Note: These are some thoughts from the first day of INTECOL.
–Sorry for the abruptness and lack of polish on these entries, there were many
talks and I have little time for a proper composition.
*acronyms: BEF = Biodiversity and Ecosystem Function; GBIF =
Global Biodiversity Information Facility
It is clear to me that INTECOL is the premiere ecological
meeting. There are delegates from countries all over the world from 67
countries , with especially strong European contingents. The next INTECOL
meeting will be in Beijing in 2017. This is a special INTECOL as this is the
100th anniversary of the British Ecological Society. The opening talk by Sandra
Diaz was held in an immense auditorium at the ExCeL centre, with a couple of
thousand in attendance.
Morning plenary:
Sandra Diaz: functional traits are at the core for
understanding changes in biodiversity and how species contribute to ecosystem
function. Theophrastus, Greek philosophers, created first functional groups.
Looks at key traits for tens of thousands of species, only possible through TRY
data base. Most variation explained by size ( height, seeds, etc.), second was
leaf economy ( leaf N, Leaf area, etc). These traits define plant functional
design. Densities low on the fringes of this trait space -physical challenges,
and many of these species use human help for success (crops and weeds). Two
dense areas in the trait space -big slow growing trees, and small species.
Effect and response traits are important for linking environmental change to
ecosystem services. These traits can be linked or decoupled, and could change
management options.
Linking trait dispersion and values to ecosystem function is
a new area, and so few studies. We just don't know enough to understand how
functional diversity links to environmental change and ecosystem services.
Tree of life in ecosystems symposium:
Lisa Donovan: how selective pressures influence evolution of
biogeochemical cycling. Traits appear evolutionary labile, and reported on a
common garden experiment to find genetic differences controlling traits.
Nitrogen has phylogenetic signal but few differences between close relatives.
Major differentiation within species and especially for different agricultural
lines.
Erika Edwards: Need to move down to small scale to truly
understand the evolution of traits that affect ecosystem function. She looks at
the genus Viburnum. Need to think about whole organism traits. E.g., branching
and growth pattern. This originates from tropics and reinvaded temperate
regions repeatedly, and a mix of different and similar strategies emerged.
growth patterns highly conserved, but leaf spectrum traits were not. Flowering
time seems linked to carbon economy traits.
Amy Zanne: Evolution and biogeography of leaf and stem
traits. Angiosperms originated in the tropics and understory woody species and
spread everywhere and all types of morphologies. Most species are woody and not
exposed to freezing, and lineages move back and forth in climate species but
less so with growth form. lineages shift growth form first, followed by climate
changes.
Cornwell. Evolution of decomposition. Differences in
decomposition rates among different phylogenetic lineages. Did plant life go
from fast cycling world to slow one during evolution. Experiment in common
garden for decomposition rates. basal angiosperms (magnolias) has lower
decomposition than eudicots, which has fast decomposition rates.
Afternoon plenary:
Joel Cohen. Taylor's law after half a century. Taylor's law
has been verified but we don't understand it. Taylor's law states that the
variance of a population is positively related to the mean population size.
Further mean population size is correlated with body size. He showed that tree
data supports a body size-variance relationship. Does it apply to food webs?
Data from aquatic systems show this pattern across species. Why do we care about
Taylor's law? Used for understanding fluctuations in epidemiology, conservation
of endangered species and management of forestry resources. Can see the same
variance-mean relationships in nonbiological data -computer data packets,
weather data and stock market trades. No underlaying theory to explains these.
Previous attempts, such as affects of competition, do not seem to affect
pattern.
Biodiversity & Ecosystem function session:
Enrique Chaneton. Movement of large herbivores around the
world, introduction of cattle versus reintroducing native extirpated
herbivores. Little is know how these large herbivores influence forests.
Multiple pathways of effect from changing plant composition and waste excretion,
affects decomposition. Within an Argentinean park, sites on lake islands do not
have introduced herbivores and compared to nearby mainland sites. Herbivores
reduce vegetation cover by sixty percent. Trees and shrubs were particularly
affected. Distinct composition shifts. Litter layer was substantially
different. In dry sites, higher decomposition in ungrazed sites. Volcanic
eruption during research 'sometimes shit happens' killed many of the cattle.
Carsten Meyer. Examined the completeness of species point
data inventories. Looked at GBIF records and compare to known distribution maps.
GBIF records are highly biased to North America, Europe and Australia. Species
rich areas are almost absent from GBIF records. Not adequate for research or
conservation. Funding, accessibility and human safety all at play for biases.
These factors seem to differ among taxonomy, interestingly. Countries that
under report are large emerging economies (china, India, Brazil, Russia) which
could finance these efforts but for some reason do not.
Julia Koricheva. Tree species richness and genetic diversity
on leaf miners. What is the relative importance of these two effects. Two
experiments, one manipulating tree richness -up to five species, and another
with up to eight clones of silver birch. Silver birch was in both experiments,
so was the focus of leaf miner surveys. Tree richness affects miner richness,
but not abundance. More leaf miner species with higher tree richness in first
year, but not second. For genetic diversity, miner richness also increased with
number of clones. Looked at effect sizes of two experiments and genetic
diversity appeared to have a stronger effect on leaf miner richness.
Tommaso Jucker. Complementarity in functional groups
enhances wood production. He noticed that there were eighty talks on BEF at
INTECOL. Four species combinations two pines and two oaks. Biomass increased
with richness, but looked at more detail, growth over the past ten years from
wood cores. Both pines grew much better in mixture, but oaks only increase
growth when other oak is present. Tree that benefit the most are small trees.
For pines, wet year showed largest increase in growth, most room for
complementarity.
Eric Allen. Direct and indirect effects of landuse on
multifunctionality. Landuse intensity changes functions, it increases biomass
but reduces bird diversity, flower cover, increases pathogens, etc. Used path
analysis to compare landuse and biodiveristy as well as environmental
variables. from this analysis, plant richness seems negatively correlated with
multifunctionality. looked at groups of functions (e.g., production, soils,
cultural). some plots shows strong indirect effects of richness for some
functions.
Siobhan Vye. Responses to multiple stressor change. Examined
stressors in coastal systems. Looked at how an invasive species affected
community response to stress by experimentally combining species in mesocosms
and manipulated nutrient enrichment and temperature. Invader increases
productivity. The presence of the invader determined how the stressor
influenced community functions.
Sebastian Meyer. BEF changes over time. A number of studies
show that BEF experiments increase in strength over time. Examined how
functions change over time using Jena experiment. How many different functions
show changes over time? Over half of functions are influenced by diversity
generally. He regressed the richness-function slopes across time, and about one
third of functions showed increasing diversity effects over time. What are the
mehanisms? The stronger relationships are driven by a combination of changes in
high diversity treatments and changes in low diversity treatments.
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