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  1. Hi, I’m interested in doing some niche modelling for a species that I’m studying. I’ve casually followed the use of ecological niche modelling and GARP over the past few years and am now starting to read up about it more. The more I read, however, the more I realize there are so many other newer alternative predictive tools available, such as the new WhyWhere algorithm or some of these novel techniques evaluated in the Elith et al. 2006 paper (e.g., MAXENT, BRT, mars-comm, etc.). It’s difficult to know which one to use? How would you go about deciding which way to go? If I felt that they all were very useful, I might feel more comfortable just sticking with DesktopGARP, but that was one of the lowest performing methods according to the Elith et al. paper. Any advice? Thanks!

  2. Good question Rob but the answer has a lot of facets that I will try to do justice to next week in a longer reply. Think about the assumption in your question “It’s difficult to know which ONE to use?”. There are a number of dimensions across the models you might want to explore – classical vs heuristics, new vs. well researched, plus they more rightly exist in a benefit/cost framework, i.e. an optimal method in your situation might be something really simple that is average.

    I think the OpenModeller group found a bug in the rule archiving part of DesktopGARP that increased the accuracy of the GARP algorithm to the medium group along with GLM and some others. You might want to look into that version but they would have the full story on that though. Then there is the fact that you get higher accuracy with a broader range of variables, particularly monthly temperature and rainfall instead of annual averages reported in S06. Time could be more efficiently spent getting predictor variables optimized.

    I also don’t think the validation process used in Elith et.al. tells the full story either. An in-range random sample from highly autocorrelated data does little more that test goodness of fit. The real test of a niche model is on out-of-range problems, such as detection of new species or invasive species problems, of which there are many documented successes for DesktopGARP. Then there are the types of model not examined, based around k-means, such as reviewed here. I am not saying it is a flawed study, but that it is not complete.

    I am the first to acknowledge that results can sometimes be dissapointing. Its not an exact science yet. You have to do a lot of testing.

  3. I’m interested in doing estuarine benthic species niche modeling But I am unable to get estuarine environmental parameters, is any open source predictive tools available for estuarine ecology?

  4. hi,i am interested in knowing about how organisms are distributed in spatial?we can predict the distribution of organisms by using GARP model.

  5. G’day all,

    Stats not being my field, I would appreciate someone doing the numbers on the correlation between the global NASA AIRS CO2 maps (there are only 3 out, far as I know) and the global annual sea surface temperature range contour map, that I have posted in kindergarten form on the ABC Pool Climate change debating group (of 2 folk, so far, but it is Australia’s public broadcaster’s open website, so far totally uncensored, all welcome). My stuff there is all public domain, but you can mix and match to suit. We hope by late next week to supplant “Nature.”

    It seems to me that most CO2, at least at 8kms up in the troposphere, is over or downwind of where the oceans and seas annually change temperature most. As one would expect, from the chemistry of CO2 and seawater, as per the Clausius- Clapeyron equation, long known. Or cause, warm Cokes fizz when you take the top off, same thing.

    And, would someone like to do the numbers on groundwater depletion vs annual global ice melt? I think those will surprise a few Use the new Anthropogenic Groundwater Depletion AGD, to get a better, fresher rise out of your sea levels.

    My email is p.s.ravenscroft@gmail.com



    Geologist, Closeburn, Queensland, Oz.

  6. Dear David,
    I started reading the Copenhagen Synthesis Report as well and I do have a question that puzzled me ever since. It shows in its figure 2:
    “The change in energy content in different components of the Earth System for two periods: 1961-2003 (blue bars) and 1993-2003 (pink bars)2 (figure 5.4).”

    The energy content change of the earth system for the period 1993 – 2003 according to the figure 2 is 8.9x10E22 Joule. Divided by the area of the earth and the seconds of 10 years this gives 0.55 W/m2.
    The net radiative forcing from the models however in this period I estimated from IPCC AR 4 to be roughly about 1.3 W/m2. IPCC AR 4 says 1.6 W/m2 for 2005 and 20% increase since 1995.
    However, this means the models are off by 0.8 W/m2 for this 10 year period alone in terms of energy conservation. Do I miss something here? Maybe I miss the definition of net radiative forcing or the definition of energy content change?

    Hopefully you or anybody can help me out.
    Best regards

  7. Bob Tisdales has some similar calculations and conclusions in his paper http://www.climatesci.org/publications/pdf/R-334.pdf .
    He quotes the IPCC2007 as calling the 2005 anthropegenic forcing as 1.6(+0.8, -1.0) W/sq meter and solar irradiance change as 0.12(+0.18, -0.06). Then says this corresponds to heat accumulation of 2.8(+1.6, -1.7) x 10E22 joules into the climate system. 2.8/(1.6+0.12) = 1.63 x 10E22 joules heat gain per year for 1 watt/sq meter of forcing. (your calculations are 1.62x10E22 J per 1wm-2 of forcing. Same answer when rounded)

    The only other comment I have is that the IPCC definition of forcing assumes that the stratosphere has reached equilibrium. I don’t know the timescale this takes nor the amount of this lagging effect, but I doubt it is anywhere near the 0.8W/m2 discrepancy you note.

    I have only seriously looked at the science of global warming in the last month or so and am amazed at the number of significant fundamental discrepancies such as this. You can’t get much more fundamental than “is the earth gaining heat content or isn’t it?”.

    Hopefully somebody more knowledgeable will notice this in the “recent comments” section and pop in to educate us.

  8. What is missing here is the increased outward radiation due to higher temperatures. The basic AGW proposition is that current GHG bring in nett 1.6 W/m2 more, and the Earth warms until at equilibrium that is balanced by an increase of 1.6 W/m2 in IR leaving the planet. We’re part-way to equilibrium.

  9. Nick,

    Thank you for your reply. I really appreciate that.
    But I do have still difficulties with this explanation, since net radiative forcing is the difference between incoming energy by radiation and outgoing energy by radiation. This difference integrated over time should be equal to the change in the energy content of the earth system.

    This energy content change is mentioned in the IPCC AR4. The figure caption reads:
    “Figure TS.15. Energy content changes in different components
    of the Earth system for two periods (1961–2003 and 1993–2003).
    Blue bars are for 1961 to 2003; burgundy bars are for 1993 to
    2003. Positive energy content change means an increase in
    stored energy (i.e., heat content in oceans, latent heat from
    reduced ice or sea ice volumes, heat content in the continents
    excluding latent heat from permafrost changes, and latent and
    sensible heat and potential and kinetic energy in the atmosphere).
    All error estimates are 90% confi dence intervals. No estimate of
    confi dence is available for the continental heat gain. Some of
    the results have been scaled from published results for the two
    respective periods. {Figure 5.4}”

    If the figure represents something similar to the energy content change of the whole system, for my opinion net radiative forcing should by energy content change otherwise energy conservation is violated, since CO2 can only hold back incoming energy.
    In order to calculate the energy content change one needs to consider the different systems with heat capacities attached. A surface without a heat capacity attached seems to me for my gut feeling like a virtual energy constant that is added or subtracted on both sides of the equation, fairly arbitrary. One increases the net radiative forcing and balances it with IR radiation in the future from a thin surface layer that will occasionally heat to the temperature Ts. However the difference of 1.6 W/m2 needs to be in the system right now.
    Energy content and conservation of energy is the physical reality, or not. Conservation of IR radiation is not a physical law. Of course the radiative properties are calculated by models, but how does one show that they are correct., if not with real quantities.
    Best regards

  10. Here’s the TAR IPCC definition of the radiative forcing their 1.6 W/m2 (AR4) refers to:

    The radiative forcing of the surface-troposphere system due to the perturbation in or the introduction of an agent (say, a change in greenhouse gas concentrations) is the change in net (down minus up) irradiance (solar plus long-wave; in Wm-2) at the tropopause AFTER allowing for stratospheric temperatures to readjust to radiative equilibrium, but with surface and tropospheric temperatures and state held fixed at the unperturbed values

    Note that it’s before allowing for increased radiation due to warming.

  11. Nick,
    thanks your comment and reading through your link helped. I think the IPCCs anthropogenic radiative forcing values are also referenced back in time to 1750, which I did not account for. So it doesn’t reflect the current radiative imbalance at the tropopause, but the imbalance compared to 1750 before warming as you mentioned in your comment.
    Thanks and best regards

  12. Perhaps someone can answer a basic question about smoothing and end point treatment.

    CRU’s webpage has time series of annual global temperatures, with a smoothed plot. http://www.cru.uea.ac.uk/cru/info/warming/ . There is also a datadownload, complete with smoothed data through 2008.

    This graph shows up in many places.
    Does anybody know what the smoothing algorithm is, and how the end points are handled?

    My interest arose from noting that JPL NASA is showing a perfectly flat line for smoothed temp over the last 3 years at
    http://www.cru.uea.ac.uk/cru/info/warming/ even though the rest of the graph appears to be identical to the CRU annual+smoothed global temp plot.

  13. Charlie, you have raised a question that has puzzled me for some time – the caption of that graph does not even mention the thick black line, let alone say how the endpoints are handled!
    There is a reference to a paper by Brohan et al, but it is not explained there.
    You could try writing to the email address given at the bottom of the page, cru@uea.ac.uk, but given that the name on the page is Phil Jones, you are unlikely to get a satisfactory answer (see recent climate audit posts).

    There is another web page
    that does explain how the smoothing is done – 21-point binomial filter plus repeating the final year beyond the endpoint. But the smoothed graph there looks DIFFERENT from the graph on the page you refer to, so clearly a different method is used there.

  14. Thanks Paul. The 2nd link you gave has a link pointing to the coefficients of the 21 point filter and a good discussion on how they just extend the final data point.

    The discussion on that page is yet another example of confirmation bias at work. Apparently the CRU would update the historical graph in March, just using Jan/Feb of that year as the annual average anomaly. That was OK in 2007 when it made the graph rise rapidly, but in 2008 that made the smooth temperature fall and that triggered a review of procedures.

    This may explains the strange graph at climate.nasa.gov — the initial graph from CRU in March 2008 showed a strong downturn. Then they discovered the error. Perhaps NASA took care of the error by just flatlining the smoothed curve for the last few years and hasn’t gotten around to doing a 2009 update.

  15. Phil Jones responded quickly to my e-mail inquiry sent yesterday.

    He included a pdf of Jone et al 1986a, Northern Hemisphere Surface Air Temperature Variations: 1851-1984 and pointed me to Figure 5.
    The caption for that figure mentions 13 point Gaussian filter “designed to suppress variations on timescales less than 10 years.” and “six extra years are used at each end with values equal to the mean of the six years at the beginning/end of each curve”.

    This clarified his short e-mail in which he told me that “Most plots are either 10-year or 20-year Gaussian filters.”

    Although I haven’t figured out the specific “20 year Gaussian filter” used, just doing 3 iterations of the IPCC 13 point Gaussian filter (about 20 year half amplitude by my calculation) does an emulation of the smoothed datapoints of the CRU data close enough for my purposes — which is to check what is being posted by JPL NASA at their Key Climate Indicators website intended for the general public.

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