field ecology's future - DiscussWorldIssues - Socio-Economic Religion and Political Uncensored Debate

**Butiqueso** · 05-10-2012, 11:44 PM

I found this most interesting and thought others might too.

10 May 2012, 2.04pm AEST
The end of field ecology?

The image of the bearded, grubby ecologist, out-dated spectacles askew and sporting an eccentric grin of geeky, scientific relish, is one that is shared by many, including novice ecologists themselves. But as ecology has matured into a full-fledged, hard-core, mathematical science on par with physics…
Director, Ecological Modelling at University of Adelaide

"The image of the bearded, grubby ecologist, out-dated spectacles askew and sporting an eccentric grin of geeky, scientific relish, is one that is shared by many, including novice ecologists themselves.

But as ecology has matured into a full-fledged, hard-core, mathematical science on par with physics, chemistry and genetics (and is arguably one of the most important sciences of our times given how badly we’ve trashed our only home – planet Earth), its sophistication now threatens to render many of the traditional aspects of ecology redundant, or at least, much less important.

As a person who cut his teeth in field ecology (with all the associated dirt, dangers, bites, stings, discomfort, thrills, headaches and disasters), I’ve had my fair share of fun and excitement collecting ecological data. There’s something quaintly Victorian about the romantic and obsessive naturalist collecting data to the exclusion of nearly all other aspects of civilised life. The intrepid adventurer in some of us takes over (probably influenced by the likes of David Attenborough) and we convince ourselves that our quest for the lonely datum will heal all of the Earth’s ailments.

Err, probably not.

As I’ve matured in ecology and embraced its mathematical complexity and beauty, the recurring dilemma is that there are never enough data to answer the really big questions. We have sampled only a fraction of extant species, we know embarrassingly little about how ecosystems respond to disturbances, and we understand next to nothing about the complexities of ecosystem services. And let’s not forget our infancy in quantifying extinction synergies and predicting how human endeavour and climate change will affect ecosystems of the future. Multiply this uncertainty by several orders of magnitude for ocean life.

The upshot is that ecologists have been searching for proxies and indicators of biodiversity patterns and processes. The ultimate aim is to predict how they work (or fail) based entirely on decidedly non-biological features.

Collecting data in the field is hard work. Ben Rawson/Conservation International

A case in point is one that I’m most familiar with – the use of “surrogates” in marine ecology. This uses a relatively easy-to-sample species (or group of them) to predict the distribution of many more species. We have also done some work to predict coral reef fish diversity using little more than the position of the reef (latitude and distance to shore), and we have inferred the extinction risk of coral reef fish using nothing more than the shape and isolation of reefs on which they live.

I even remember once that Hugh Possingham wished out loud at a conference that he hoped we’d never have to collect real biological data again if we got our maths right. That might be a little far-fetched, but it highlights my main point.

A new study we published recently demonstrates this component well. Thanks to the hard work of one of my post-doctoral fellows and several clever colleagues, the paper tests a fairly simple idea – by taking a photo of an area where animals hang out, one can estimate how many different species are there.

We used datasets comprising painstakingly collected surveys of coral reef fish in the Great Barrier Reef, and compared these to habitat photos taken at spatial scales ranging from single transects to entire reef complexes. We then measured the amount of “complexity” in the photo using something called the “mean information gain”. This metric essentially measures how complex the image is; in other words, it’s a proxy for habitat complexity, which tends to correlate rather well with the number of species in that particular area.

It turns out that we could explain up to 29% of the variance in fish species composition, 33% in total fish abundance, and 25% in fish community structure.

Now, this might not seem like a terribly high predictive capacity, but in ecology, it explains a remarkably large component of these biodiversity measures relative to most other studies. And all this from merely taking a photograph.

I’m not suggesting (as the title of this exposé implies) that we need to abandon all ecological sampling studies; however, we should be constructing ever-more-efficient ways to estimate biodiversity patterns and processes using such short cuts. They’re less time-consuming, more cost-effective and potentially cover areas that are difficult or impossible to sample directly.

A version of this article appeared on Corey’s blog, ConservationBytes.

From
" Corey Bradshaw

Director, Ecological Modelling at University of Adelaide

Disclosure Statement

Corey Bradshaw receives funding from the Australian Research Council, the South Australia Premier's Science and Research Fund and the Australian Centre for Ecological Analysis and Synthesis.

The Conversation provides independent analysis and commentary from academics and researchers.

Founding and Strategic Partners are CSIRO, Melbourne, Monash, RMIT, UTS and UWA. Members are Deakin, Flinders, Murdoch, QUT, Swinburne, UniSA, UTAS, and VU.
"

**Biradallo** · 05-11-2012, 12:30 AM

"The image of the bearded, grubby ecologist, out-dated spectacles askew and sporting an eccentric grin of geeky, scientific relish, is one that is shared by many, including novice ecologists themselves. Hey! I don't wear spectacles

I think there will always be a place for field ecologists for the very simple reason that models need to be based on real data. There are still many questions that can't be answered by mathematical models as we simply don't have any data to build those models on.

Models can be cool for big theoretical questions where a lot of field work has already been done. Not all ecologists work on the big questions. Some of us work with single species.

In my current work with invasive species, it's the little questions that are often the most important. They can only be answered by the painstaking process of collecting data in the field. Same as when I was working on Paragalaxiid fish in Tasmania. Some of these fish were discovered as late as 1976 and virtually no data had been collected on them. You can't build models when you don't know things like where and when the fish breed, how many offspring they have, how many of the offspring survive, how long they live, age of sexual maturity, habitat preferences and a load of other factors. We had none of that data. It required two years of hard work to barely scratch the surface.

**Butiqueso** · 05-11-2012, 12:36 AM

Making sense there, Teleost.
Thanks.
ooops I just recalled reading about some research in the amazon, trying to establish general principles about minimum sizes for conservation areas .
Samething ... needing real raw data before extrapolating ... E.O Wilson in Biophilia.

**majestictwelve** · 05-11-2012, 12:57 AM

Hey! I don't wear spectacles

I think there will always be a place for field ecologists for the very simple reason that models need to be based on real data. There are still many questions that can't be answered by mathematical models as we simply don't have any data to build those models on.

Models can be cool for big theoretical questions where a lot of field work has already been done. Not all ecologists work on the big questions. Some of us work with single species.

In my current work with invasive species, it's the little questions that are often the most important. They can only be answered by the painstaking process of collecting data in the field. Same as when I was working on Paragalaxiid fish in Tasmania. Some of these fish were discovered as late as 1976 and virtually no data had been collected on them. You can't build models when you don't know things like where and when the fish breed, how many offspring they have, how many of the offspring survive, how long they live, age of sexual maturity, habitat preferences and a load of other factors. We had none of that data. It required two years of hard work to barely scratch the surface.

I do not think that anything will or can replace field data Teleost, but there should be a place for modelling based on perceived concepts, this theoretical data should however come with a tag that clearly spells out the error or reliability component.

In my opinion, this method may be convenient in initial information gathering for a project but cannot be compared to ground based data collection.

And by the way I have seen some shocking models……

**chechokancho** · 05-11-2012, 01:19 AM

I suppose this story is just a statement of reality: field work will always be required, and modelling is an efficient way to look at the environment.

It has been this way for a long time.

As time goes on there is greater development and accuracy of modelling, with computing, gis, satellite imaging (colour, infrared, water etc) and who knows what.

We still need field data to feed into and "build" the models assumptions, then run the model, then back out to the field to see how accurate the model was.

**Butiqueso** · 05-11-2012, 01:22 AM

I suppose this story is just a statement of reality: field work will always be required, and modelling is an efficient way to look at the environment.
...
We still need field data to feed into and "build" the models assumptions, then run the model, then back out to the field to see how accurate the model was.

That was my guess ... the cycle will always be needed for verification and modification.

I can certainly understand why early models are so poor ... would HATE to be the person to put a first run up in public.

**SasortFkire** · 05-11-2012, 01:52 AM

A new study we published recently demonstrates this component well. Thanks to the hard work of one of my post-doctoral fellows and several clever colleagues, the paper tests a fairly simple idea – by taking a photo of an area where animals hang out, one can estimate how many different species are there. As new technology comes along I imagine there may be less need to actually get out and about as much. For example stuff like satellite imagery and aerial photography combined with GIS software is proving very useful for mapping vegetation types, but only in a rather broad and general way. In forests with a close canopy you can't see what's underneath. Bit hard to know what's actually there if some trained person doesn't go and have a look. How does one know if there is a particularly nasty weed growing there, or a rare and threatened species. If I were an ecologist, I wouldn't be stressing about being stuck in an office all day and not getting out to do field work just yet.

**chechokancho** · 05-11-2012, 01:53 AM

Environmental modelling can be straight forward under the right conditions. But there are so many factors that can throw a spanner in the works. Eg climate variation from year to year, soil type, aspect, species interactions, bushfires wiping out plots etc. Measuring things at the same time of year is important and depending on recent weather that can change things a lot. It can take a lot of years to get a grip on what is average/within a normal range in an environment.

My favourite field notes were from early days growing trees on coal mine rehab in the Hunter Valley. Next to the missing measurement was written "spontaneous combustion"!

(Which can actually happen to coal under the right conditions).

**Buincchotourbss** · 05-11-2012, 02:05 AM

Teleost but you do have all the other attributes?? Ducking for cover

fortunately well hidden in the bush by being grubby (well known method of observing while being unobserved.

Hi Podzol that must have added to the atmosphere of the work (did you get danger money ????)

Verification will always be needed, if the models are going to be of any use in the long term. No computer model is able to match the complexities and interactions of the natural world.

**SasortFkire** · 05-11-2012, 02:10 AM

Ducking for cover fortunately well hidden in the bush by being grubby (well known method of observing while being unobserved.

As long as you stay downwind, no-one would ever know you were there...

*sniff, sniff*

**Buincchotourbss** · 05-11-2012, 02:17 AM

As long as you stay downwind, no-one would ever know you were there...

*sniff, sniff*

That goes without saying well known tracking technique, although grubbyness is from rubbing in animal droppings to hide smell. Probably way too much information.

**Heopretg2006** · 05-11-2012, 05:38 AM

Next-generation DNA sequencing for the win

Go into an area, pick up some scats, run the DNA to identify every species in each scat, and bam! - fauna survey on your desktop.

The future looks bright

**Biradallo** · 05-12-2012, 05:11 AM

Teleost but you do have all the other attributes?? As in Grubby, Bearded, and geeky grin?

My Mrs and my Mum seem to think so.

**GeraldCortis** · 05-12-2012, 05:20 AM

As in Grubby, Bearded, and geeky grin?

My Mrs and my Mum seem to think so.

Ah, so you have the same problem I do.. Their sense of smell is too acute.

**Biradallo** · 05-12-2012, 05:23 AM

At least I no longer smell of fish on top of it

**GeraldCortis** · 05-12-2012, 05:49 AM

At least I no longer smell of fish on top of it

fish, is really over the top. Smelling of fish could get you grounded or worse.

**Butiqueso** · 05-14-2012, 01:30 PM

love this thread.
and enjoying reading this again

http://conservationbytes.com/2012/05...ogy/#more-7126

05-10-2012, 11:44 PM	#1
Butiqueso Join Date Nov 2005 Posts 488 Senior Member	field ecology's future I found this most interesting and thought others might too. 10 May 2012, 2.04pm AEST The end of field ecology? The image of the bearded, grubby ecologist, out-dated spectacles askew and sporting an eccentric grin of geeky, scientific relish, is one that is shared by many, including novice ecologists themselves. But as ecology has matured into a full-fledged, hard-core, mathematical science on par with physics… Director, Ecological Modelling at University of Adelaide "The image of the bearded, grubby ecologist, out-dated spectacles askew and sporting an eccentric grin of geeky, scientific relish, is one that is shared by many, including novice ecologists themselves. But as ecology has matured into a full-fledged, hard-core, mathematical science on par with physics, chemistry and genetics (and is arguably one of the most important sciences of our times given how badly we’ve trashed our only home – planet Earth), its sophistication now threatens to render many of the traditional aspects of ecology redundant, or at least, much less important. As a person who cut his teeth in field ecology (with all the associated dirt, dangers, bites, stings, discomfort, thrills, headaches and disasters), I’ve had my fair share of fun and excitement collecting ecological data. There’s something quaintly Victorian about the romantic and obsessive naturalist collecting data to the exclusion of nearly all other aspects of civilised life. The intrepid adventurer in some of us takes over (probably influenced by the likes of David Attenborough) and we convince ourselves that our quest for the lonely datum will heal all of the Earth’s ailments. Err, probably not. As I’ve matured in ecology and embraced its mathematical complexity and beauty, the recurring dilemma is that there are never enough data to answer the really big questions. We have sampled only a fraction of extant species, we know embarrassingly little about how ecosystems respond to disturbances, and we understand next to nothing about the complexities of ecosystem services. And let’s not forget our infancy in quantifying extinction synergies and predicting how human endeavour and climate change will affect ecosystems of the future. Multiply this uncertainty by several orders of magnitude for ocean life. The upshot is that ecologists have been searching for proxies and indicators of biodiversity patterns and processes. The ultimate aim is to predict how they work (or fail) based entirely on decidedly non-biological features. Collecting data in the field is hard work. Ben Rawson/Conservation International A case in point is one that I’m most familiar with – the use of “surrogates” in marine ecology. This uses a relatively easy-to-sample species (or group of them) to predict the distribution of many more species. We have also done some work to predict coral reef fish diversity using little more than the position of the reef (latitude and distance to shore), and we have inferred the extinction risk of coral reef fish using nothing more than the shape and isolation of reefs on which they live. I even remember once that Hugh Possingham wished out loud at a conference that he hoped we’d never have to collect real biological data again if we got our maths right. That might be a little far-fetched, but it highlights my main point. A new study we published recently demonstrates this component well. Thanks to the hard work of one of my post-doctoral fellows and several clever colleagues, the paper tests a fairly simple idea – by taking a photo of an area where animals hang out, one can estimate how many different species are there. We used datasets comprising painstakingly collected surveys of coral reef fish in the Great Barrier Reef, and compared these to habitat photos taken at spatial scales ranging from single transects to entire reef complexes. We then measured the amount of “complexity” in the photo using something called the “mean information gain”. This metric essentially measures how complex the image is; in other words, it’s a proxy for habitat complexity, which tends to correlate rather well with the number of species in that particular area. It turns out that we could explain up to 29% of the variance in fish species composition, 33% in total fish abundance, and 25% in fish community structure. Now, this might not seem like a terribly high predictive capacity, but in ecology, it explains a remarkably large component of these biodiversity measures relative to most other studies. And all this from merely taking a photograph. I’m not suggesting (as the title of this exposé implies) that we need to abandon all ecological sampling studies; however, we should be constructing ever-more-efficient ways to estimate biodiversity patterns and processes using such short cuts. They’re less time-consuming, more cost-effective and potentially cover areas that are difficult or impossible to sample directly. A version of this article appeared on Corey’s blog, ConservationBytes. From " Corey Bradshaw Director, Ecological Modelling at University of Adelaide Disclosure Statement Corey Bradshaw receives funding from the Australian Research Council, the South Australia Premier's Science and Research Fund and the Australian Centre for Ecological Analysis and Synthesis. The Conversation provides independent analysis and commentary from academics and researchers. Founding and Strategic Partners are CSIRO, Melbourne, Monash, RMIT, UTS and UWA. Members are Deakin, Flinders, Murdoch, QUT, Swinburne, UniSA, UTAS, and VU. " Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 12:30 AM	#2
Biradallo Join Date Oct 2005 Posts 512 Senior Member	"The image of the bearded, grubby ecologist, out-dated spectacles askew and sporting an eccentric grin of geeky, scientific relish, is one that is shared by many, including novice ecologists themselves. Hey! I don't wear spectacles I think there will always be a place for field ecologists for the very simple reason that models need to be based on real data. There are still many questions that can't be answered by mathematical models as we simply don't have any data to build those models on. Models can be cool for big theoretical questions where a lot of field work has already been done. Not all ecologists work on the big questions. Some of us work with single species. In my current work with invasive species, it's the little questions that are often the most important. They can only be answered by the painstaking process of collecting data in the field. Same as when I was working on Paragalaxiid fish in Tasmania. Some of these fish were discovered as late as 1976 and virtually no data had been collected on them. You can't build models when you don't know things like where and when the fish breed, how many offspring they have, how many of the offspring survive, how long they live, age of sexual maturity, habitat preferences and a load of other factors. We had none of that data. It required two years of hard work to barely scratch the surface. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 12:36 AM	#3
Butiqueso Join Date Nov 2005 Posts 488 Senior Member	Making sense there, Teleost. Thanks. ooops I just recalled reading about some research in the amazon, trying to establish general principles about minimum sizes for conservation areas . Samething ... needing real raw data before extrapolating ... E.O Wilson in Biophilia. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 12:57 AM	#4
majestictwelve Join Date Oct 2005 Posts 515 Senior Member	Hey! I don't wear spectacles I think there will always be a place for field ecologists for the very simple reason that models need to be based on real data. There are still many questions that can't be answered by mathematical models as we simply don't have any data to build those models on. Models can be cool for big theoretical questions where a lot of field work has already been done. Not all ecologists work on the big questions. Some of us work with single species. In my current work with invasive species, it's the little questions that are often the most important. They can only be answered by the painstaking process of collecting data in the field. Same as when I was working on Paragalaxiid fish in Tasmania. Some of these fish were discovered as late as 1976 and virtually no data had been collected on them. You can't build models when you don't know things like where and when the fish breed, how many offspring they have, how many of the offspring survive, how long they live, age of sexual maturity, habitat preferences and a load of other factors. We had none of that data. It required two years of hard work to barely scratch the surface. I do not think that anything will or can replace field data Teleost, but there should be a place for modelling based on perceived concepts, this theoretical data should however come with a tag that clearly spells out the error or reliability component. In my opinion, this method may be convenient in initial information gathering for a project but cannot be compared to ground based data collection. And by the way I have seen some shocking models…… Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 01:19 AM	#5
chechokancho Join Date Oct 2005 Posts 465 Senior Member	I suppose this story is just a statement of reality: field work will always be required, and modelling is an efficient way to look at the environment. It has been this way for a long time. As time goes on there is greater development and accuracy of modelling, with computing, gis, satellite imaging (colour, infrared, water etc) and who knows what. We still need field data to feed into and "build" the models assumptions, then run the model, then back out to the field to see how accurate the model was. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 01:22 AM	#6
Butiqueso Join Date Nov 2005 Posts 488 Senior Member	I suppose this story is just a statement of reality: field work will always be required, and modelling is an efficient way to look at the environment. ... We still need field data to feed into and "build" the models assumptions, then run the model, then back out to the field to see how accurate the model was. That was my guess ... the cycle will always be needed for verification and modification. I can certainly understand why early models are so poor ... would HATE to be the person to put a first run up in public. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 01:52 AM	#7
SasortFkire Join Date Oct 2005 Posts 377 Senior Member	A new study we published recently demonstrates this component well. Thanks to the hard work of one of my post-doctoral fellows and several clever colleagues, the paper tests a fairly simple idea – by taking a photo of an area where animals hang out, one can estimate how many different species are there. As new technology comes along I imagine there may be less need to actually get out and about as much. For example stuff like satellite imagery and aerial photography combined with GIS software is proving very useful for mapping vegetation types, but only in a rather broad and general way. In forests with a close canopy you can't see what's underneath. Bit hard to know what's actually there if some trained person doesn't go and have a look. How does one know if there is a particularly nasty weed growing there, or a rare and threatened species. If I were an ecologist, I wouldn't be stressing about being stuck in an office all day and not getting out to do field work just yet. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 01:53 AM	#8
chechokancho Join Date Oct 2005 Posts 465 Senior Member	Environmental modelling can be straight forward under the right conditions. But there are so many factors that can throw a spanner in the works. Eg climate variation from year to year, soil type, aspect, species interactions, bushfires wiping out plots etc. Measuring things at the same time of year is important and depending on recent weather that can change things a lot. It can take a lot of years to get a grip on what is average/within a normal range in an environment. My favourite field notes were from early days growing trees on coal mine rehab in the Hunter Valley. Next to the missing measurement was written "spontaneous combustion"! (Which can actually happen to coal under the right conditions). Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 02:05 AM	#9
Buincchotourbss Join Date Nov 2005 Posts 479 Senior Member	Teleost but you do have all the other attributes?? Ducking for cover fortunately well hidden in the bush by being grubby (well known method of observing while being unobserved. Hi Podzol that must have added to the atmosphere of the work (did you get danger money ????) Verification will always be needed, if the models are going to be of any use in the long term. No computer model is able to match the complexities and interactions of the natural world. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 02:10 AM	#10
SasortFkire Join Date Oct 2005 Posts 377 Senior Member	Ducking for cover fortunately well hidden in the bush by being grubby (well known method of observing while being unobserved. As long as you stay downwind, no-one would ever know you were there... sniff, sniff Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 02:17 AM	#11
Buincchotourbss Join Date Nov 2005 Posts 479 Senior Member	As long as you stay downwind, no-one would ever know you were there... sniff, sniff That goes without saying well known tracking technique, although grubbyness is from rubbing in animal droppings to hide smell. Probably way too much information. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-11-2012, 05:38 AM	#12
Heopretg2006 Join Date Oct 2005 Posts 531 Senior Member	Next-generation DNA sequencing for the win Go into an area, pick up some scats, run the DNA to identify every species in each scat, and bam! - fauna survey on your desktop. The future looks bright Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-12-2012, 05:11 AM	#13
Biradallo Join Date Oct 2005 Posts 512 Senior Member	Teleost but you do have all the other attributes?? As in Grubby, Bearded, and geeky grin? My Mrs and my Mum seem to think so. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-12-2012, 05:20 AM	#14
GeraldCortis Join Date Oct 2005 Posts 486 Senior Member	As in Grubby, Bearded, and geeky grin? My Mrs and my Mum seem to think so. Ah, so you have the same problem I do.. Their sense of smell is too acute. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-12-2012, 05:23 AM	#15
Biradallo Join Date Oct 2005 Posts 512 Senior Member	At least I no longer smell of fish on top of it Share Share this post on Digg Del.icio.us Technorati Twitter
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05-12-2012, 05:49 AM	#16
GeraldCortis Join Date Oct 2005 Posts 486 Senior Member	At least I no longer smell of fish on top of it fish, is really over the top. Smelling of fish could get you grounded or worse. Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote

05-14-2012, 01:30 PM	#17
Butiqueso Join Date Nov 2005 Posts 488 Senior Member	love this thread. and enjoying reading this again http://conservationbytes.com/2012/05...ogy/#more-7126 Share Share this post on Digg Del.icio.us Technorati Twitter
	Quote