Download Climate change,12-3

Global climate change
This graph, based on the comparison of atmospheric samples contained in ice cores and more recent direct measurements,
provides evidence that atmospheric CO2 has increased since the Industrial Revolution. (Source: NOAA)
Much of the information from this presentation comes from:
http://climate.jpl.nasa.gov/
The chart on the left shows historical sea level data derived from 23 tide-gauge measurements. The chart on
the right shows the average sea level since 1993 derived from global satellite measurements, updated here
monthly. Sea level rise is associated with the thermal expansion of sea water due to climate warming and
widespread melting of land ice.
http://climate.jpl.nasa.gov/keyIndicators/
This illustration on the left shows areas where ice melt occurred for more than three days over Greenland
during 2007. Areas in which melt occurred for longer time periods are shown in a darker red while those
areas melted for fewer days are shown in lighter red.
The time series shows the combined global land and marine surface temperature record from
1850 to 2007. The year 2007 was eighth warmest on record, exceeded by 1998, 2005, 2003,
2002, 2004, 2006 and 2001.
Between 1850 and 2007
the eight warmest years on
record were 1998, 2001, 2002,
2003, 2004, 2005, 2006 and
2007
The main cause of current global
warming is an increased
greenhouse effect caused by
human activities
http://climate.jpl.nasa.gov/causes/
The greenhouse effect results from
heat energy being trapped in Earth’s
atmosphere. In the past, much of this
heat energy escaped Earth’s
atmosphere. Today, increased
greenhouse gases in the atmosphere
don’t allow this energy to escape.
http://climate.jpl.nasa.gov/causes/
Greenhouse gases
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Water vapor
Carbon dioxide (CO2)
Methane
Nitrous oxide
Chlorofluorocabrons
Intergovernmental Panel on
Climate Change, Fourth
Assessment Report
Greater than 90% chance that CO2,
methane, and nitrous oxide increases in
atmosphere as a result of human activities
are responsible for warming patterns in the
last 50 years.
Why have these gases increased in
Earth’s atmosphere?
Burning of coal and oil to fuel human
civilization results in carbon and oxygen
combining in the atmosphere to creat CO2
Clearing of forests also results in increased
CO2 because forests typically take up CO2
so photosynthesis can take place
Could climate change be a result of changes
in the amount of the sun’s energy that
reaches Earth?
Probably not
Evidence that changes in sun
energy haven’t been responsible
for climate change
Since 1750, solar energy reaching Earth has
been constant or increased slightly (based
on sunspot and tree ring data)
Warming has only occurred in Earth’s lower
atmosphere, where greenhouse gases
accumulate
Climate models suggest solar energy
changes can’t account for warming
patterns of last century
Climate change drivers are
categorized into
Forcings—the ultimate drivers of climate
change
Feedback—processes that further influence
climate change after being set in motion
by forcings
Forcings
Solar energy changes over time influence
climate
Particulate matter like aerosols, dust, or soot
in atmosphere can result in cooling or
warming
Feedbacks
Ice-albedo feedback—ice reflects solar
radiation. If ice melts because
temperatures are rising, there is less ice to
reflect solar radiation and more water to
absorb it. More and warmer ocean waters
on Earth will cause Earth to warm more.
Other important feedback
phenomena
Clouds
Carbon cycle
Ocean circulation
Precipitation
Global climate change is predicted
to have important effects on
species’ distributions
Methods for studying climate
change effects on distributions
Comparisons over time
Comparisons over space to determine if
same responses are occurring in different
parts of the world
Modelling
Lenoir et al. 2008, plants in western
Europe
Question— Do species shift their optimal
elevational range upward when the climate
is warming?
Question 2—Do species with particular life
history traits have greater responses to
climate change?
Studied forest plants in six mountain ranges
in Europe, from sea level to 2600 m
Used data from surveys conducted from
1905 through 1985 (early surveys) and
compared these data to data from surveys
conducted between 1986 and 2005 (late
surveys)
1986 was chosen as the “break” year
because at that year the average annual
temperature shifted upward
Fig. 1. Climatic trends from 1965 to 2006. (A) Yearly mean surface temperature anomalies (using overall mean temperature as baseline) and ( B) annual precipitation anomalies (using overall mean annual precipitation as baseline) averaged for 73 elevation sites in the French mountains ranging in altitude from 10 to 2010 m above sea level. Solid gray bars refer to positive anomalies, whereas open bars refer to negative ones. The solid curve is the smoothed average with use of a 10-year filter. The vertical dotted lines mark the split between the two studied periods. Data have been gathered from the French National Climatic Network (Météo-France). [View Larger Version of this Image (114K JPEG file)]
Fig. 1. Climatic trends from 1965 to 2006. (A) Yearly mean surface temperature anomalies (using overall mean temperature as baseline) and
(B) annual precipitation anomalies (using overall mean annual precipitation as baseline) averaged for 73 elevation sites in the French mountains ranging in
altitude from 10 to 2010 m above sea level. Solid gray bars refer to positive anomalies, whereas open bars refer to negative ones. The solid curve is the smoothed
• Based on how many times each plant
species was detected at particular
elevations during the early surveys and
the late surveys, scientists calculated the
“optimal elevation” for the earlier and later
time periods
There was a significant upward shift in
optimal elevation for 2/3 of the plant
species. The mean shift was 64.8 meters
between the two time periods.
Fig. 2. Scatter diagram of forest plant species (n = 171) optimum elevation (i.e., altitude value at maximum probability of presence) for the periods 1905–1985 and 1986–2005. Each point represents one species: Species showing nonoverlapping 95% CIs around the optimum elevation between periods are displayed as solid triangles (
) (n = 46), whereas species with overlapping 95% CIs are displayed as solid circles (
) (n = 125) (see tables S1 and S2 for details) (23). (Inset) The distribution of the species differences in optimum elevation between periods. The vertical dotted line marks zero shift, and the vertical solid line marks the median shift. The arrow describes the direction of the shift.
Fig. 2. Scatter diagram of forest plant species (n = 171) optimum elevation (i.e., altitude value at maximum probability of presence) for the periods 1905–1985
and 1986–2005. Each point represents one species: Species showing nonoverlapping 95% CIs around the optimum elevation between periods are displayed as
solid triangles ( ) (n = 46), whereas species with overlapping 95% CIs are displayed as solid circles ( ) (n = 125) (see tables S1 and S2 for details) (23). (Inset)
The distribution of the species differences in optimum elevation between periods. The vertical dotted line marks zero shift, and the vertical solid line marks the
median shift. The arrow describes the direction of the shift.
Authors also found that species of higher
elevation (mountainous areas) and
species with shorter life cycles (i.e. faster
rates of reproduction) showed the greatest
upward shifts
Fig. 4. Magnitude of optimum elevation shifts for plant species in relation to their ecological and life history traits ( 23). Shifts in mean optimum elevation according to geographic distribution pattern (solid line and symbols) correspond to ubiquitous (n = 104), and mountainous species (n = 67). Shifts in mean optimum elevation according to life form (dotted line and open symbols) correspond to woody (n = 56) and grassy species (n = 115). Means are shown with standard errors. Significance of the magnitude of mean shift from the null hypothesis of zero shift is displayed for each trait (n.s. indicates nonsignificant, *P < 0.05, **P < 0.01, ***P < 0.001; Student's paired sample t test).
Fig. 4. Magnitude of optimum elevation shifts for plant species in relation to their ecological and life history traits (23). Shifts in mean optimum elevation
according to geographic distribution pattern (solid line and symbols) correspond to ubiquitous (n = 104), and mountainous species (n = 67). Shifts in mean
optimum elevation according to life form (dotted line and open symbols) correspond to woody (n = 56) and grassy species (n = 115). Means are shown with
standard errors. Significance of the magnitude of mean shift from the null hypothesis of zero shift is displayed for each trait (n.s. indicates nonsignificant,
*P < 0.05, **P < 0.01, ***P < 0.001; Student's paired sample t test).
Results demonstrate upward shifts in optimal
elevational range and that the magnitude of
these shifts varies with species’ life history traits.
Still unknown are how temperature shifts might
interact with other changes like land-cover
changes and the presence of invasive species to
influence species’ distributions.
Hitch & Leberg 2006, North
American birds
Are distributions of North American birds
moving north?
Are distributional shifts similar to those seen
in a study from Great Britain (similar
results suggest a global cause may be
responsible)
Methods
Used Breeding Bird Survey (BBS) data
Breeding Bird Survey routes
Volunteers drive routes each year during the
peak of the breeding season in North
America when bird singing should be at a
peak
Volunteers record all birds seen and heard
during 3-minute stops each half-mile for
24.5 miles
The data are available online
BBS has been going on since 1966
(Now it has expanded into other countries)
Investigators used data from east of the
Rocky Mountains to exclude potentially
confounding influences of geography
Most bird species were used in analyses,
except for game birds (because of human
influences on distributions) and aquatic
birds (because they may not be sampled
well by BBS methods)
• Birds with distributions not more north than
44° North were considered to have a
southern distribution
• Birds with distributions not more south
than 34° North were considered to have a
northern distribution
Figure 1. Sampling area (dark, solid line) for breeding bird distributions in North America
.
Figure 1. Sampling area (dark, solid line) for breeding bird distributions in North America.
Authors calculated whether birds with southern
distribution had ranges that were shifting north
and whether birds with northern distributions had
ranges that were shifting south.
It was necessary to do both types of calculations to
exclude the possibility that all birds were
experiencing range expansions for reasons not
necessarily associated with climate change, like
land-cover change for example
Authors use data from between 1967 and
1971 to compare to data between 1998
and 2002
Authors determined whether mean northern
latitude (mean latitude determined from
the 10 northernmost routes where the
species was detected) had changed
between the two time periods
Analyses were conducted for all species
simultaneously and for individual species
Results
Birds with southern distributions showed a
significant northward shift, averaging 2.35 km
per year
Birds with northern distributions did not show a
significant southward shift
Species varied in their individual responses but
more species with southern distributions shifted
north than shifted south
Results
Results are similar to those of a study of
birds from Great Britain, suggesting that a
global force, likely climate change, is
driving the shifts
Modelling approaches
What are the advantages of modelling, as
compared to field studies, to predict
species’ responses to climate change?
Pearson and Dawson 2003 evaluate the
bioclimate envelope modelling approach
Use information that is known about how a
species’ distribution relates to climate
variables to describe the species’ “climate
envelope”
Then examine how future scenarios of
climate change would affect species’
distributions, given their climate envelopes
Fig. 1 Simulated redistribution of suitable climate space for stiff sedge (Carex bigelowii)
under future climate scenarios in Great Britain and Ireland as predicted by the
SPECIES model (Pearson et al., 2002). Climate change scenarios are those of
Hulme & Jenkins (1998). Suitable climate space is expected to be lost, with a
general migration northwards as the climate changes.
Limitations of bioclimate envelope
modelling
Potential effects of biotic interactions on
distributions, as well as other
environmental characteristics like landcover type, are not considered
Remember Connell’s work on impact of
species interactions on distributions of
barnacles
However, at large scale, climate tends to be
a dominant influence on distributions at
large scales, so bioclimate envelope
modelling that looks at distributions at
large scales may reduce errors that stem
from ignoring species interactions
Fig. 2 Observed European distribution of hard-fern (Blechnum spicant)
alongside the distribution as simulated by the SPECIES model
(Pearson et al., 2002). Presented as an example of the good agreement
achievable between observed and simulated European-scale distributions using
a bioclimatic model.
Fig. 3 Observed European distribution of yew (Taxus baccata) alongside the
distribution as simulated by the SPECIES model (Pearson et al., 2002).
Although the broad distribution trends are identified in the simulated distribution,
the finer details of the distribution are not captured.
Limitations of bioclimate envelope
modelling
Evolutionary change is ignored. Several studies
have show that populations can often change
rapidly
Example, Thomas et al. 2001—Bush crickets in
new populations (founded within the last 20
years) in new areas in Britain had more longerwinged individuals than older populations,
indicating that evolution can occur rapidly
Thus bioclimate models would be best for
species that are unlikely to undergo rapid
evolutionary, for example long-lived
species and species that don’t disperse
well
Limitations of bioclimate envelope
modelling
Predictions of future ranges based on
bioclimate envelope models assume
species will be able to migrate into the
new areas that, in the future, have their
preferred climates. If a species is a poor
disperser, or if it inhabits a region with
many barriers to dispersal, this may not be
a good assumption.
Thus bioclimate models are probably most
appropriate for species that are good
dispersers although there is evidence that
even poor dispersers are able to expand
their ranges through rare, long-distance
dispersal events
Conclusions
Bioclimate envelope models can be a useful
first step in predicting species’ potential
range changes in the face of climate
change
It is necessary to bear in mind their
limitations and to use the models with
species that are most likely to meet the
assumptions of the models. They will be
more useful at larger scales.
Fig. 5 Schematic example of how different factors may affect the distribution of
species across varying spatial scales. Characteristic 'scale domains' are proposed
within which certain variables can be identified as having a dominant control over
species distributions. Approximate spatial extents have been assigned to categories
of scale based in part on Willis & Whittaker (2002). It is assumed that large spatial
extents are associated with coarse data resolutions, and small extents with fine data
resolutions.
Solutions
“It is not NASA's role to develop solutions or
public policies related to global climate
change. Instead, the agency's mission is
to provide the scientific data needed to
understand climate change and to
evaluate the impact of efforts to control it.”
http://climate.jpl.nasa.gov/solutions/
Individual action
A guide to reducing personal greenhouse gas emissions
from U.S. Environmental Protection Agency
http://www.epa.gov/climatechange/wycd/index.html
Personal Emissions Calculator
A tool from the U.S. E.P.A. to estimate your greenhouse
gas emissions and explore how to reduce them.
http://www.epa.gov/climatechange/wycd/calculator/ind_c
alculator.html
We need corporate action as well
as individual action. Get involved
in the political process.
Vote, write to newspapers and politicians,
blog, support appropriate organizations