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Species
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There are multiple ways of defining species, and no one concept works for all groups
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Evolutionarily Significant Units (ESUs) – might be a better measure
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Frequent definitions include: current geographic
separation, genetic differentiation at neutral markers among related ESUs caused by past
restriction of gene flow, or locally adapted phenotypic traits caused by differences in
selection
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In his 1758 standardised list he counted
9000 species – but as they were mostly temperate it was very biased
Just because more species are being discovered doesn’t mean there are more eg spider
species on earth – just that no one used to care about them
The current catalogue of life shows 1
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The problem with extrapolation is that it assumes similar patterns between species
(eg a 2:1 tropic:temperate ratio)
A study by Alroy suggests that 20-33% of species named are invalid – which is not improving
Body size affects the number of species – there are more small species (for every 10x
decrease in length, there’s a 1000x decrease in volume, and a 100x increase in number of
species – no one knows why it works)
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The best view is of them as an
evolutionary hypothesis
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More taxonomy is
needed, especially in the tropics
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Multiple
methods lead to a rough consensus of around 8-10M species – but not definite
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Arrhenius plots of
species to area (S = logc + zlogA)
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Ie the
smallest island has less species than would be expected for the size
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Therefore the local SR is most likely merely a subset
of the regional SR – and is a mostly linear relationship
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At higher densities identity effects
(recognising invader and blocking it) and niche effects (resource overlap) do take effect but
not significantly (invader increase SR)
Humans normally increase SR – due to introducing invasive species –
except in birds due to habitat destruction (forest → field)
Coral species richness has a clear ranking between
areas(slop>crest>flat) but the SR is not the same even across the
same reef
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• Elevation itself does not cause these patterns,
nor does oxygen – the temperature decreases
with altitude, and the precipitation can change
drastically (Polar, temperate, Tropic, Subtropic,
Equator)
• There is no simple rule of how a species will
react to altitude – there are many complex
relationships
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Depth also decreases SR, but not because of light (life to 10km
but usable light only penetrates to around 200m)
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SR in the ocean is often humped
Local geography is also important
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Disturbance can increase SR if at an intermediate rate – Japanese rice paddies have the
highest SR with intermediate mowing, as it prevents woody plants from monopolising
(moving the system more towards annual plants)
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Plants correlate with about
20% of the variance in animals (and others are weak an unreliable)
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Three processes maintain diversity:

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1 Multiple limiting resources
2 Heterogeneity in space and time
3 Top-down control
Paradox of the plankton describes the situation in which a limited range of resources
supports an unexpectedly wide range of plankton species, apparently flouting the
competitive exclusion principle which holds that when two species compete for the same
resource, one will be driven to extinction
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This doesn’t happen a lot because there is an advantage to being rare, and a cost to
being common
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Any effects are temporary
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Grime 1973 – thought that species richness peaked at mid NPP, due to competition at high
productivity (best competitors win and exclude, and scarcity
of species at low NPP
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Increasing the number of limiting resources actually
increases biomass (Harpole and Tilman)

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Diversity gives rise to more diversity
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The persist in bad times so long as
they have good years occasionally which buffer the population
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Stabilises by having a heavier cost on common
organisms (search image etc) and having less impact on rare individuals
Janzen-Connell effects – distance dependent top down effects which promotes diversity
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Animals disperse
seeds
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Herbivores can also be restricted range and control distribution

Summary: SAR is a general law
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Congruence (or indicator taxa) is uncommon and unreliable
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Diversity
begets diversity, and top-down control stabilises co-existence
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• Niche packing works to try and limit overlap, predicting regular
overlap – little support
• Liebig’s law says that plant production is limited by
light/water/nutrients, and that its most limiting resource is the most
important
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Limiting factors can be
predation stress, space etc, but it normally only comes down to one or two limiting factors
The act of any organism on resources is to decrease them
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Each prey increases
the predator population, but too many predators reduces prey,
reducing predators
R* - the minimum resource level at which a population can persist
(where B=D or where dN/dt=0)
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Other versions for predation (P*) and stress (S*)
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For P* and S* it is whoever can tolerate the highest
which wins
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Can be called apparent competition
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Two factors added together give
boundaries of where a population can persist
– ie only with resource A and B above X and Y
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ZNGI – the line between R*s, where the
growth rate = 0 – the boundary of where the
population can persist
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Not necessarily a
straight line, just easier to draw that way
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• Per capita impact vectors – how much an organism impacts on a variable in
its environment
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In graphs of R:S the resources are depleted, but the
squirrel cannot change the abiotic stress of its environment
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• Supply point – what the environment would have without that organism
• These three can be combined to predict the outcome of
competition depending on where the supply point is:
❷ S2 wins as it can tolerate lower levels of RB than S1
⓿ Both species coexist as they both have an
advantage over each other – S1 can tolerate lower RA,
but S2 can tolerate lower RB, and neither consumes
one to excess
❶ S1 wins as it can tolerate lower RA
• Criteria for coexistence – the ZNGIs must intersect,
and the impact vectors must be proportional to the
ZNGIs (ie has the strongest impact on its most limiting
resource – the one it needs most of)
• In the example on the left, each species uses most of the resource it
needs least – pulling levels below what the other can tolerate
Trade-offs allow coexistence – eg one can cope with high predation, but one can cope with
low resources
R* predictions:
1 Species with lowest R* is the best competitor
2 Dominant species varies with ratio of resources
3 Number of species ≤ number of limiting resources

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4 Outcome depends on supply and per capita impact
5 Coexistence along a gradient via tradeoffs
6 Peak SR at an intermediate ratio of resources
95% of tests support that R* determines the outcome
Gause’s theory that it is impossible for two species eating the same
thing to coexist
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Tilman showed that they can coexist as long as there are
tradeoffs
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Multiple limiting factors
2
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Tradeoffs between requirements and impacts
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Spatial or temporal
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Heterogeneity in resources or predation actually leads
to the most similar species winning, but can maintain
multiple species
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Variable predator and resource levels
maintain multiple species (as no competitor has an
advantage for long enough) -as long as the range is
within the cloud
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In Darwin harbour mangrove swamp 3 different mangrove species
can be maintained due to having different hydroperiods (time they can be
submerged) with tidal variation
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alba has the highest S* as it can
tolerate the longest underwater, whereas S
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If you look at the ZNGIs for these species though, you can see
that there is a trade off: S
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tagal has a lower R* for resources (is the best competitor for R)
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Another real world example is in prairie plants – they compete for light (l*)
and nitrogen (R*)
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S
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tagal
wins
S
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alba

• In the first graph, the ZNGIs do not cross, so Agropyron is outcompeted by
Schizachyrium (as it has a lower R* and l*)
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In the third graph,
Schizachyrium and Panicum still cross, so out compete Agropyron and Boutella
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The graph on
the left shows S and P coexisting and slowly out competing A and B
• In real world systems all four of these species coexist, and the lowest R* species
didn’t dominate – shows that factors are missing from the model (such as herbivory,

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disturbance, environmental variation, unmixed soil, or incumbency – being hard to remove a
pre-existing species)
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Another example is in the Serengeti, where
Topi and Wildebeest both feed on grasses
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Instead, with plenty
of stem Topi win, and with less stem wildebeest
win
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As
you transition from nutritious
grasses to heavy tough grasses, the ungulates get larger
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Therefore, cannot say
SR is low therefore ecosystem is not useful
However, SR obviously can improve some
services
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The nitrogen pollution
removal by freshwater algae is improved with the addition of extra
species (even above the removal rate of the single best species – ST) if the
environment is heterogenous
The same thing happens with oil decomposing marine plankton
• This is not necessarily a linear relationship
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After about 15 species, additional species start to become
redundant
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Individual species can become more variable with the
addition of more species, but it still makes the whole
system more predictable
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In the graph on the right, the
historical species richness of a plot before a two year
drought increased the resilience of the plot (how much it
could return to the old value)
• The graph to the right ranks
diversity as more important than
fertiliser in the productivity of a
system
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The yields are
more than just the sum of the plants involved
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Overyielding does not occur in legumous plants – but
overyielding happens in so many other systems that its unlikely to just be an artefact
More than just species richness, in BIODEPTH they found that increasing the number of
functional groups (sets of similar species, eg grasses/forbs/legumes) increased biomass
SR almost always has a positive effect on ecosystem processes, for productivity, nutrient
cycling, diversity, stability etc
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BIODEPTH also found a 20-50% overlap species contributing to processes,
meaning that they may trade off between them
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As more years/sites/functions/environmental shifts were
studied more and more species were found to be involved meaning that
redundancy is unlikely
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All of these experiments use random species assemblies
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However, with a non-random real world assemblage removing species
also decreased the average uptake
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For example marine species disturb the sediment at the bottom of the
ocean, adding oxygen to the sediment (bioturbation)
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With a random simulated extinction the mixing depth doesn’t decline too
much until there’s only 10 or so species left
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With
extinctions by order of rarity, there is very little impact until the last 25 species or so –
showing that it is the common species which have the largest effect (not necessarily per
capita)
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Local NPP is a response of SR not a driver of SR (but it depends how you ask the question)

Summary: ZNGIs are real world testable definitions of a niche
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Greater SR increases ecosystem functioning and
stability
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Real world impacts
are often stronger than experiments, and not all species are equal
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Whereas if all species make up 20% of the total trees,
your first sample of 20 trees or so would be likely to find all of them
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• Chao’s method – estimates minimum SR in a
community from a sample
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Coverage – the total relative abundance of species in a
sample: 𝐶 = ∑𝑆𝑖=1 𝑃𝑖 × 𝑛𝑖 where 1 – C = the probability of
finding a new species if you observed one more individual

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A rule of when to stop is when you have seen two of all species (in a random sample
𝑓

with a large N)
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But the rarest 5400
species only make up 0
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The point at which rare species (left side) cease to be sampled is the veil line
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Demonstrate species
richness (how many are ranked), evenness (steep slope shows high ranking
species greatly outnumber low ranking species, shallow is high evenness) and structure
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Assumes all species are
represented: 𝐻 ′ = − ∑ 𝑝𝑖 ln 𝑝𝑖 , where eH’ is the effective number of common species
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With
replacement: 𝐷 = ∑ 𝑝𝑖 2
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𝑁[𝑁−1]

1/D is the effective number

of highly abundant species
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α

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𝑞

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Hill series - 𝐷 = (∑𝑆𝑖=1 𝑃𝑖 𝑞 ) [1−𝑞] , where S is the total number of species, can have plots
Diversity indices help predict the right answer with less time
and money than a complete coverage sampling
Other measures of diversity include taxonomic distinctness
(path length between the species – has a big formula), and interaction diversity (count
interactions instead of species – eg in host-parasitoid systems), and functional (trait) diversity
• There are three levels of diversity:
α – number of species in a single location
β – turnover in number of species between locations
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γ – number of species in a region
Eg, the alpha diversity would be 1, 2, and 3, the beta diversity between 1 and
2 would be 1, and between 2 and 3 would be 1
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Beta diversity can be measured in different ways
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Sꝋrenson’s index of dissimilarity is the most widely used, and gives the
𝑏+𝑐

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number of shared species (a) in two samples (b, c): 𝛽𝑆ꝋ = 2𝑎+𝑏+𝑐
A study in Papua New Guinea showed a lower turnover for insects than plants, with insects
being mostly generalists and having a large range
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Eg, is a lake a community, or is it split into east and west, limnetic and benthic?
Can use dissimilarity indices (like Sꝋrenson’s index) or
ordination (statistical technique which shows similar
things as close together on a xy graph) – looking at the
degree of turnover
Can do analysis to look at clusters etc, but can discern
real groupings from them
transition
Cannot assume the same number of communities in two
habitats which are similar, and more SR does not mean
more communities
Communities always made of the same things
Functional groups – like plants or ground feeding
predators etc (hard to get coexistence between multiple
species in the same functional group)
Dominant species (normally the most abundant by biomass), the basal species (bottom
species which generates the energy going into the food chain – normally autotrophic
plants/algae, but decomposition or chemosynthetic species in midnight zone of ocean)
Ecosystem engineer – shapes the environment around it, creating the niche it needs (like a
beaver knowing down a tree to form a dam for fishing)
Californian kangaroo rats create large burrow mounds – grazes down the prairie and
maintains the composition of vegetation and changes the habitats for other species –
burrows used by other species
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Keystone species – a species which has an influence which outweighs its biomass (slightly
different to ecosystem engineers, and near impossible to test)
Mistletoe in Australia – actually tested keystone concept, when totally removed bird diversity
dropped 20% - but birds didn’t interact with them
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Migrants – species which come and go (seasonally, or just pass through)
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Eg bats migrating to south America pollinate cacti even though are only there for
a day – crucial
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Are rarely linear (not 1:1), and
are very inefficient (on land transfer is only about 10%, better in the ocean as most things
ectothermic and don’t waste time heating themselves)
The overall size of a system is the best predictor for food chain length
At the lower nodes of food webs, it tends to be simplified into functional groups (big plants,
insects etc) otherwise they would be huge (study in papa new guinea found 7000 links but
estimated that it only comprised 20% of the total food web)
Connectance – a measure of the number of links seen divided by the number of potential
𝐿

links – gives how many links there might be: 𝐶 = [𝑆(𝑆−1)]
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There are rarely specialists which interact only with
specialists (birds which pollinate one plants, the plant can normally be pollinated by many
birds, and plants which can only be pollinated by one bird, the bird pollinates many plants)
This maintains high connectivity in systems – the generalists link all the specialists together
Communities break down into compartments defined by the functional groups within them
and particular interactions/mutualisms
Makes communities more stable than a random assortment
Tend to have roughly 40 most important links between two trophic levels
and 12 species which have most of the energy flow
When cod invade the Gulf of Riga, herring decrease, zooplankton increase,
and phytoplankton decrease making the water very clear – the cod act as
keystone species
• Rarely parasites can be keystone
species
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Then the trout eat less of the
streambed invertebrates (which break down leaves
and eat algae)
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Have a number of rules which natural systems follow:
1 Many differing components (species)
2 Interactions on multiple scales (local→global)
3 Non-linear dynamics
4 Stochastic and deterministic processed
5 Positive and negative feedbacks
6 Open systems
7 Historically contingent (depend on past conditions)
8 Often nested
Means that physics and such have implications on understanding natural systems

Summary: Species richness must be estimated
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Diversity indices combine
abundances and are more efficient than sampling
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Communities are consistent sets of interacting species, which can be tested with quantitative
methods
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Stability
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Observed communities are not a random assortment – only the tried and tested ones
survive (many possible combinations do not persist, whilst other groupings are seen
repeatedly) – something stabilises these
Communities can be stable at the local or
the global scale, or locally unstable but
globally stable etc
Stability has two properties:
Resistance – the ability to avoid
displacement (trees)
Resilience – the ability to return to the
previous state (grasses)
High resilience systems are very variable
environments with frequent disturbance,
but a rapid recovery to previous state
High resistance systems have very stable
environments where they can accumulate biomass to resist disturbance, and have a very
low recovery if disturbed
Communities can have different stable states eg stable coexistence or competitive exclusion
In Krummholz there are patches of clear ground and patches of pines
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In the Savannah there are blobs of woodlands
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The timescale for these
changes vary across systems
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It
gradually dried out over 1000 years before it switched to
desert
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There is
a risk of this happening in the Amazon and South America because of
deforestation
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Catastrophic bifurcation - as conditions
change incrementally, a sudden switch occurs
that is difficult to reverse – the point of switch is
not the same as the point of return
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In the right hand graph, when the
precipitation is below the red line, the system
switches from the green with vegetation state to
the orange without state
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When this reduces the macroalgal cover below
a certain amount eg when there are 4 sea urchins, the system switches
from a kelp forest state to a sea-urchin barren state
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Increased light levels and
having shock dilutions lead to population crashes after only 6 dilutions
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There are very few intact coral reefs left, and
mostly the original state has been forgotten – except in
the northern line islands
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Should have lots of top predators (leftmost bar
is the healthiest reef, but all are counted amongst the
best conserved reefs in the world)
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In the Philippines coral disease in marine protected areas in decreasing, as
higher taxonomic diversity has led to fewer butterfly fish (which spread coral
disease, and are unpleasant to eat
so not fished)
C
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More
butterfly fish correlates with more coral
disease, and more butterfly fish means a
lower taxonomic distinctness, which also
correlates with coral disease (lower
distinctness means more coral disease)
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Shows Gaia theory is stupid because the
butterfly fish damage their environment and
detriment things – not a large regulating
super-organism
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The turf algae did invade, which
reduced the resistance on the system (as fewer
macroalgae) – models deforestation reducing the
stability of the system
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Predators (like a flatworm) can drive prey
(ciliates) extinct – unless refuges and non-prey
species co-occur (rotifers, ciliate non-prey)
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a) is a control
b) shows the prey with the predator – swiftly
wiped out
c) without a predator, prey and non-prey 1 can
coexist
d) add a predator to c) and the prey still goes
extinct but takes much longer
e) without a predator, prey and non-prey 2 can
coexist
f)
adding a predator to e) still causes the prey
to go extinct, as the prey and non-prey compete
(a) shows that with both non-prey the prey can
persist considerably longer
Increased complexity, even by adding non-trophic
interactions, increases persistence
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• Succession – the non-seasonal, directional, and continuous composition turnover
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The frequency and intensity of
these disturbances confers the stable state
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Get
there first, but rapidly get outcompeted
• Competitors – have limited dispersal, grow slowly and have a low fecundity
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Then additional pots (synthetic
microcosms) with the same species and with or without mesh covered holes to the
external pools (so water could be exchanged)
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• The natural pools returned to their low similarity post treatment
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Without holes it had a high
similarity etc
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Facilitation depends on other species not being able to
establish first (eg Mt St Helens), and by the time other species
arrive the environment accommodates them
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Inhibition allows whoever gets there first to win (but the
environment does not change), with no turnover until the
colonist dies
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From this you can make transition matrices which give the probability that
X will turn to Y/Z or stay as X
• Continuous disturbance causes persistent secondary succession,
with continuous succession
• In Abies balsamea this can cause travelling waves of regeneration across landscapes
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The
older trees (next victims) shelter the younger trees, but once they are big enough
to be hit by the winds (60 years) they too die, continuing the wave
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They are primary producers and influence the physical
structure of the habitat
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Animals are mostly passive followers of succession, with fast decomposing bodies
(no long-standing effect)
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They modulate
succession by interacting with producers as mutualists, or in top-down control
In Mpala Kenya Acacias maintain extrafloral nectaries to entice ants to live on them,
where the ants defend the tree from herbivory
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If large herbivores are excluded, the trees stop
producing as much sugar
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s) who cannot defend the tree from longhorn
beetles
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Summary: Systems can move between stable states, with hysteresis preventing an easy return to
past states
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Gaia is
stupid
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Disturbance is followed by regeneration
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Animals can modify the
pathway of succession
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Controlled by habitat features and
species interactions
Chequerboards frequently occur in nature due to species not being able to coexist
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Clues that this has happened is if species are less related
than you might expect: closely related species are more similar to
each other and therefore compete more strongly (more related
protists exclude each other faster than unrelated)
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Not coevolution, just that too similar get outcompeted
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Species:genus has no support (never
less related than would be expected), resource overlap has some, but not great, and
resource overlap better but not good
• Competitive exclusion most likely not a dominant force
• 20 species of Hawaiian spiders which have one of four body types,
have a common green ancestor and have evolved through convergent
evolution (independently)
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They
form a chequerboard over island habitats, with whatever got there
first taking the niche (and then resisting invasion – never more than
one thing doing the same thing in the same place)
• Variation in the habitat leads to a variation in the plant species,
leading to a highly dispersed chequerboard in butterflies (which are

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R*
P*/R*

usually specialists at some point in their lives – host plant species chequerboard drives effect
not distance between islands)
Alternative stable states (eg clear water with fish vs turbid water with algae) can determine
species allowed, merely by chance
Fynbos – a biodiversity hotspot, it has a high species turnover through the valleys, due to
stochastic fires
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Locally high turnover but as
a landscape low turnover (so valleys can be distinct from one
another) – no valleys had less than 30% turnover over 30
Can live there
Can get there
years
Metacommunities linked by species dispersal
Dark dispersal – what didn’t get there and why – what can it
tell us?
For bacteria it is true(ish) that everything is everywhere –
the environment selects
• Species sorting by resources – brings
together the most similar species, not the most
different
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Eg clay and
white sand soils have very different tree communities,
but not because they are specialised
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They need to be large to contain enough resources to
withstand growing on the dark forest floor for years
Turnover in composition is due to approximately 22% environment, 16%
geography, 10% a combination thereof, and the rest is due to species interactions

S*/R*

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In New Jersey forests, saplings have 50 year life spans,
and can be replaced by other tree species as adults
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Eg after 50 years Grey
Birch only has a 5% chance of still being Grey Birch
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This approach doesn’t take into account the variation
between species or the dispersal limitations
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It also doesn’t allow for
alternative stable states
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Buffon looked at large mammals in the old and new worlds,
whereas von Humboldt looked at many animals and
flowering plants
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The boundaries reflect turnover
Wallace’s line – the line separating the animals in Asia and
the animals in Wallacea (transition zone between Asia and
Australia)
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Wallace
noted a clear divide when travelling through the east indies in 1859
Is more modernly split into biomes:

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Climatic drivers – Influence ecosystem processes
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There are no cold and wet habitats
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They warm
up faster than the ocean, so take up water from the ocean to fall as
rain, dragging it deep into the continent (Sahara)
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Eg
depending on precipitation you could have three
stable biomes – treeless, savannah, and forest
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This can be due to seasonality
(hard to maintain trees in dry season, leading to trees being more spaced out),
or fire varying in frequency, intensity, and seasonality
• Fire is an important driver, and occurs in large parts of the world – to the
point that the world can be split into Pyromes, by the probability of certain
types of fire in certain locations is highest
Ecoregions – patches which have a distinct
composition
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There are 867 unique patches, with the
smallest being a 9km2 island, and the largest
being the entirety of the Sahara
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Further apart ecoregions are more and more different (distance decay works on most scales)
Studies with globally distributed bats found 9-11 clusters of bats, which roughly followed
Wallace’s line and zoological regions

• Modern zoological regions have 11 realms with 20 more
specific regions (non-marine)
• In Europe there are 18 floristic elements (which make up 20%
of the global pool), but there are no clear lines
• The same thing can be done for European mammals
• Many regions poorly studied (as most research is
concentrated in the tropics)

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Despite oceans covering 2/3 of our surface area, comprising 99
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98% of marine species are benthic, but only the surface waters are accessible to studying
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Coastal shelves can also be divided up (12 realms, 62 provinces, 232 ecoregions)
Freshwater is actually a tiny proportion of global area (and most of that is in a few large
lakes)
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Summary: Communities are subsets of a regional species pool which is filtered by the
environment and dispersal
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Important to look at top-down
and bottom-up processes
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Even stable states have constant death and replacement
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Tradition regions are backed by empirical evidence (and
regions for plants and animals roughly correspond)
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Biogeography
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Congruence – when two species evolve to complement each other (so can be used to predict
that the other species) – works well at regional levels (lots of marsupials corelates with lots
of birds etc), but not local (which is usually 1:1 species)
There are six possible factors to explain regional species richness: Climate and NPP,
Heterogeneity, Nutrients, Area, Biotic interactions, and Dispersal and history
NPP – corelates positively with SR at a regional scale (not at local scale)
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Or due to climate differences (warmer→more species)
and various tolerances etc – could be many causes
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Another study found that temperature and
precipitation limit SR (measuring solar energy by
potential evapotranspiration) – when energy is low
that is the most important constraint, and after that
rainfall is the limiting factor
...
Adding in heterogeneity accounts for 70% of the variation
in species richness across regions
Animal regional SR corelates strongly with plant SR, and is limited by temperature (if
ectotherms) or productivity (if endotherms)
For marine SR the sea surface temperature is the main predictor (unless endothermic)
The rest of the factors have minor effects
...
Dispersal is only important to island SR
...


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Climate and NPP was the only one significantly higher
than by chance
...

Grain size – size of the unit in nature you’re investigating
As move from small localised patches to regional scale,
different factors come into play and change in
importance
...

ABCD
EFGH
Surveys on marine epifauna found considerably more species in the
warm tropical waters than in gold area
Regional SR accounts for about 75% of local SR
...
Higher productivity increases turnover and the number of
possible stable states
Latitudinal diversity gradient (LDG) - the increase in species richness or
biodiversity that occurs from the poles to the tropics (diversity peaks in
the tropics)
• Not just species diversity – cultures, languages, diseases,
genetics…
• May be because tropics are a centre of diversity: 86% of
the species in the Indian and pacific oceans are found in
the east indies and radiate out
...
Endemic Area Relationship (EAR) curves are linear, as they
only consist of species which naturally occur in that area (loglog scales)
• Asking why species don’t exist can be informative – eg why don’t dragons
exist? Why bother being a super predator (adding trophic links) and being
huge and defensive, when it could just be a lion and eat sheep
...
Terrestrial predators tend to be the same size as their
prey
...


α
4
4

γ
5
8

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Regional SR is determined by speciation, extinction & dispersal
...
Theories include Area,
Climatic stability, Energy and NPP, Niche sizes, Evolutionary speed
and ‘Out of the tropics’
Geographical area hypothesis – The equator is much larger than
maps show, and has a large continuous area band – therefore SAR
impacts
...
The past
distribution and area can predict the current SR (more than current
area – tropics small relative to boreal forests but way more SR) (assuming niche conservation, no evolution, and no lag in
movement)
...
Tropical habitats are older and maybe
weren’t as damaged by the ice age (actually dried out a lot in the ice ages) – more time for
populations to speciate? There is also reduced (if any)
seasonality, so species don’t need a wide tolerance range
...

Productivity – energy and NPP peak in the tropics, and have a
linear correlation with SR (but no clear mechanism as to
why/how)
...
Solar energy goes through
less atmosphere at the equator, so is less diffuse
...
Says that there are more specialists in the tropics
due to competition for resources and tropics stability, so niches are narrower and can be
packed in
...

The tropics also have increased beta diversity
Diversity enhances diversity – a symptom of tropic diversity not the cause (chicken or egg?)
Rapoport’s rule - latitudinal ranges of plants and animals are smaller at lower latitudes than
at higher latitudes
...

Evolutionary speed hypothesis – More energy in the tropics leads to an increase in growth
and reproduction, reducing generation times, therefore increasing the mutation rate,
meaning that there is stronger natural selection in the tropics
...

Neutral evolution – base substitutions etc – is faster in the tropics due to higher
temperatures

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Swallowtail butterfly clades split in the (warm) Eocene
...

Tropics may not generate diversity – they may just have maintained
species that went extinct outside of the tropics
Out of the tropics – most things originate from the tropics, and may go
extinct when they leave
...
There is niche conservatism (species
tend to keep their ancestral traits)
Summary: climate and productivity drive regional species richness
...

Species richness peaks in
the tropics
...
General constraints do
exist on the range of
possible organisms
...
The
balance differs in different
groups

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