White Nose Syndrome in Bats

Part 1: White Nose Syndrome in Bats

00:00:07.14 Hi.
00:00:08.06 My name is Winifred Frick,
00:00:09.19 and I'm an Assistant Adjunct Professor
00:00:12.07 in the Department of Ecology and Evolutionary Biology
00:00:14.25 at the University of California in Santa Cruz.
00:00:17.25 I'm gonna be talking today about my research that I did a couple years ago
00:00:22.12 on the impacts of a disease called white-nose syndrome
00:00:26.01 on a bat, the little brown bat,
00:00:28.14 that used to be really common in the northeastern United States.
00:00:33.02 White-nose syndrome is a new disease
00:00:34.25 that was only discovered a couple of years ago.
00:00:37.14 And it's caused by a fungus
00:00:39.08 that grows on bats while they're hibernating.
00:00:44.07 It was first discovered, actually in 2007,
00:00:47.13 when researchers from the New York Department of Environmental Conservation
00:00:51.07 went in to do their annual surveys of hibernating bats.
00:00:56.15 So, biologists go in,
00:00:59.12 and the bats in the northeastern US
00:01:02.02 aggregate during the winter into what we call hibernacula.
00:01:06.02 And these are caves and mines where bats spend the winter.
00:01:08.29 And biologists from different states go in and count them every year
00:01:13.01 to see how many are there and to monitor them.
00:01:15.17 And part of the motivation for this is
00:01:18.12 because we have a species called the Indiana bat that is federally endangered...
00:01:22.18 on the endangered species list,
00:01:24.12 so people need to go in and count so we can monitor
00:01:26.21 how those species are being...
00:01:29.01 how they're faring.
00:01:30.17 And in 2007, people noticed something they had never seen before,
00:01:33.23 which is a bunch of bats dead on the cave floor,
00:01:37.06 and this funny white fungus growing on their faces.
00:01:40.29 It was later that cavers actually came forward
00:01:43.18 with a picture of bats with white fungus on their...
00:01:46.10 white fluffy stuff on their faces, in 2006.
00:01:49.02 So, we can date the introduction of white-nose syndrome to 2006,
00:01:53.22 but we didn't know it was a problem until 2007.
00:02:00.06 The main concern with white-nose syndrome
00:02:02.21 is that it's causing massive mortality of hibernating bats
00:02:06.28 in their hibernacula during the wintertime.
00:02:09.14 So, the bats go into these places,
00:02:11.22 and they spend all winter there, in hibernation.
00:02:14.17 They actually turn their metabolisms off
00:02:16.28 and spend the whole winter,
00:02:19.16 and they're what we call torpid.
00:02:21.15 So, they're mammals, like you and me,
00:02:23.06 but they actually will turn their... turn their...
00:02:25.29 turn their bodies off to be able to survive the whole winter.
00:02:28.28 And during that time, this is when this...
00:02:31.14 what we now know is a fungus grows on them.
00:02:34.19 And from what we can understand
00:02:37.02 -- we're still trying to figure out all the mechanisms
00:02:39.11 of why this disease is killing all the bats --
00:02:42.27 it's causing them to wake up too frequently while they're hibernating,
00:02:47.25 and that makes them use up their fat reserves,
00:02:49.28 and then they die before spring comes.
00:02:52.07 So, this picture here,
00:02:54.23 these different pictures here that I'm showing you,
00:02:57.01 are piles, literally piles, of dead bat carcasses on cave floors.
00:03:01.22 This is from a cave in Vermont.
00:03:05.12 So, the symptoms of white-nose syndrome
00:03:07.27 are this characteristic fungal growth on the face of the bats.
00:03:11.16 This is how it got its name, white-nose syndrome,
00:03:13.17 but actually the fungus grows all over their wings and tail membranes.
00:03:18.06 Also, the bats start doing weird things in the winter.
00:03:20.23 They should be hunkered down and hibernating all winter long,
00:03:24.01 but instead they're getting out, flying about...
00:03:26.17 flying out on the landscape.
00:03:28.02 Back in 2007, there were all these reports of people
00:03:30.27 saying that they were seeing bats flying out into their backyards
00:03:34.05 in the middle...
00:03:36.06 even when there was snow on the ground,
00:03:38.02 and this is something that these little critters should not be doing.
00:03:40.17 And then in springtime,
00:03:42.22 if the bats manage to survive,
00:03:45.02 we see that they have these terrible wing lesions.
00:03:49.07 And basically the fungus has been sort of eating at their wings all winter long,
00:03:53.01 and they have all of these terrible injuries.
00:03:57.26 Well, it took a couple years to figure out
00:04:03.01 exactly what was causing white-nose syndrome.
00:04:05.08 It was... it was originally named a syndrome
00:04:07.15 because we didn't know what was going on.
00:04:09.10 We didn't know what that white fluffy stuff was on their faces.
00:04:11.26 We now know that that is caused
00:04:14.21 by a pathogenic fungus called Geomyces destructans.
00:04:17.21 The fungus wasn't known to science previously,
00:04:20.07 so it's newly described.
00:04:22.21 And so David Blehert at the National Wildlife Health Center and others
00:04:28.04 aptly named it Geomyces destructans
00:04:30.13 because of the destruction that it's wreaking on our...
00:04:32.29 on our bat faunas.
00:04:34.16 And so what the fungus does is
00:04:36.21 it actually grows into the skin issues.
00:04:39.17 It invades the different skin layers.
00:04:43.23 It's sort of like a really terrible case of athlete's foot.
00:04:48.04 But the bats really depend on their... on their skin tissues
00:04:53.12 for all sorts of physiological processes,
00:04:59.02 and... and as I said previously,
00:05:01.27 we're still working out some of the mechanisms of death.
00:05:03.23 It may be that this fungus just irritates them,
00:05:06.20 and that's what wakes them up.
00:05:08.05 Or it could be that the fungus causes them
00:05:11.15 to become dehydrated, and they've got to wake up to try to find water.
00:05:15.19 Scientists are still working out some of those questions.
00:05:20.06 But we do know that they wake up too frequently,
00:05:22.10 and that they starve to death before... before spring comes.
00:05:27.23 So, the motivation for the study that I'm talking about today...
00:05:33.05 and you have to remember that this was...
00:05:35.01 we started this study back in 2008 and 2009,
00:05:37.18 when we didn't really know very much about white-nose syndrome at all.
00:05:41.09 We just knew that lots of bats were dying.
00:05:43.23 And so what we wanted to know was,
00:05:47.04 were populations in the northeastern United States...
00:05:50.09 because that's where white-nose syndrome hit...
00:05:52.16 it started... it was first discovered in Albany, New York,
00:05:55.18 in upstate New York...
00:05:57.27 were these populations okay before WNS hit?
00:06:00.21 Were they... were...
00:06:03.21 there were some hypotheses about...
00:06:06.00 well, perhaps the bats were being stressed
00:06:09.11 by pesticide use or depleted insect populations,
00:06:15.15 and that was causing them to go into their hibernacula
00:06:19.12 in more stressed conditions,
00:06:21.28 and that perhaps was causing
00:06:26.01 some sort of secondary infection to emerge.
00:06:28.02 So, we wanted to know,
00:06:29.24 how were these populations doing before white-nose syndrome hit?
00:06:31.28 And then we wanted to know,
00:06:34.11 what was going to be the impact of all this mortality
00:06:39.04 on this regional population of this bat that was really common?
00:06:42.22 Little brown... little brown bats are the bat
00:06:45.10 that's in people's attics or in their barns.
00:06:47.21 They're really quite a common species
00:06:49.23 up in the northeastern United States.
00:06:51.26 And so we wanted to ask this question of,
00:06:54.00 what is the potential impact
00:06:57.08 of this mortality to this population?
00:07:00.12 Do we need to be worried about the persistence of this species?
00:07:04.22 So, to do that,
00:07:07.01 the study was sort of conducted in kind of two different stages, really.
00:07:11.26 The first involved, actually,
00:07:15.15 the use of a data set that my co-author, Scott Reynolds,
00:07:17.27 collected for 17 years.
00:07:20.25 You can see here this barn.
00:07:23.17 This is the Peterborough barn in Peterborough, New Hampshire.
00:07:26.09 And it has a colony...
00:07:28.11 had a colony of little brown bats roosting in the attic.
00:07:31.15 And so, as part of his PhD project,
00:07:33.18 when he was a PhD student with Tom Kunz at Boston University,
00:07:38.05 he'd go to this barn and he'd capture the bats.
00:07:42.17 Here, I have a picture of a mist net.
00:07:45.07 And the bat gets captured in a mist net.
00:07:48.06 You put the mist nets around, and bats get tangled in them.
00:07:51.13 It doesn't hurt them, but they get tangled,
00:07:53.27 and then you can take the bat out.
00:07:55.24 And then you can put a little forearm band
00:07:58.12 -- it's just a little a little piece of metal
00:08:00.23 that you can squeeze around the forearm;
00:08:02.27 you can see it here --
00:08:04.07 onto the bat.
00:08:05.02 And it has a unique ID.
00:08:07.10 And then you let the bat go,
00:08:08.28 and it lives out its life in the barn.
00:08:10.23 And you go back every year,
00:08:13.10 and you try to capture the bats each year.
00:08:16.07 And you find out... you basically
00:08:20.16 develop a dataset that has this record of how long the bats live for.
00:08:25.01 And we were able to use that over this 17-year time frame
00:08:29.19 to estimate what the probability
00:08:32.12 that a bat lives from year to year is.
00:08:33.23 And we call that annual survival rates.
00:08:36.04 And we were also able to estimate the fecundity,
00:08:38.18 or the number of bats...
00:08:40.16 of young that adult females produce.
00:08:43.29 And as well as the probability that the female bats
00:08:47.00 come back to this barn to breed.
00:08:49.19 So, this gave us quite a bit of information about the...
00:08:53.16 what we call the population dynamics of the bats.
00:08:56.15 So, we were able to use that information.
00:08:59.15 In addition, as I mentioned,
00:09:01.17 state biologists go in
00:09:04.16 and they count the bats in their winter hibernacula,
00:09:08.18 in these caves and mines where bats spend the winter.
00:09:10.07 So, we have a record of how many bats
00:09:12.15 are at these sites from year to year.
00:09:14.18 And we can also use that information
00:09:16.16 to try to estimate what the population dynamics are.
00:09:20.13 How stable are the populations?
00:09:22.07 Are there fewer bats every year at these caves and mines?
00:09:25.08 Are there more bats every year at these caves and mines?
00:09:27.14 Or are there roughly the same number from year to year?
00:09:32.00 And so, we kind of combine these two pieces of information,
00:09:35.00 because the demographic data
00:09:36.23 -- the data from that that bat banding study --
00:09:39.18 gives us a really in-depth look,
00:09:41.21 but we only had it from one barn.
00:09:43.01 So, we didn't know if that would be representative of the population...
00:09:47.27 the regional population as a whole.
00:09:50.00 Whereas these data from the winter hibernacula
00:09:52.11 -- these count data --
00:09:54.05 are a little bit more of a rough estimate
00:09:59.09 of how the population is doing.
00:10:00.25 It's not as precise of information,
00:10:03.06 as detailed of information,
00:10:05.16 yet we had it for 22 different hibernacula
00:10:08.05 across the northeastern US.
00:10:11.27 So, we had kind of a broader regional picture.
00:10:14.15 So, combining those two datasets...
00:10:17.16 so, looking at the demographic rates from the 17 year...
00:10:20.18 what we call a mark-recapture
00:10:23.07 because we mark the bats and then we recapture the bats...
00:10:25.04 from this maternity colony of little brown bats,
00:10:27.28 we estimate annual survival for adults and juveniles,
00:10:31.13 as well as the breeding probabilities.
00:10:33.04 And then from the hibernacula counts,
00:10:37.09 we were able to estimate population growth rates.
00:10:41.06 So... over the past 30 years...
00:10:43.26 because they've been doing these surveys for a long time.
00:10:47.20 So, first I'll just show you a little bit of the data.
00:10:51.27 This is actually data that didn't appear in the Science paper,
00:10:54.29 but is in a previous paper,
00:10:57.09 but we used it in the Science paper.
00:10:58.27 What this shows us is... on the x-axis, we have the year.
00:11:04.05 So, this is just the range of years that the study took place over.
00:11:08.00 So, Scott started banding the bats back in 1993,
00:11:11.11 and then we... he did the study up through 2008.
00:11:17.01 And then on the y-axis,
00:11:21.06 we have the annual survival probability of adult female bats.
00:11:25.09 So, this is the probability that an adult female bat
00:11:29.09 lives from year to year.
00:11:31.11 And what this graph shows us is a couple things.
00:11:34.28 One is that, overall,
00:11:37.25 there's a... there's a fair bit of variability
00:11:40.16 in the survival of female bats.
00:11:42.25 It ranges from about 0.6
00:11:45.26 -- so, a 60% chance of living from one year to the next --
00:11:49.21 to about 0.9.
00:11:52.17 And the other thing is that we found in this study
00:11:54.28 that the chance that you survive from year to year
00:11:58.13 is actually strongly correlated
00:12:00.15 with the amount of rainfall that you get in the summertime
00:12:05.19 in New Hampshire near this... near this site.
00:12:07.21 So, that's what this dashed line is,
00:12:10.27 is the amount of cumulative summer precipitation,
00:12:12.20 the amount of rainfall that happens in the summer.
00:12:14.13 And so, what we found was that in years
00:12:16.27 that had high amounts of summer rainfall
00:12:20.02 that we have the highest survival rates.
00:12:24.14 And in this study,
00:12:27.22 we hypothesized that that was probably true...
00:12:30.08 because this pattern actually has been found for
00:12:33.11 passerine birds, little songbirds that also eat insects...
00:12:38.19 is that in the northeastern US when you have a lot of rainfall in the summer
00:12:41.05 you have more insects,
00:12:43.26 and so there's more food, and so the bats probably do better in those years.
00:12:48.29 So, we used the data, here, from...
00:12:53.01 with all this information about how...
00:12:55.12 not just what the actual estimates of survival are,
00:12:57.15 but the variability around those estimates,
00:12:59.22 how much difference there is from year to year in these estimates,
00:13:03.00 to put into our population models.
00:13:07.22 This part here is kind of a... a little sort of diagram, if you will,
00:13:12.26 of thinking about the life of a bat.
00:13:17.20 So, you start off as a... as a juvenile.
00:13:19.23 So, we use the term juvenile to mean
00:13:21.26 a bat that's born in a... in a given year,
00:13:24.10 and that whole first year of life.
00:13:26.01 So, from the time that you're born...
00:13:28.04 and bats are born in like June/July... they're born in the summer...
00:13:31.17 that whole first year until the next June or July.
00:13:34.22 And so your probability of becoming an adult is represented by this S-sub-j.
00:13:41.01 That means the survival of being a juvenile.
00:13:44.06 So, that's the chance that you make it from being...
00:13:47.17 from the time you were born to when you come back to the breeding colony
00:13:50.19 as an adult the next year.
00:13:52.25 And then there's the probability, if you're an adult,
00:13:55.25 that you'll survive the next year and...
00:14:00.27 or, you know, survive each year as an adult to become...
00:14:05.04 you stay an adult,
00:14:07.01 but it's your chance that you survive from year to year.
00:14:10.20 Then, if you're an adult,
00:14:12.28 there's the chance that you will return to the breeding colony and breed.
00:14:18.10 And so that's that B-of-a times F.
00:14:22.04 So, that's your... the B-of-a is the chance that you return to the breeding colony,
00:14:25.22 and then F is, if you return,
00:14:28.10 how likely you are to actually have a pup.
00:14:31.19 And so... and since you can breed after your first year of life,
00:14:34.13 the juveniles also get that probability as well,
00:14:39.26 but it can be different for them from the adults.
00:14:42.23 So, this is just sort of a cartoon about
00:14:47.06 the way we can sort of break down the different stages in life
00:14:52.04 for a bat.
00:14:53.21 And then we can try to do some math to sort of
00:14:56.19 estimate what these different probabilities are,
00:14:59.24 and put those together in a matrix,
00:15:02.00 and do some matrix algebra
00:15:05.05 to determine what the population growth rate will be for these populations.
00:15:11.11 So, that's what we did.
00:15:14.09 And from the 17-year mark-recapture dataset,
00:15:17.19 we found that overall...
00:15:20.16 with those with those survival rates and breeding probabilities
00:15:24.05 that we had estimated from banding the bats in the barn...
00:15:26.26 that those populations were doin' okay.
00:15:29.18 They were... what we call lambda,
00:15:32.07 which is just the mathematical term for population growth...
00:15:37.06 it was positive, meaning those populations were actually
00:15:40.20 producing more individuals over time than they were losing.
00:15:45.20 Okay.
00:15:47.06 So, in lambda... if lambda is 1, then...
00:15:50.20 if lambda is 1, then population...
00:15:53.07 it basically means it's stably the same number of individuals
00:15:55.21 in the next year as you had the first year.
00:15:59.01 So, any number greater than 1 means the population is increasing over time.
00:16:01.18 And any number less than 1
00:16:03.12 means the population is decreasing over time.
00:16:05.19 And then we wanted... like I mentioned,
00:16:09.13 we wanted to relate how that detailed demographic data
00:16:13.04 related to the regional picture of the populations.
00:16:15.09 And so we did that using these annual winter counts,
00:16:18.24 and we estimated with the annual counts
00:16:22.20 what that lambda with that population growth rate was.
00:16:26.15 And for 86% of those populations,
00:16:29.04 the [population] was stable or positive.
00:16:31.21 And so that kind of told us that...
00:16:36.03 and the regional average was 1.07.
00:16:39.01 And so those numbers aren't exactly the same,
00:16:41.18 but what it told us was that those demographic rates
00:16:45.07 that we got from the banding study
00:16:46.27 were roughly representative of what was going on across the region.
00:16:51.00 And that gave us confidence that we could go ahead
00:16:53.22 and use those in our stochastic population model,
00:17:00.12 that I'll talk about it in a second,
00:17:02.18 to try to estimate what the impacts of white-nose syndrome
00:17:06.01 will be on the population.
00:17:10.16 And importantly, the...
00:17:13.16 one of the big take-homes from this was that,
00:17:15.28 prior to white-nose syndrome,
00:17:18.07 these populations in the northeastern US
00:17:21.10 were healthy and growing.
00:17:23.05 These were... and that makes sense.
00:17:25.05 This is a common bat.
00:17:26.24 It's a bat that can live in your barn and your attic.
00:17:29.13 And so it was...
00:17:31.26 these populations were not suffering.
00:17:33.18 So, by the time we had gotten all these numbers and crunched all this down,
00:17:37.27 we sort of already knew that
00:17:40.19 what was killing the bats was the fungus.
00:17:42.16 But this sort of corroborated that
00:17:45.01 the fungus wasn't just opportunistically taking bat's lives
00:17:49.24 because they were stressed from other sources.
00:17:51.23 These populations were actually doing well.
00:17:54.11 And this was... the fungus
00:17:57.10 kind of came in as a novel pathogen,
00:17:59.26 as something from somewhere else.
00:18:01.14 And we now know it came from Europe.
00:18:04.15 At the time, we didn't know that.
00:18:06.05 So, as in all science,
00:18:10.03 you want to sort of stay within the scope of your data.
00:18:12.28 And so this is kind of to remind us that,
00:18:17.05 although at this point... so, this map is outdated.
00:18:18.24 This map was in the paper, but white-nose
00:18:20.29 has been continuing to spread
00:18:23.09 and continuing to sort of march its devastation across the US
00:18:27.20 and further into Canada.
00:18:29.18 But at the time that we were working on this,
00:18:32.01 the data that we had was from where white-nose syndrome originated,
00:18:35.21 which was in... sort of centered in New York,
00:18:39.15 and sort of in the northeastern US.
00:18:41.21 So, the... when we...
00:18:44.19 when I get to talking about the impacts of regional extinction,
00:18:48.01 it's important to remember that is regional,
00:18:50.22 and it's based off of the data that we had,
00:18:52.26 which comes from a particular area.
00:18:55.00 Because little brown bats,
00:18:57.05 as this map down here shows,
00:19:00.17 actually range all the way to the western US and into Alaska.
00:19:05.15 So, here we have graphs that show us
00:19:08.10 actually what we call the raw data,
00:19:10.01 which is actually the...
00:19:11.27 just the count, the number of bats
00:19:14.07 that are counted at a hibernacula in the winter.
00:19:16.26 That's on our... on our y-axis.
00:19:20.15 And again, year is on our x-axis.
00:19:23.17 So, this is just sort of through time.
00:19:25.28 And so our timeline actually spans
00:19:30.08 from the early to mid-1980s
00:19:32.23 all the way up until 2010.
00:19:36.17 It's broken into three different panels here
00:19:38.21 because hibernacula come in all different sizes,
00:19:42.28 and so it's hard to actually see
00:19:45.17 what's happening at the small... at the small hibernacula
00:19:48.19 if you plot them on the same graph as the large hibernacula.
00:19:51.17 So, this large panel... this panel here that says large
00:19:55.12 are hibernacula they range from 30,000 bats down to 5,000 bats.
00:19:59.29 And here we have the medium.
00:20:02.22 So, this is the hibernacula that range from 4,000 bats down to 1,000 bats.
00:20:07.15 And here we have small hibernacula that range from 1,200 bats
00:20:11.13 down to just a couple hundred bats.
00:20:13.22 And these are just the number of bats counted each year.
00:20:18.11 And so a couple of things that you can kind of tell from these graphs
00:20:20.25 is that prior to white-nose syndrome...
00:20:23.25 white-nose syndrome is...
00:20:26.12 when it enters the system is noted in these... in these gray bars.
00:20:30.24 The bats... overall these populations were increasing,
00:20:34.29 which you sort of can just visually see,
00:20:38.21 and I showed you the math that sort of shows
00:20:42.05 that that indeed is the case.
00:20:43.24 Occasionally, you have a big catastrophic decline,
00:20:47.13 like here, where you'll see a big...
00:20:53.12 a year with a big decline in bats.
00:20:55.25 And those were usually...
00:20:57.20 those were always well documented in the field notes of the biologists
00:21:01.01 who would go out.
00:21:02.13 And they'd say things like, there was a big flood,
00:21:03.28 or, you know, part of the cave caved in.
00:21:08.04 And so you occasionally do get catastrophic events,
00:21:12.10 but the overall picture is one of populations
00:21:14.16 that were actually doing quite well.
00:21:16.24 But then, in the gray bars, what you see...
00:21:20.06 and you can use this middle panel as an example...
00:21:23.24 that the populations just crashed down when...
00:21:27.21 once white-nose syndrome hits.
00:21:30.08 So, at the time that we were doing this,
00:21:32.15 there were only three years post white-nose syndrome infection.
00:21:36.10 And we did have just a smidgen of data
00:21:39.02 that indicated that perhaps the impacts of this
00:21:43.01 might lessen over time.
00:21:44.23 And there's quite a bit of work done
00:21:47.16 in disease ecology theory
00:21:50.17 that talks about differences between
00:21:53.07 the way that pathogens or disease are transmitted to individuals,
00:21:58.15 and how that impacts the long-term dynamics of a disease.
00:22:05.26 And we didn't have the information we needed
00:22:08.20 to do sort of a proper disease model to understand that.
00:22:12.14 So, we used the available data that we had.
00:22:14.13 And what we had was that in...
00:22:18.12 the declines in the first year post infection
00:22:21.07 were very high, averaging around 80%.
00:22:25.25 And then in the second year,
00:22:28.16 there was a little bit more variability, and overall a little bit lower.
00:22:32.03 So, averaging around 60% or so.
00:22:34.04 And then in the third year, we only had two data points,
00:22:35.28 but it was even lower, and it averaged around 45%.
00:22:40.05 So, we took that data... this is actually the same data,
00:22:44.01 it's just the axis is flipped now,
00:22:45.28 so that we express it in terms of population growth,
00:22:50.00 that lambda.
00:22:51.21 And so 1, again, would be where populations are stable,
00:22:54.21 the same number of individuals from year to year.
00:22:57.09 And so, what we did was we said,
00:22:59.26 okay, well we don't really know what's gonna happen in the future.
00:23:02.08 We're not fortune tellers here.
00:23:04.13 But we're just gonna take some guesses
00:23:07.01 and build sort of a best case/worst case scenario.
00:23:08.28 So, our best case scenario was that the populations would continue to stabilize.
00:23:15.13 And we could say,
00:23:18.26 okay, we think they'll stabilize around 1,
00:23:21.00 and we just sort of fit a line that said,
00:23:22.23 okay, let's go to 1,
00:23:25.23 and let's see how long it takes us to get there.
00:23:28.05 And it takes about 16 years to get there.
00:23:31.10 And then... so that became our sort of best case scenario.
00:23:33.29 And then our worst case scenario was that they just would
00:23:36.24 stay at that 45% decline rate forever.
00:23:42.27 So, those gave us our sort of best case and worst case scenarios.
00:23:48.16 So, then we do some more math.
00:23:52.07 And this is that same matrix, population matrix,
00:23:57.16 that I showed you on the earlier slide,
00:24:00.11 where we had the cartoon of the different stages
00:24:03.17 that a bat goes through.
00:24:05.01 And this is just expressed in the matrix... a matrix form.
00:24:08.12 So, you start off in one time step
00:24:10.26 with the number of individuals that are a juvenile
00:24:13.23 and the number of individuals that are an adult.
00:24:16.13 And then you multiply that by this matrix,
00:24:19.09 which are those different transition probabilities,
00:24:22.10 that transition of being... a juvenile bat becoming an adult bat,
00:24:25.07 or an adult bat breeding,
00:24:28.26 and the juvenile bat breeding.
00:24:30.22 And that then gets you to...
00:24:34.21 being the number of juveniles and the number of adults in the next time step.
00:24:38.19 So, we do that for susceptible bats,
00:24:41.07 which are bats who haven't gotten disease yet.
00:24:44.05 And then that feeds into
00:24:47.20 the number of infected bats, based off of the rate of spread,
00:24:52.09 which we calculated directly from the number of hibernacula
00:24:56.28 that were becoming infected each new year.
00:24:59.29 And so, the same... so, the...
00:25:03.24 these transition values for the susceptibles
00:25:06.11 came directly from the data from that banding study,
00:25:10.24 the mark-recapture study.
00:25:12.12 But then, when the bats become infected,
00:25:14.24 we have to change their survival probabilities, right?,
00:25:17.07 because their chance of surviving from white-nose syndrome is much lower.
00:25:20.26 And so we based those off of the observed population declines,
00:25:30.03 and we used these different scenarios
00:25:32.16 to sort of say, well, what if decline sustained at 45%,
00:25:36.01 or what if declines started to ameliorate,
00:25:40.09 or the population started to stabilize over time,
00:25:43.06 but then persisted at a certain...
00:25:47.29 with a certain level of impact from the disease.
00:25:50.13 So, the point of this exercise
00:25:52.27 is not necessarily to sort of fortune-tell exactly
00:25:57.22 what was going to happen,
00:25:59.06 but to look at a range of scenarios
00:26:01.08 so we could understand the scope of the impact
00:26:03.17 that the observed mortality that we were having
00:26:06.16 would have on the populations.
00:26:09.22 So... and then this fancy term stochastic,
00:26:13.19 that comes into play in that we let the... those...
00:26:17.26 all those probabilities vary.
00:26:19.27 And so we basically,
00:26:24.03 you know, put the data in, and we...
00:26:26.20 and we run it out in a bunch of different simulations, forward through time,
00:26:30.19 and we let things vary a little bit,
00:26:33.13 and that adds a certain amount of noise.
00:26:35.00 So, stochastic just means random.
00:26:38.03 So that we could...
00:26:41.10 allow sort of for chance events to happen as well.
00:26:45.25 So, we had to have some assumptions in the model.
00:26:48.06 So, we had to pick a starting population size.
00:26:50.00 We don't really know how many bats
00:26:52.19 there are in the northeastern US,
00:26:54.24 so we used the records
00:26:57.27 of how many bats had been accounted for in hibernacula.
00:27:01.12 But we know that there have to be more than that,
00:27:04.21 but we don't know how many more there have to be.
00:27:06.27 We don't know what percentage of the hibernacula
00:27:10.17 that we know about is of the total population.
00:27:14.26 So, we had to just kind of take a guess.
00:27:17.14 So, because of that, we actually fit...
00:27:21.17 we actually stated that what we would call extinction in the model
00:27:26.25 is when the number of bats remaining in the population
00:27:30.04 was only 0.01% of the starting population.
00:27:33.07 And that would mean that there would only be 650 bats left
00:27:38.11 across that whole five-state northeastern US region
00:27:41.09 that I showed you in the map.
00:27:43.17 And so our idea here was that would be basically functional extinction,
00:27:50.17 that there weren't enough bats left on the landscape
00:27:52.26 to be considered a viable population.
00:27:56.09 We also assumed that the population was single and well-mixed,
00:27:59.07 so there wasn't a lot of spatial structure,
00:28:02.19 so that... basically, bats have every chance of being in different places across that range.
00:28:08.18 So then, we did a thousand simulations,
00:28:12.29 out 100 years into the future
00:28:16.11 with these different parameters, to see...
00:28:17.27 to calculate what the probability of extinction would be
00:28:21.00 based off of these numbers.
00:28:24.03 And that's what these graphs show us.
00:28:27.07 So, the first scenario is this...
00:28:31.28 what if declines continue at this 45% rate,
00:28:37.14 meaning that the... for your first year, once you get infected, you get...
00:28:42.14 you decline by around 80%,
00:28:45.26 and the second year you decline by 65%,
00:28:48.24 and then the third year declines by 45%,
00:28:51.00 and every year after you continue to decline at that 45% rate.
00:28:55.23 And that the spread continues at the rate
00:28:58.28 that we've been seeing it.
00:29:01.01 And so what you get is this horrifying prediction
00:29:04.07 that within about 16 years all of the bats go extinct.
00:29:08.26 So, we reach that extinction threshold incredibly rapidly.
00:29:12.22 And if we say, okay, well, we don't...
00:29:18.19 maybe there's some chance that the populations are gonna stabilize.
00:29:21.10 And so if they stabilize at a 20% decline
00:29:26.19 -- that the disease only ends up causing a persistent 20% decline each year --
00:29:32.02 then this still goes to extinction,
00:29:35.00 but it takes a little longer.
00:29:36.18 It's now, you know, between 20 and 30 years.
00:29:40.09 And likewise, if you drop down to only a 10% persistent effective mortality from the disease,
00:29:45.08 you still... eventually the populations go extinct,
00:29:50.08 but it takes us closer to 60 years.
00:29:53.21 And then it only a 5% persistent mortality,
00:29:58.21 you get to about 60% of the bats...
00:30:08.13 there's a six...
00:30:10.09 sorry, there's a 60% chance that the bats will go extinct over 100 years.
00:30:15.26 Now, in these what we call...
00:30:19.09 this kind of exercise is called a population viability analysis,
00:30:22.18 and 100 years is typically the time frame
00:30:26.04 that we use for assessing the risk of extinction.
00:30:29.05 And under normal circumstances,
00:30:32.20 a prediction that there's a 60% chance that a population may go extinct in 100 years
00:30:38.18 would be considered a dire prediction,
00:30:41.09 and that this would be a species that
00:30:43.16 vastly warranted being covered under the Endangered Species Act.
00:30:47.09 It only looks good here because of the sort of horrifying first...
00:30:53.02 implications of the... of the worst case scenarios.
00:30:56.15 And it isn't until you get to
00:30:59.28 only a 2% persistent effective mortality
00:31:02.25 that you see an appreciable drop in the probability of regional extinction.
00:31:11.26 And under all scenarios,
00:31:15.06 we see a significant population crash, rapidly, even at that 2% level.
00:31:20.01 So... and that's... and that's been played out.
00:31:22.25 That is what we have seen.
00:31:24.22 There has been a massive... a massive collapse.
00:31:27.16 And so there's other ecological ramifications for losing...
00:31:33.09 even if you don't lose the species,
00:31:36.21 losing the abundance of that species,
00:31:39.02 and what the kind of impacts that may play out in the ecosystem are.
00:31:44.20 So, the conclusions from this particular work
00:31:49.18 were that white-nose syndrome is threatening imminent regional extinction
00:31:52.17 of the little brown myotis, the little brown bat,
00:31:54.19 that was once formerly quite common in the northeast.
00:31:58.26 And that even if populations stabilize, or the declines ameliorate over time,
00:32:04.07 sustained mortality from white-nose syndrome
00:32:07.15 has to get to less than 5% per year
00:32:09.28 to significantly reduce that probability of extinction
00:32:11.28 over a 65-year time frame.
00:32:17.02 So... but the other take-home is that
00:32:20.26 before this disease was introduced,
00:32:23.10 before the fungus was introduced into North America,
00:32:27.03 these populations were doing really well.
00:32:29.20 They were robust and growing.
00:32:31.15 They had been hard hit in the 70s, likely from DDT.
00:32:34.09 But they were... they were experiencing strong population growth.
00:32:39.28 So, you know, if we can find ways to control the mortality and the spread,
00:32:44.07 these populations do stand a good chance of coming back
00:32:49.00 and recovering from this.
00:32:53.23 Now, this work was published a couple years ago,
00:32:57.11 and we've learned a lot,
00:32:59.13 and we're continuing to learn a lot about white-nose syndrome.
00:33:01.16 So, it's... I encourage you to go and look at current research,
00:33:08.03 or access things online
00:33:10.16 to see what is the current status of what's happening.
00:33:14.28 We have a big research program going right now
00:33:17.23 to look at the spread of white-nose syndrome
00:33:20.22 across the continental United States,
00:33:22.26 and to look at the seasonality of the disease dynamics.
00:33:25.23 We're really sort of diving into trying to understand
00:33:28.29 the ecology of the transmission dynamics
00:33:31.29 in the spread of white-nose syndrome,
00:33:33.20 and what kind of impacts that has on populations.
00:33:37.04 And we're focusing on the other species
00:33:39.17 that white-nose syndrome affects.
00:33:41.20 So, all the work that I've been talking about today
00:33:44.16 focused on the little brown myotis, or the little brown bat,
00:33:47.23 but there are a number of other species
00:33:52.04 -- about six other hibernating bat species --
00:33:54.21 that are affected by white-nose syndrome right now.
00:33:57.29 So, we're looking into transmission dynamics, and spread, and other...
00:34:04.19 and other types of impacts.
00:34:06.22 Well, thank you so much for listening.
00:34:08.26 And in... to close,
00:34:11.12 I'd like to acknowledge my co-authors and collaborators
00:34:14.03 who worked very hard on this project with me,
00:34:16.26 and also to the United States Fish and Wildlife Service,
00:34:19.26 who funded this work.
00:34:21.17 And I'd also like to give a special thanks
00:34:24.28 to the countless individuals and the state biologists
00:34:28.04 who have done an extraordinary amount of work
00:34:31.06 over the past several decades, really,
00:34:33.17 of going into these icy-cold hibernacula
00:34:36.03 and counting bats year in and year out,
00:34:38.16 and that gave us the ability to do this analysis.
00:34:41.25 And without that, and their detailed record-keeping and their detailed notes,
00:34:44.29 none of this would have been possible.
00:34:47.02 And they're really at the forefront of fighting for the bats,
00:34:50.01 and for fighting for saving the bats from this terrible disease.

Part 2: Follow-up Questions and Answers for Students

We were unable to retrieve the video

00:00:22.16 Well, we do know that they can get it
00:00:25.01 from the cave environment.
00:00:27.01 So, this work actually is still not yet published,
00:00:30.10 but was done by Al Hicks at the Department of Environmental Conservation
00:00:34.25 in New York,
00:00:36.26 where he actually took some bats
00:00:40.08 that were not infected and put them into a cave or mine
00:00:43.27 that had had infection the previous year,
00:00:46.12 and made it so that bats couldn't go in or out,
00:00:49.23 and they all got infection and died.
00:00:52.06 So, we know that they can get it from the...
00:00:55.04 from an environmental reservoir,
00:00:58.24 which is actually not good news for the bats,
00:01:02.04 because it means that even if there's just a few left
00:01:04.24 they can still pick it up from the... from the cave.
00:01:07.22 But they also get it from each other, most likely.
00:01:11.13 There's been work done in the lab
00:01:15.17 that shows that if you infect a bat with the fungus
00:01:20.02 that it can infect other bats.
00:01:28.02 Right.
00:01:29.18 So, the fungus... we now know that the fungus
00:01:32.00 is coming from Europe.
00:01:33.21 And the way that we know that is that a...
00:01:39.14 after the discovery of white-nose syndrome and the fact that it was com...
00:01:43.00 that it was caused by Geomyces destructans, the fungus,
00:01:45.21 in North America,
00:01:47.24 researchers in the white-nose syndrome community
00:01:50.20 started reaching out to European researchers
00:01:53.09 and said, hey, have you guys seen anything like this
00:01:56.21 in Europe?
00:01:58.06 And it turns out that there is...
00:02:00.14 were lots of photographs and evidence that their bats...
00:02:05.29 it's really common in Europe for hibernating bats
00:02:08.26 to have white stuff on their faces.
00:02:11.06 So, a couple of folks went
00:02:14.05 and started sampling bats in Europe,
00:02:17.09 and found out that there is Geomyces destructans
00:02:20.19 growing on bats in Europe.
00:02:22.13 And a number of different species
00:02:25.06 in countries really all over Europe.
00:02:27.27 So, using the same sort of molecular diagnostics
00:02:34.11 -- either through what we call quantitative PCR
00:02:37.18 to identify the DNA of the fungus,
00:02:40.08 and/or actually culturing the fungus
00:02:45.01 and looking at it on a microscope and seeing
00:02:48.04 that it has the same characteristics --
00:02:49.22 we found it on a bunch of species in Europe.
00:02:56.21 There are... there's no evidence that bats...
00:03:00.04 because there...
00:03:02.17 there are no species that are the same in North America versus Europe.
00:03:05.21 There's really no chance that a bat
00:03:07.25 is gonna accidentally fly from Europe to North America.
00:03:11.13 And so the fungus most...
00:03:15.15 basically almost had to get here through some means of
00:03:19.02 human trade or travel.
00:03:20.26 Now, there's a number of different competing hypotheses.
00:03:23.14 Sort of the... sort of the most plausible explanation
00:03:29.07 is that somebody visited a cave in Europe
00:03:32.05 and then went to Howes Cavern,
00:03:34.26 which is where white-nose syndrome was first detected,
00:03:37.04 and Howes Cavern is a commercial tourist cave
00:03:40.03 that tourists go and visit every year,
00:03:41.28 and probably had sort of dirt on their boots still
00:03:45.28 that had some of the fungus on their boots.
00:03:48.08 That's the most likely.
00:03:50.03 Other... there's some other ideas
00:03:52.14 that perhaps a bat got stowed away on a shipping bunker.
00:03:55.04 Albany is a port town,
00:03:56.26 and if a shipping bunker had a bat in it
00:03:58.21 and it came into the port,
00:04:00.16 then the bat kind of got out of the shipping bunker
00:04:03.20 and it, you know, found the nearest place to roost,
00:04:06.11 that's also potentially plausible.
00:04:09.10 But in any case,
00:04:11.19 humans were implicated in how it got here,
00:04:15.15 because there's no way that a bat would have flown across the Atlantic.
00:04:24.20 The fungus, Geomyces destructans, is in Europe.
00:04:28.21 But the... but white-nose syndrome as a disease,
00:04:32.00 where it's actually killing bats,
00:04:34.18 does not exist in Europe, as far as we know.
00:04:37.11 So, the bats are actually living with it just fine in Europe.
00:04:39.29 And we still don't know why that is.
00:04:41.24 We don't know if it's just that it's been there
00:04:44.03 for a very long time in Europe.
00:04:45.14 We do have a sense that it's been there for a very long time in Europe,
00:04:48.13 in the sense that genetically it looks very diverse there,
00:04:52.10 and not very diverse at all in North America.
00:04:55.19 That's some unpublished work by a friend of mine, and colleague.
00:05:00.05 But... so we don't...
00:05:03.27 so if it's been there for a very long time,
00:05:06.01 maybe the bats have sort of co-evolved with it.
00:05:08.01 But we don't know if it...
00:05:11.27 some people think maybe it's the fact that colony sizes
00:05:16.00 tend to be smaller in Europe.
00:05:18.01 But we don't... I'm actually working on an analysis
00:05:21.09 to address just precisely that question right now.
00:05:23.14 And so there's hypotheses at this point,
00:05:28.02 but no good answers as to why bats
00:05:30.24 are so severely affected here in North America
00:05:34.21 and are apparently living with the fungus
00:05:37.22 just fine in Europe.
00:05:44.11 There are no species of bats
00:05:47.08 that occur both in Europe and in North America.
00:05:50.24 So, the two faunas are quite separate.
00:05:54.11 There is a pretty high diversity of bats in Europe, actually,
00:05:59.15 and we have the same genera,
00:06:01.04 so there are lots of different myotis species in Europe.
00:06:04.28 And we have several myotis species here.
00:06:08.08 So, you know, we don't know to the extent that it might be a phylo...
00:06:12.08 a phylogenetic difference between the two.
00:06:16.17 But we do see that white-nose syndrome
00:06:18.22 affects the species here in North America differently.
00:06:23.12 So, not all species are as severely impacted as the little... the little brown bat.
00:06:27.29 But species across genera are also affected.
00:06:31.15 So, like, tri-colored bats, which are in a different genus,
00:06:34.08 the Perimyotis,
00:06:36.20 are also very severely affected by white-nose syndrome.
00:06:46.01 No.
00:06:47.10 There's not been any progress yet on eradicating the fungus.
00:06:51.09 There's been a number of different attempts
00:06:54.15 to do different kinds of treatment,
00:06:56.09 ranging from putting on antifungals on the bats...
00:07:02.20 one of the really challenging things is that
00:07:05.29 hibernating bats are incredibly sensitive to being handled
00:07:08.22 and worked with while they're hibernating.
00:07:10.21 So, just the mere act of trying to apply fungicides
00:07:14.12 to the bats while they're hibernating
00:07:16.25 wakes them up, disturbs them, and often kills them.
00:07:19.20 We have a project right now
00:07:22.18 that my grad students are working on
00:07:25.03 of trying to look at what kind of naturally occurring bacteria
00:07:28.15 occur on bat skin,
00:07:32.15 and whether or not we can use that to help boost the...
00:07:39.15 see if those bacteria inhibit the growth of Geomyces destructans
00:07:43.12 on the skin.
00:07:44.23 And can we use that in a way that might help
00:07:47.00 prevent or reduce infection?
00:07:49.28 But that work is very much in progress.
00:07:58.01 I actually started graduate school the first time
00:08:00.20 at the University of Montana at Missoula,
00:08:03.14 and I dropped out.
00:08:06.22 I had... for a long time...
00:08:08.27 I did my undergraduate degree in environmental studies,
00:08:11.10 and for a long time I couldn't decide
00:08:14.01 whether I wanted to be a scientist,
00:08:17.11 or to be a science writer,
00:08:20.15 or interpret science for people.
00:08:24.05 And so I kind of had one sort of foot in each door.
00:08:26.28 And so I actually started grad school with the idea of...
00:08:29.21 still sort of on that fence.
00:08:31.07 And once I started grad school
00:08:33.18 in a program that was really designed to be
00:08:35.27 more sort of interpretive about science,
00:08:38.00 rather than doing science,
00:08:39.11 I realized at that point...
00:08:41.23 that's when I was going to actually really want to be a scientist.
00:08:46.16 So, I dropped out and then...
00:08:48.24 and then reapplied to be in an actual science grad school path.
00:09:00.11 I got interested in studying bats about 13 years ago.
00:09:04.02 I was sort of in between college and graduate school,
00:09:10.03 and started working for somebody
00:09:13.27 who was a bat biologist, as their field assistant.
00:09:18.04 And we fell in love,
00:09:20.23 and I fell in love with bats.
00:09:22.19 And we're now married,
00:09:24.12 and I still study bats.
00:09:31.28 Well, bats are a fascinating group of organisms.
00:09:34.26 I mean, I think I would feel passionately about
00:09:37.05 any organism that I would work on
00:09:39.25 in terms of conservation and protection.
00:09:44.20 And bats in particular, you know,
00:09:47.10 they can be sort of misunderstood
00:09:49.28 and there's, you know, sort of different myths,
00:09:52.25 and these ideas that they're, you know,
00:09:55.15 these sort of creepy animals that get stuck in your hair,
00:09:57.21 which is, you know, totally false.
00:10:00.19 But, you know, they're...
00:10:04.14 a lot of people don't realize that bats make up
00:10:07.15 a quarter of all mammalian diversity.
00:10:09.15 They're incredibly diverse.
00:10:10.27 There's about 45 different species of bats here in the US.
00:10:15.13 And so only the rodents are more diverse than bats
00:10:19.11 in terms of mammalian diversity.
00:10:21.09 They do... they're the only mammals that can fly.
00:10:24.06 They echolocate,
00:10:27.21 and so they, you know, do some very unusual things.
00:10:30.25 And they're just really sort of fascinating to work with and to study.
00:10:36.28 There's so much we still don't know about bats.
00:10:41.11 And in terms of, you know, why should we protect them?
00:10:48.26 Lots of... the sort of...
00:10:50.23 the standard answer to that question is that bats
00:10:53.20 provide ecosystem services.
00:10:55.12 And ecosystem services is this idea that the...
00:11:00.16 that they... that...
00:11:03.21 an ecosystem service is a service
00:11:06.23 that either wildlife or some part of nature provides to humans
00:11:09.23 that has some kind of monetary value.
00:11:12.05 So, in the case of bats, bats eat insects, and insects eat our crops,
00:11:16.27 or bore into our forests that we cut down for wood,
00:11:20.26 or carry diseases,
00:11:23.18 or simply annoy us in the case of mosquitoes.
00:11:26.25 And so there's been a lot of effort to sort of
00:11:32.24 advocate for bats in terms of the role they play
00:11:36.08 for eating insects.
00:11:38.13 I've recently decided that
00:11:40.17 I'm gonna stop using that as a reason
00:11:43.05 to advocate for the protection of bats,
00:11:44.26 because I firmly believe that bats
00:11:47.27 have an intrinsic right to exist and be protected.
00:11:51.09 They have a right to be on the planet,
00:11:54.00 just as much as we do.
00:11:55.14 And that it's our job,
00:11:58.04 as members of the animal community and as stewards of habitats,
00:12:04.15 to protect and respect animals,
00:12:07.11 regardless of whether or not they provide some
00:12:10.16 economic benefit to us as humans.
00:12:17.08 I guess, you know, for me as a...
00:12:19.22 as a conservation biologist,
00:12:22.14 in this particular system the dream discovery
00:12:26.03 would be a way to protect bats from white-nose syndrome.
00:12:29.06 If we could find a way that we could protect the bats
00:12:32.13 and that they could not be suffering from this disease,
00:12:36.20 that would be fantastic.
00:12:39.04 In my heart, you know, what I...
00:12:41.13 I care deeply about science and discovery,
00:12:43.13 but I also care very much about conservation.
00:12:53.27 I still try to get into the field as often as I can.
00:12:56.28 Unfortunately, that's not as often as I used to.
00:13:01.03 I work on a number of different research projects,
00:13:04.28 and for this... for the research on white-nose syndrome
00:13:08.21 that I'm doing now, I'm really only kind of getting to visit grad students in the field.
00:13:13.13 But I'm actually heading to Illinois in a couple weeks
00:13:15.27 to get to go into a mine there
00:13:18.20 and help with some surveys,
00:13:20.05 so that'll be exciting.
00:13:22.05 I do a bunch of research in northwestern Mexico,
00:13:25.20 in Baja California,
00:13:28.11 and I spend usually between two and four weeks
00:13:32.10 each spring down there.
00:13:33.21 And I'm getting to head down there in about a month, so that'll be great.
00:13:36.22 Now that I have a kid,
00:13:39.19 field work is a little more challenging,
00:13:42.00 but I've sort of taken the attitude that he'll just go with us.
00:13:44.26 So, he's been... my son's been in the field in Texas and Baja
00:13:49.09 and in all sorts of places.
00:13:51.07 So, hopefully I'll get to keep that up.
00:13:58.08 So, I have a three-year-old son.
00:14:01.05 And I spend a lot of time playing with him on the beach or wherever.
00:14:06.25 I am...
00:14:10.09 I also have two stepdaughters that are 16 and 13.
00:14:12.04 And so I have a really fantastic family.
00:14:16.13 We like to go bicycling
00:14:20.08 and spending as much time outside as possible, traveling.
00:14:30.03 I love to travel and,
00:14:33.00 like I said, I try to spend a couple weeks in Baja every spring.
00:14:36.10 And we kayak and snorkel
00:14:39.25 and get to play outside as much as possible.
00:14:48.16 I love being a scientist.
00:14:50.22 It is one of the most creative fields.
00:14:54.19 You know, when I was in high school,
00:14:57.26 I had no idea I wanted to be a scientist.
00:14:59.05 Actually, high school biology was the number one class
00:15:02.00 that I skipped out on when I was in high school.
00:15:04.21 And it was not interesting to me at all
00:15:07.19 because it seemed like it was just rote memorization.
00:15:10.09 I think it's a tragedy the way that
00:15:13.05 high school biology is taught.
00:15:15.26 And it wasn't 'til I got into college
00:15:17.26 that I realized that science was a creative...
00:15:21.04 a creative field.
00:15:23.02 And I think it's actually one of the most creative fields there is.
00:15:26.29 I mean, you have to... you have to actually come up with
00:15:30.18 questions that you want to answer,
00:15:32.05 and then you have to figure out how you're gonna answer that question
00:15:35.09 in a way that's gonna give you a definitive answer.
00:15:38.16 Then you design the study to do that.
00:15:40.17 Then you gotta carry out the study
00:15:43.01 and problem-solve constantly when things aren't...
00:15:46.24 didn't go the way that you thought they were gonna go.
00:15:49.04 And then you have to analyze the data,
00:15:52.16 and figure out the best way to analyze the data.
00:15:55.11 And then write all that up so that someone can understand what you did.
00:15:58.21 It's an... it's an incredibly
00:16:02.06 creative and rewarding process to go through all those stages.

Videos in this Talk

Part 1: White Nose Syndrome in Bats
Audience:
- General Public
- Student
- Researcher
- Educators of H. School / Intro Undergrad
- Educators of Adv. Undergrad / Grad
Part 2: Follow-up Questions and Answers for Students
Audience:
- Researcher
- Educators of Adv. Undergrad / Grad

Speaker: Winifred Frick

Total Duration: 0:51:05

Recorded: January 2013

All Talks in Ecology

Talk Overview

Collaboration with Science in the Classroom

This talk is a supplement to the annotated primary literature paper found in the American Association for the Advancement of Science’s (AAAS) Science in the Classroom Project.

A horrific fungal disease called White Nose Syndrome began to cause massive mortality of small brown bats in the Northeastern United States in 2006. Dr. Frick explains that she and her colleagues used historical data from bat censuses and recent mortality data to model possible outcomes for bat populations in this region. Sadly, their data indicate almost certain regional extinction for the bats unless this disease can be stopped. This work was done in Dr. Thomas Kunz’s lab at Boston University. Dr. Frick is currently an Assistant Adjunct Professor of Ecology and Evolutionary Biology at the University of California, Santa Cruz.

Speaker Bio

Winifred Frick

Winifred is an assistant adjunct professor in Ecology and Evolutionary Biology at UC Santa Cruz. My research is broadly focused on exploring how populations respond to anthropogenic and natural stressors. Much of my research focuses on bats, although my interests in ecology and conservation transcend my mono-taxophilic research habit. I believe good science combines natural… Continue Reading