
  • depends on effect on fitness, genome neighbours
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129
Q

natural selection requirements

A
  • must be phenotypic variation in pop.
  • variation must result in fitness differences
  • variation must be heritable
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130
Q

types of selection

A

purifying selection

positive selection - directional, balancing

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131
Q

purifying selection

A

removes deleterious mutations

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132
Q

random genetic drift

A
  • chance/ random event allele frequency fluctuation
  • drift direction unpredictable (especially in small pop.)
  • reduces variation w/i pop.
  • causes populations to diverge from one another
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133
Q

how does random genetic drift reduce population variability

A
  • causes lost off alleles
  • increase homozygosity
  • decreases heterozygosity
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134
Q

random genetic drift example

A

x # marbles in a jar

  • some fraction passed on at random
  • unique combinations for each sample repitition
  • smaller sample = higher chance of misrepresenting true pop.
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135
Q

favours beneficial mutations

A

positive selection

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136
Q

fixation of a beneficial mutation

A

directional selection

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137
Q

genetic bottlenecks

A
  • relatively large pop is reduced to very small # by catastrophic event
  • non-natural selection related
  • bottleneck survivors likely have low level of genetic diversity and usually carry non-representative collection of source pop. alleles
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138
Q

founder effect

A

small # individuals form a pop. with low diversity

  • may be positive, negative, or all new
  • rare alleles present more often due to bottleneck effect
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139
Q

inbreeding coefficient

A

probability that alleles in an individual are identical by descent, homozygosity

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140
Q

number of eggs that fail to hatch vs inbreeding coefficient

A

increasing exponentially as inbreeding increases

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141
Q

inbredding coefficient vs generations for N=i

A
  • for i = low population increase exponentially until completely inbred
  • for i = 500 linear increase
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142
Q

balancing selection

A

maintains polymorphisms

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143
Q

MVP

A
  • minimum viable population

- smallest population that will not exacerbate inbreeding effects

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144
Q

% homozygosity vs # generations of inbreeding

A

smaller pop. increases to complete homozygosity exponentially

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145
Q

F = 1/4

A

brother-sister matings

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146
Q

Effective population size

A

N_e

  • N_census > N_e
  • not everyone in pop. contributes to reproduction
  • fluctuation of N_e influences genetic drift
  • difficult to measure
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147
Q

N_e : N_c

A
  • generally 0.1 - 0.2

- i.e. for every 5-10 indiv. only 1 breeding individual

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148
Q

fixation index

A
  • a measure of the difference in the allele

- increased in small populations

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149
Q

F statistics

A

-useful to summarize reduction in heterozygosity at different scales and due to different processes

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150
Q

F = 1/16

A

means children of first cousins

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151
Q

reduction in heterozygosity due to

A
  • bottlenecks
  • founder effects
  • population structure
  • inbreeding
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152
Q

barrier to migrations

A
  • subdivide populations

- decrease heterozygosity

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153
Q

isolated population

A
  • can see reduced gene flow

- in real life we can not

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154
Q

without barriers to migration we expect to see

A

HW ratios of homozygosity : heterozygosity

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155
Q

Sewall Wright’s F statistic

A
  • reduction in heterozygosity at one level of of pop. hierarchy relative to another level
  • popular, useful measure of pop. differentiation
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156
Q

F_ST levels

A 
0-0.05 = little structure
0.05 - 0.15 = moderate
0.15 - 0.25 = high
>0.25 = very high 
1 = full homozygosity, no breeding
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157
Q

no gene flow =

A

genetic divergence among subpopulations

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158
Q

F_ST =

A

1/(4Nm + 1)
N_e*m = number of migrants
N = drift
m = migration

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159
Q

Equilibrium fixation index F^ vs number of migrants per generation (Nm)

A
  • negative exponential
  • high F = very great divergence
  • low F = little divergence
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160
Q

migration

A
  • reduces pop. structure

- can balance drift

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161
Q

Ne*m =~

A

(1 - F_ST)/ 4F_ST
F_ST = (H_T - H_s) / H_T
H_s = average heterozygosity of sub pop.
H_T = average allele frequency

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162
Q

the 50/500 rule

A
  • N_e should be at least 50 to avoid inbreeding depression (loss of fitness)
  • N_e should be at least 500 to avoid eroding evolutionary potential (evolve and adapt to env’t ∆)
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163
Q

revised 50/500 rule

A
  • not good enough
  • Ne >100 required to limit inbreeding depression to 10% over 5 generations
  • Ne >1000 required to retain evolutionary potential
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164
Q

phylogeny

A

history of descent of a group of taxa from their common ancestors
-includes order of branching, absolute ages of divergence

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165
Q

cladogram

A
  • only shows branching points, divergences

- no distances implied by length of lines

166
Q

reconstructing phylogeny

A
  • ID, score taxa for phylogenetically informative characters
  • model how evolution might have given rise to the states we see
  • ID tree most compatible w/ data
167
Q

homoplasy

A

character shared by a set of species but not present in their common ancestor

168
Q

homology

A

existence of shared ancestry between a pair of structures, or genes, in different taxa

169
Q

molecular clock

A

how fast DNA sequences change over time

170
Q

why gene tree doesn’t always = species tree

A
  • horizontal gene transfer and hybridization
  • incomplete lineage sorting
  • different rates of evolution
171
Q

red panda most closely related to

A

other weasels, raccoons, skunks

172
Q

Levin model

A

-assume a large set of identical habitat patches with ‘global’ dispersal
-df/dt = C - E
df/dt = are of change in fraction of occupied suitable patches
-c = colonization rate
-e = extinction rate

173
Q

E (extinction rate) =

A

p_e * f

p_e = probability a pop. in an occupied patch becomes locally extinct

174
Q

patch occupancy

A
  • determined by a balance between colonization and extinction (independent events)
  • colonization rate increases until few patches left to colonize
  • extinction rate increases as colonization increases
  • equilibrium where the two cross
175
Q

how does additional habitat destruction affect population viability, Levin’s model

A
  • lowers colonization curve = equilibrium shift left

- if colonization is lowered too much, p_e>c, f = 0, entire meta population extinct

176
Q

key implications of Levin’s Model

A
  • empty habitat patches are not dispensable (new colonizations)
  • there are critical thresholds (habitat destruction, dispersal barriers) below which entire metaphor. doomed to extinction
177
Q

same total habitat but smaller patches, Levin’s model

A

colonization curve = same

extinction line = steeper

178
Q

same patch size, fewer patches, Levin’s model

A

colonization curve decreased

extinction line same

179
Q

key concepts from meta population theory

A
  • unoccupied suitable habitat important
  • reduced dispersal success can cause extinction
  • critical thresholds for habitat destruction
  • arrangement and connectivity of patches can be just as important as absolute habitat
  • local effects depend on regional context
180
Q

demographic matrix model

A
  • structured population
  • start with life cycle diagram
  • convert to demographic matrix model
181
Q

demographic matrix model M =

A 
b1    b2    b3 ...
p2,1  0    0.... 
0    p3,2  0....
births across top
survival on diagonal 
px, y = prob of surviving from age y to x
y = column
x= row 
by = # offspring produced by individual of age y that survive to enter next age class
182
Q

number of births =

A

% of females that give birth x % of births that are female

183
Q

practice of making conservation decisions based on evidence accumulated from similar studies

A

Evidence-based conservation

184
Q

fewer patches, smaller patches, Levin’s model

A

colonization curve decreased, extinction line increases, complete extinction

185
Q

meta-analysis

A

quantitative s summary of the size of the treatment effect

186
Q

levels of science

A
  • government
  • academic
  • environmental/ NGOs
187
Q

the top threats to at-risk species

A
  • habitat loss/ degradation
  • intrinsic factors
  • harvesting
  • pollution
  • invasives
188
Q

manipulative experiments can help determine

A

most significant threat and most effective management

189
Q

experiments must be

A
  • random
  • replicated
  • control for confounding variables
190
Q

sea turtles

A

7 species, all endangered or threatened

  • long-lived
  • nest on beach
  • disturbance to nest sites and bycatch
191
Q

loggerhead turtle sensitivity analyses

A
  • lambda much more sensitive to survivorship of stages 2-4
  • traditional conservation focuses on wrong age class
  • critical importance of increasing juvenile survivorship not obvious w/o modeling
192
Q

TEDs

A
  • turtle excluder device

- lets turtle escape fishing net

193
Q

Spring/Summer Chinook Salmon, biggest threat?

A
  • dams most obvious
  • others: CC, water use/pollution, fishing, hatchery issues
  • brook trout?
194
Q

ESU

A

evolutionary significant unit

-demographically and genetically independent, significant pop. of the species

195
Q

calculating birth in the demographic matrix model

A

bpµ
b = fecundity (number of eggs produced)
p = survival from age 0-1
µ = adult survival

196
Q

SRSS chinook salmon and brook trout

A
  • 12% higher survival when brook trout absent
  • but correlation does not equal causation
  • confounding variables in study (habitat quality, brook trout habitat may have different favourability)
197
Q

Types of studies utilized to determine threats to SRSS chinooks

A
  • demographic matrix model
  • control impact studies
  • regression approaches
  • before-after-control-impact analyses
198
Q

BACI

A

before after control impact analyses

  • examines if impacted sites do worse after the impact relative to the control site
  • combination of before/after and control/impact studies
199
Q

conservation assessment most effective if

A

-hypotheses can be rigorously tested through well-designed manipulative experiments

200
Q

When experiments are not feasible

A
  • careful observations/ monitoring

- modeling approaches (matrix, control-impact, BACI, regression)

201
Q

adaptive management

A
  • scientific approach to conservation
  • projects are designed, managed, and monitored to maximize opportunities to learn from actions, test assumptions, and adapt future management in response to findings
202
Q

reactive management

A
  • managers deal w/ events as they arise or as new info becomes available
  • do not systematically attempt to build learning into project design and implementation
203
Q

Passive management

A
  • course of action remains constant w/ no opportunity for new info to influence future actions
  • usually no monitoring
204
Q

are grey seals inhibiting recovery of Atlantic cod

A
  • 20 years later cod have not recovered
  • cull the seals and call it an experiment?
  • can’t control any of the other variables
  • no evidence to support the hypothesis that killing seals will help
205
Q

why so important to monitor?

A

spending conservation $ w/o rigorous evidence is ineffective and wasteful

206
Q

when randomization is not possible

A

perform a quasi-experiment

207
Q

confounding variable

A

variable besides hypothesized predictor, response variables that might lead to incorrect conclusions

208
Q

hardest adaptive management decision

A

when to give up

209
Q

protected areas

A

now typically intensively managed areas w/ some restrictions on human activities

210
Q

IUCN categories of protected areas

A

strict nature reserves, wilderness areas, national parks, natural monuments, habitat/species management areas, protected landscapes, protected areas w/ sustainable use of natural resources

211
Q

IUCN definition of protected area

A

clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve long-term conservation of nature w/ associated ecosystem services and cultural values

212
Q

goal of protected lands

A

10%

-surpassed goal

213
Q

global growth of protected areas

A

-levelling off
around 70k areas
-around 18 million km^2

214
Q

why are protected lands not increasing

A
  • people weren’t compensated for their lands

- governments backing away from earlier commitments

215
Q

why do protected areas typically require intensive management

A
  • too small to maintain MVP
  • overpopulation of some species
  • invasive species
  • enforcement against illegal logging and poaching
216
Q

protected area costs

A
  • monitoring
  • science
  • enforcement
  • assessing quality
  • removing non-native spp.
217
Q

how to increase effectiveness of protected areas

A
  • design them strategically
  • enhance enforcement
  • buy-in from local communities
  • research and review goals
218
Q

how to get support from locals

A
  • compensate for their land/resources
  • education
  • involve them
219
Q

conservation on privately owned lands

A
  • 60% of at-risk species only on private lands
  • purchase and protect lands (land trust)
  • engage private land owners in voluntary contracts or legal agreements
220
Q

paper park

A

protected areas existing on paper only, no enforcement

221
Q

natural vegetation inside and outside of protected areas

A

significantly lower outside of protected area

222
Q

GDP and change in forest volume

A
  • no nation w/ per capita GDP > $4600 had shrinking volume of harvestable trees
  • poor countries lowing forests, rich gaining (kuznets?)
223
Q

habitat destruction often greatest

A
  • in areas of highest biodiversity
  • more to lose?
  • more human dominated?
224
Q

mountain logging

A
  • on steep slopes = erosion, mudslides

- drain into tributaries

225
Q

Is habitat loss reversible from logging

A
  • structure, function, recreational value - Yes

- biodiversity- Maybe?

226
Q

is habitat loss reversible from desertification

227
Q

other impacts to forests

A

-road building = edge effects

228
Q

FAO definition of forests

A

too broad

  • overestimate global land area forested
  • underestimate deforestation
229
Q

FAO

A

Food and Agricultural Organizations of the United Nations

230
Q

forest ecosystem services

A
  • food
  • timber
  • fuel
  • carbon storage
  • nutrient cycling
  • water/air purification
  • social and cultural benefits
231
Q

Introduced species

A
  • non-native, non indigenous, alien, exotic

- species that have been moved through human activities beyond their natural range

232
Q

naturalized

A
  • an introduced species that establishes

- self-perpetuating

233
Q

Invasive species

A

-introduced species that thrives, spreads, harms native species, ecosystems, and/or ecosystem services

234
Q

The invasion process

A

uptake from native range –> transfer via vector –> release in new region –> establishment –> population increase and range expansion

235
Q

Pathways of invasion

A
  • intentional introductions

- unintentional introductions

236
Q

Intentional introductions

A
  • European colonization
  • Agriculture, horticulture, aquaculture
  • Pet trade
  • Biocontrol agents
237
Q

Unintentional introductions

A
  • stowaways: ship ballast, water, grain shipments, commercial freight, individual travellers
  • escape from aquaculture facilities
  • unregulated e-commerce
238
Q

Southwest BC aliens

A
  • eastern grey squirrel
  • Japanese knotweed
  • English Ivy
  • House sparrow
  • Scotch broom
  • Himalayan blackberry
  • European green crab
239
Q

The tens rule

A
  • 10% of imported species escape control/cultivation (eg. 100 out of 1000)
  • 10% of these establish (eg. 10 out of 100)
  • 10% of these become invasive (eg. 1 out of 10)
240
Q

key points of tens rule

A
  • not literal/exact

- only a small proportion of introduced species actually become invasive

241
Q

predictors of invasion success

A
  • reproductive rate
  • trophic level
  • # times introduced
  • habitat generalist
  • diet generalist
242
Q

most consistent predictor of success

A

propagule pressure

243
Q

community invasibility

A
  • susceptibility of a community to invasion

- measured as presence, success, # invasives

244
Q

what controls community invasibility

A
  • disturbance
  • diversity
  • natural enemy release
  • ecosystem health
245
Q

community invasibility, disturbance

A
  • frees resource and/or harms native species

- habitat destruction, pollution create high levels of disturbance (reduced diversity, increased invasion)

246
Q

community invasibility, diversity

A

-higher native diversity = lower risk of invasion

247
Q

community invisibility, community health

A
  • degraded ecosystem more prone to invasion

- overexploitation removes competitors/ predators (low biotic resistance)

248
Q

Biotic resistance hypothesis

A
  • community w/ more species more resistant to invasion

- more species = higher proportion of utilized available resources = less available for invaders

249
Q

The Natural Enemy Release hypothesis

A

-degree of enemy release predicts invasiveness

250
Q

ecological consequences of invasive species

A
  • extinction
  • dilution of native biodiversity (local, regional)
  • biotic homogenization
  • modify env’t, alter ecosystem processes
251
Q

direct mechanisms of invasive species consequences

A
  • outcompete
  • exclude
  • predation
  • disease
252
Q

alines and extinctions

A
  • > 50% of documented animal extinctions
253
Q

biotic homogenization

A
  • the anthropogenic blender

- establishment of exotics, loss of natives reduces regional differences

254
Q

alteration of ecosystem processes and services by invasives, examples

A
  • C4 grasses (eg. cheatgrass) increase fire frequency

- nonnative N fixers change soil nutrients, facilitate other invasions

255
Q

of invaders vs trophic level

A

producers - highest
consumers - lower
predators - lowest
-however predators can cause highest damage

256
Q

economic consequences of invasive species

A
  • reduce agricultural/ pasture productivity
  • forest damage
  • clog water intakes
  • choke waterways
  • health costs
257
Q

what aliens cause forest damagae

A

insect pests

258
Q

what alines clog water intakes

A

zebra mussesls

259
Q

cost of aliens

A
  • > 100billion/yr in US

- $840,000 million/yr

260
Q

strategies for dealing w/ introduced species

A

Prevention: uptake and transfer stages
Eradication: release and establishment stages
Control: population increase and range expansion stages

261
Q

prevention of invasives

A
  • public education
  • inspection (border control)
  • regulation (empty ballast water)
262
Q

eradication of invasives

A
  • possible on islands and/or if species is easily removed, restricted in range, small pop., easily accessible habitat
  • extremely difficult on mainland
263
Q

invasive species controls

A
  • biological
  • restoration
  • acceptance
264
Q

what aliens have health costs

A

introduced diseases

265
Q

Biological invasive control

A
  • introduction of natural enemies (consumer, pathogen)
  • difficult
  • backfires
266
Q

restoration control of invasives

A

-restore natives to minimize reinvasion

267
Q

what aliens choke waterways

A

aquatic plants

268
Q

lionfish

A
  • from Indo-Pacific –> invading Caribbean, Atlantic
  • largest magnitude marine invasion
  • harming already stressed corals
  • voracious, ambush predators
  • well camoflouged
  • 65% reduction in prey biomass over 2 yrs
  • very low predator abundance
269
Q

historical views of the ocean

A
  • hostile, barrier
  • mysterious, we don’t occupy it
  • bountiful, food source
270
Q

current views of the ocean

A
  • fun
  • cute
  • delicious
  • endangered
271
Q

Marine ecosystem services

A
  • provisioning: seafood, timber, fiber, parhmaceuticals
  • regulating: water quality, climate regulation
  • cultural services: tourism, recreation, aesthetic, spiritual
  • supporting services: nurseries
272
Q

world fisheries value

A
  • $240 billion

- $10 billion in tuna alone

273
Q

island nations

A
  • 90% of ppl who derive livelihood from fishing live in developing nations
  • 1 billion ppl in developing countries depend on fish for primary source of protein
274
Q

types of fisheries

A
  • recreational
  • artisanal /subsistence
  • industrial
275
Q

artisanal fisheries

A
  • communities w/ few resources
  • nearshore, limited by fuel costs
  • multi-species
276
Q

artisanal fishery tools

A
  • cast net
  • seine net
  • line
  • spear
  • trap: passive, non-selective
277
Q

selectivity in fisheries

A
  • more selective = better ecological impacts and management

- more selective = lower by-catch

278
Q

Industrial fisheries

A
  • far ranging
  • on-board processing
  • onboard technology: GPS, fish-finder
279
Q

Industrial gear

A
  • purse seines: circle net, close like purse
  • trawls: shrimp, groundfish
  • longline: surface, pelagic, demersal; >2500 hooks, miles long
280
Q

overfishing

A

fishing rate that exceeds maximum sustainable yield

281
Q

MSY

A
  • largest yield that can be taken over an indefinite period
  • maintain high growth rates by reducing #s
  • maintain stocks below carrying capacity
282
Q

Effectiveness of MSY

A
  • should be able to avoid overfishing if fish below MSY

- ecosystems are complicated and we can’t always predict what will happen

283
Q

Problems w/ MSY

A
  • hard to estimate: uncertain data
  • stochasticity
  • multispecies interactions difficult
284
Q

tragedy of the commons

A
  • everyone competing for common resource, only concerned about personal needs
  • overuse and exploit
285
Q

Who owns the ocean

A

historically everyone

  • EEZs governed by nations ( 200 nautical miles offshore) – 42% of the ocean
  • high seas governed by UNCLOS
286
Q

UNCLOS

A

UN Convention on the Law of the SEa

287
Q

fishing subsidies

A
  • US: $92 million/yr for boat construction, fishery development, tax exemption, fuel subsidy
  • Globally: tens of billions /yr
288
Q

Types of fisheries data

A
  • catch data

- Stock assessments

289
Q

catches vs time

A

catch is all increasing - more fish?

-no, just more effort, better technology

290
Q

status of stocks vs time

A

1950s: 85% developing, 15% fully exploited
2000s: 40% collapsed, 30% over-exploited, 30% fully exploited

291
Q

state of fisheries projection

A

global collapse of all taxa currently fished by 2048

292
Q

human predation

A
  • unsustainable super predators

- prey on adults

293
Q

catch data

A
  • landings, CPUE catch per unit effort
  • variable quality
  • widely available
294
Q

stock assessments

A
  • model output: biomass, harvest rate
  • high quality
  • rare
  • difficult to find
  • no single database
295
Q

why don’t we see overfishing

A
  • effort displacement, supermarket problem

- shifting baselines

296
Q

The supermarket problem

A
  • overstocking

- makes it look like sea is inexhaustable

297
Q

effort displacement

A

when local populations become overexploited move to new ones, expand to underdeveloped regions

298
Q

shifting baselines

A

our perception of what is normal changes across generations

299
Q

mean fish size 1956 - 2007

A

1956 mean: 19.9kg

2007 mean: 2.3kg

300
Q

why does overfishing happen

A

MSY often used as benchmark but difficult to estimate and regulate

301
Q

how common is overfishing?

A
  • difficult to know

- 63% of assessed estimated to be overfished

302
Q

coral holobiont

A

diverse community of organisms including endosymbiotic algae, protists, fungi, bacteria, Archaea, and viruses living w/i and on the coral

303
Q

zooxanthellae genus

A

Symbiodinium

304
Q

symbiosis benefit to coral

A
  • productivity
  • O2
  • nutrient recycling
305
Q

symbiosis benefits to zooxanthellae

A
  • predator protection
  • environmental regulation
  • nutrients
  • CO2
306
Q

parrotfish

A

indirectly have positive impact on coral recruitment

307
Q

2015-2016 weather

A

biggest El Niño on record + warm water anomaly

308
Q

NOAA coral reef watch

A
  • detect possible bleaching events based on SST

- 7-day bleaching alert in Nov 2015

309
Q

videophillia

A

the new human tendency to focus on sedentary activities involving electronic media

310
Q

stochasticity

A

randomness, uncertainty, hard to predict the outcome, increases probability of extinction

311
Q

demographic stochasticity

A

chance variation in ratio of sexes, reproductive success, etc.

312
Q

to make conservation decisions must know

A
  • # of individuals in population
  • trend in pop. size
  • estimated risk
313
Q

less than 1/2 species on endangered species act have

A

known population size

only 40% have trend in pop size

314
Q

census especially difficult to obtain for

A

aquatic, subterranean, cryptic, highly mobile species

315
Q

environmental stochasticity

A

fluctuations in env’t conditions that affect reproduction/survival

316
Q

relative abundance

A

of individuals sampled per unit effort

317
Q

to estimate sample/pop of sessile/ sedentary species

A

quadrat sample

318
Q

large sample size =

A

lower sampling error

319
Q

random sample to

A

reduce/avoid bias

320
Q

transects ideal for

A

vegetation, slow animals, gradients

321
Q

Lincoln-Peterson method

A 
capture, mark, release 
m = # marked 
allow time to remix
sample, s = #sampled
record # marked, r = recaptured 
total pop N = ms/r
322
Q

mark-recapture assumptions

A
  • no effect of marking on individual
  • no effect of marking on recapture
  • mixing of marked/unmarked is complete
  • captured indiv. represent whole pop.
  • closed, stable pop.
  • marks not lost/removed
323
Q

mark-recapture assumption, no effect of marking on survival

A
  • no more obvious to predator
  • no increase chance of parasite/disease
  • no increase to hunting
324
Q

non-invasive sampling techniques

A
  • photography (especially for dangerous or hard to sample species (tigers, whales)
  • DNA (fecal, hair)
  • aerial survey (open habitat)
  • vocalization
  • nests, burrows
  • records, journals, fossils, pollen
325
Q

discrete population change

A

N_t+1 = lambda * N_t

-births, deaths occur in one big pulse per yr

326
Q

population growth rate

A

λ = N_t+1 / N
λ > 1 growth
λ less than 1 = pop decline

327
Q

Discrete model assumptions

A
  1. density indepen. pop ∆ - shrinks/grows at constant rate
  2. deterministic pop dynamics
  3. homogeneous individuals
  4. closed population
328
Q

implications of density independent population ∆

A
  • resources unlimited no matter how large
  • no carrying capacity
  • no trouble finding mates/resources for small pop. (allee)
329
Q

implications of deterministic population dynamics

A
  • no ‘good’ years and ‘bad’ years
  • no stochasticity
  • constant environment
330
Q

implications of homogeneous individuals

A
  • same reproductive success

- same probability of survival, growth, behaviours

331
Q

PVA

A

population viability analysis

-combine current pop size, trend, estimated yr-yr variability, quantify prob of extinction w/i specified time frame

332
Q

essential simple PVA info

A
  • estimate of current pop size, N
  • estimated pop trend, λ
  • info about fluctuations in λ with time
333
Q

MVP

A

min # of indiv. having a 95% prob. persisting over 50-100yrs

334
Q

Threat analysis

A
  • assess factors that cause pop decline

- manipulative experiment, observational study, models

335
Q

key elements to manipulative experiment

A
  • confounding variables
  • replication
  • random
336
Q

randomization important for

A

reducing bias

337
Q

replication important for

A

discerning the signal from the noise

338
Q

observational study

A

more realistic

  • harder to discern cause and effect
  • harder to control variables
339
Q

sea turtles and conservation actions

A
  • protect nesting sites, captive rearing, reduce mortality in open ocean
  • increase prob. of juvenile survival to 1.0 – find no change to pop decline
  • increase large juvenile survival – may reverse decline
  • efforts should be focused on large juveniles, contrary to what was thought
340
Q

sensitivity analysis

A
  • systematically vary model inputs (survival, growth, fecundity)
  • determine impact of each parameter to the system
  • ID where conservation efforts most effective
341
Q

dam impact

A
  • survival of 1 yr old

- survival/health of reproductively mature adults

342
Q

determining conservation action of spring/summer chinook salmon

A

-demo matrix model: set survival of 1yr old, adult to 100%, pop still declines - dams not the biggest/only threat

343
Q

landscape ecology

A

study of how spatial patterns of landscapes affects organisms and ecosystems (fragmentation, connectiveness, etc)

344
Q

Equilibrium theory of island biogeography

A
  • larger islands tend to harbour more species
  • # species is a balance btw colonization and extinction
  • low # species = large colonization potential, low extinction potential, pop tends to increase
345
Q

faunal relaxation

A

reduction in diversity following reduction in habitat area

346
Q

extinction debt

A

difference btw large # of species doomed to extinction from habitat loss/fragmentation, and the relatively smaller # that have already occurred

347
Q

SLOSS, nested

A

single large

-contains same species of the small patches, plus others

348
Q

collection of spatially isolated subpopulations of the same species

A

metapopulation

349
Q

rate of change of fraction of patches occupied

A 
df/dt = C - E = colonization - extinction 
E = p_e * f 
C = C*f (1 - f)
p_e = prob. sub pop becomes locally extinct 
f = fraction of patches occupied
350
Q

land trust

A

non-profit organization dedicated to land protection

351
Q

IUCN categories of protected land

A

1a. Strict nature reserve- human visitation/ activity strictly limited
1b. wilderness area - human habitation prohibited
II. National park - rec permitted, protect large-scale ecological processes
III. Natural Monuments- protect geological/living features
IV. Habitat/species management area- protect particular species/habitat
V. Protected landscape/seascape - preserve distinctive character produced by human/nature interaction
VI. Protected areas w/ sustainable use of natural resources

352
Q

PADDD

A

protected area downgrading, downsizing, degazettement

353
Q

Degazettement

A

loss of legal protection for entire national park or protected area

354
Q

SLOSS, unnested

A

SS, patches contain unique species

355
Q

Debt-for-nature swap

A

NGO pays some portion of nations debt and nation commits to conservation

356
Q

management that utilizes learning by doing

A

monitor projects and allow for adaptations

357
Q

if an action has a possibility of causing harm it should be avoided

A

precautionary principle

358
Q

prioritizing species and ecosystem based on severity and likelihood of recovery

A

conservation triage

359
Q

coral reef coverage

A
  • cover less than 0.1% of Earth’s surface
  • 20% lost, 24% under imminent threat, 26% in danger
  • support 1-9 million species
360
Q

problems with reef loss

A
  • reduced storm surge protection
  • job losses
  • impacts to religion/tourism
  • reduced diversity
361
Q

threats to coral

A
  • overfishing or pollution
  • overfishing -decreased herbivores -increased algae (top-down)
  • pollution –nutrients –algae increase (bottom-up)
  • more important to focus on water quality or fishing regulation
  • find herbivores to be more important control
362
Q

manipulative experiment trade-off

A
  • ability to control, replicate, randomly assign treatments, reduce chance and confounding variables
  • small spatial scales, controlled environments, not entirely realistic
363
Q

positive deviance approach

A
  • seek out samples of unusual or rare success

- determine what these rare cases have that is lacking from other unsuccessful cases

364
Q

how to use positive deviance research in corals

A

-determine what makes some species of corals thrive in warmer waters –> particular symbiont species –> focus conservation on species that contain them

365
Q

anthropogenic mercury emissions

A
  • smoke from burning coal

- cometics, pharmaceuticals, dental products

366
Q

nearly half of the world lives

A

within 200km of the coast

367
Q

overharvest

A

harvest that exceeds productive capacity of a species and causes the pop, and consequently the yield, to decline over time

368
Q

stock

A

single harvested species in a limited geographical area corresponding to jurisdictional boundaries

369
Q

yield vs stock size and MSY

A

below MSY yield increasing, past MSY yield decreasing (less steeply than it increased)

370
Q

sequential depletion

A

deplete one marine organism until it becomes unprofitable then move on to the next

371
Q

collapse of all fisheries by 2048?

A
  • discredited

- declined in catch could have been due to fisheries management restricting harvest

372
Q

validity of CPUE as standardization

A

-as pop declines, takes greater effort to capture quota

373
Q

overcapacity

A
  • ramping up of technological efficiency and effort beyond sustainable levels
  • as stocks decrease greater effort is required which causes further depression
374
Q

stock assessment models

A

use all available data to predict whether fish pop is shrinking or growing and how pop will respond to different levels/types of harvest

375
Q

countries that utilize stock assessment models

A
  • 36%, the other 64% lack data and resources required
  • less than 350 regularly assessed w/ robust scientific methods
  • largely upper-income countries
376
Q

stock assessment in poor countries

A
  • teach fisherman to collect simple data measures that can be used for basic calculations like spawning potential
  • eg. size of fish caught, reproductive status
  • may also gain local support and belief by having the fisherman collect the data
377
Q

bycatch

A
  • includes juveniles therefore reducing future harvests
  • ca. 1.5kg of bycatch per 1kg of shrimp landed (includes turtles, seabirds, mammals)
  • ca. 500,000 individuals/yr
  • strongly influenced by type of gear used and location of fishing
378
Q

most indiscriminate fishing gear

A
  • trawl nets
  • gillnets
  • longlines
379
Q

reducing bycatch

A
  • TED
  • trailing streamers behind boat to deter seabird
  • close fishery when mammals are abundant
  • acoustic alarms deter marine mammals
380
Q

bycatch is primary threat to

A
  • vaquita
  • Hector’s dolphin
  • Mediterranean monk seal
  • North Atlantic right whale
381
Q

fishing down the food web

A
  • collapse of predator populations followed by a shift toward smaller fish and invert. pops of lower trophic level
  • fisheries then shift their attention to the lower trophic level species causing a subsequent shift to lower trophic level pops
  • sequential depletion hypothesis
382
Q

sequential depletion hypothesis

A
  • catch of top predators will decline as mean trophic level of catch declines
  • suggests that over harvest is severe and widespread
  • sustainability requires immediate and drastic reduction of harvest
383
Q

sequential addition hypothesis

A
  • top predator catch does not need to decline, could grow as mean trophic level of catch declines
  • e.g. if dietary choices or fishing gear change
  • suggests top predators have not been severely depleted, rather diversity of species targets is expanding and shifting
384
Q

sequential depletion or addition?

A
  • appears to be sequential addition

- except in N Atl where cod collapsed

385
Q

solutions to the tragedy of the commons

A
  • transform commons into privately owned areas

- establish strong regulations with severe penalties and fines

386
Q

species that have been moved through human activity beyond their natural range

A

introduced

387
Q

intentionally introducing consumer or pathogen species to control or eliminate organisms interfering with human activity

A

biological control

388
Q

biological control backfire example

A
  • cane toads native to central, south America
  • brought to Australia for sugarcane insect pest control
  • became very abundant, >2000 indiv./ha
  • secrete toxins in skin harmful to dogs, snakes
389
Q

reducing backfire in biological control

A

make sure predator is specialized

390
Q

propagule pressure

A
  • frequency of introductions and quantity of organisms introduced to a site
  • has to be relatively high for most introduced species to take hold
  • eg. Starlings introduced at least 8 times unsuccessfully before taking hold
391
Q

only a tiny fraction of introduced species exhibit the high rates of pop growth required to produce severe biological impacts

A

the tens rule

392
Q

why the tens rule may provide false comfort

A
  • the volume of introductions is enormous, even 10% can be quite large
  • long time lags are common between import and establishment
  • 10% may be too low
393
Q

species that establish as self-perpetuating populations in their non-natural habitat

A

naturalized

394
Q

species traits associated w/ invasion success

A
  • high dispersal rate
  • high rate of pop growth
  • small seed size, longer viability of seed in soil
395
Q

natural enemy release hypothesis

A

-absence of natural enemies give introduced species advantage over competing native species, promoting large pop size and rapid growth

396
Q

Naturalization hypothesis

A
  • Darwin, 1859
  • introduced species are less likely to become established if other congeners are native to the recipient community
  • natural competitors
  • likely to have shared predators
397
Q

species that become so abundant in their non-native habitat that they threaten habitats, ES, or native species

398
Q

biotic resistance hypothesis

A

-highly diverse, undisturbed communities have lower invisibility than disturbed, low species ones

399
Q

congener

A

species of the same genus

400
Q

biotic acceptance hypothesis

A
  • conditions good for native species also good for nonnative species
  • eg. nonnative reptiles most abundant where reptiles are most abundant
  • means that biodiversity hotspots might be in danger
401
Q

important nonnative species

A
  • crops
  • livestock
  • pets
  • pollinators
402
Q

nonnative species benefits

A
  • substantial increases in PP
  • increased nutrients
  • facilitate growth by adapting previously harsh environments (ex. nitrogen fixers, primary succession plants after fire)
403
Q

feral cats

A
  • 33 extinctions (bird, reptile, mammal)
  • 1.3-4 billion bird deaths/yr
  • 6.3 - 22.3 billion mammals/yr
  • greatest source of anthropogenic mortality of US birds and mammals
404
Q

invasion hotspots

A
  • areas where nonnatives are >25% of the species

- correlated w/ high human pop. and economic activity

405
Q

how to determine very rare species presence, especially in waterways

A

eDNA - environmental DNA

406
Q

Species to focus invasion control on

A

predators - have much higher impact than invasive herbivores are plants

407
Q

Improving companies environmental reputation

A
  • report debt to nature
  • carbon/water neutral
  • sustainability
  • partner w/ env’t groups
408
Q

biophilia

A

humans have an innate need for intimate association w/ nature, especially its living biota, and that this need is deeply rooted in the evolutionary history of our species

409
Q

Video games have largely replaced the outdoor activities of many adolescents

A

videophilia

410
Q

environmentalism and generation

A

millennials ca. 10% less likely to self-identify as environmentalists - due to less contact w/ nature?

2016/2017 (15 decks)

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