Judith Ullmann

• Mag.art. BSc MSc
• Scientist at Naturschutzbund Österreich

Species: Lissotriton vulgaris (please confirm; photos attached)

Total Length: 10 cm

I found this smooth newt yesterday (18.12.2019, 21:30 local time) in the outskirts of Vienna (Austria) on a stone walkway in a garden.

Environmental data (at time of observation):

Air temp: 2°C

Humidity: not measured, very likely 100%RH: foggy and very wet since sunset (no rain)

No wind

Weather during the day: 9°C and sunny around noon/in the early afternoon, no wind, no rain

In the same garden, newts have been found in previous years in springtime (in a water meter shaft 1.5 to 2 m below ground level). There is a pond in one of the neighboring gardens; the urban housing area is located within 1 km of Donau-Auen National Park.

According to Jablonski (2013) and Kaczmarek et al. (2018), winter activity in the species is unusual in this part of Europe. For this reason, I include here as much information as possible. The environmental conditions were similar to those reported in both papers.

The animal was not moving when I found and subsequently observed it for 10 min. Upon touching it (to remove from walkway), it moved its limbs lethargically. Due to a further drop in temperature (to ca. 0.5°C), I took it in overnight.

What is the best procedure to maximize its chances of survival? Where should I release it today (open/vegetated area in the garden)? Which time of day (weather forecast: 5°C in the morning, 13°C at noon, 10°C in the evening)?

In my case, pressure is the independent variable (plotted on the x-axis), and volume is the dependent variable (plotted on the y-axis).

In analogy to “xy”-plot, I’d say I get a “pressure-volume (P-V)” curve, although y is plotted against x.

However, I find it both ways (i.e. P-V vs. V-P) in the literature, even within the field of pulmonology/lung mechanics (Levitzky 1982, West 2012 vs. Frank et al. 1959, Leith 1976).

To my knowledge, a discussion of body orientation is curiously absent from the literature (cf. Hooker and Fahlman 2016) on lung (alveolar) collapse at depth (two exceptions, see below).

The experimental studies I have come across, simulated dives with animals (or excised respiratory tracts) in a (presumably) horizontal (Ridgway et al. 1969, Kooyman et al. 1970, Denison et al. 1971, Moore et al. 2011 ) or 20°-head-up (Kooyman et al. 1972, Kooyman and Sinnett 1982) position. None mentioned experiments on specimens in a more natural head-down position (whichever angle) when simulating the dive descent and analyzing the sequence of compression events of the different respiratory tract compartments/the shifting of alveolar air into the non-absorptive conducting airways, the compressibility of the trachea, the depth of lung collapse at a specific diving lung volume, etc.

Moore et al. 2011 (Figures 2 and 3) and Garcia Párraga et al. 2018 (Figure 2) showed and discussed differential alveolar collapse during simulated dives of horizontally oriented marine mammals. At depth, the (compressed) volume of lung air is always found in the absolutely uppermost portion of the lungs.

Going one step further, i.e. not seeing the lungs in isolation but in connection with the conducting airways, I would think that, underwater, the body position of the breath-hold diving animal is as important a factor to consider as the diving lung volume (McDonald and Ponganis 2012) and the relative sizes and different degrees of compressibility of the trachea/the bronchial tree/the alveoli when one wants to estimate or model (cf. Bostrom et al. 2008, Fahlman et al. 2009) lung collapse depth in an effort to e.g. assess the risk of decompression sickness in marine mammals.

McDonald and Ponganis (2012) found the lung collapse depth of a free-diving sea lion to be greater than expected on the basis of pressure chamber studies. The authors‘ explanation centered on varying diving lung volumes (larger when diving deeper). I think that the difference in animal body orientation between this free-dive study and above pressure chamber studies also plays a critical role here.

An analogy: Imagine the respiratory tract of a marine mammal as a complex made of connected lifting bags (as used in scuba diving), each made of a different material; and therefore, exhibiting different degrees of compressibility (lungs>trachea>bronchi (Kooyman et al. 1970)). Underwater, depending on the orientation of the oblong model, air will always travel to the absolutely highest portions. This must lead to different sequences of compartmental compression with depth depending on the orientation of the model; i.e. whether it is submerged in a horizontal or vertical (lungs-up), or any angle-in-between, position.

Body orientation must ultimately affect the compressibility of the trachea and lungs (cf. predicted collapse depths; Murphy et al. 2012, Davenport et al. 2013); the more air in one of these compartments, the longer this compartment will resist collapse.

In comparison with the "classic" pressure chamber experiments, during a more natural head-down descent, tracheal compression must set in earlier/be more severe because the shrinking tracheal air will be pressed upward into the lungs to join the shrunken volume of original lung air. (-Provided that the trachea and the lungs communicate freely and there are no counteracting forces from the expiratory muscles). Hence, the onset of lung collapse, the ultimate forcing-out of lung air into the non-absorptive conducting airways, must be deferred. In other words, all things (i.e. diving lung volume, dive depth, size of the respiratory tract compartments) being equal, lung collapse sets in at a greater depth than predicted on the basis of chamber experiments with horizontally oriented animals.

Since large enough hyperbaric chambers exist to orient an experimental animal/carcass head-down, I am curious if anyone has ever tried it? And if not, why not? (I don’t get the logic of orienting an animal slightly head-up when trying to simulate a natural dive descent.)

[References attached.]

The idea is to use a "normal" GLS in combination with a pre-programmed, possibly weight-reduced GPS logger that switches on/off at defined dates (let's say 4 weeks before/after the equinoxes) and also under constant light (or dark) conditions; the latter is basically in function like a saltwater switch, but working with information on light. When active, the GPS would log 2 positions a day (no finer resolution needed than with the GLS working for the rest of the year), therefore saving battery life and reducing size. No trouble in using a GPS logger, since the bird has to be recaptured to get at the GLS anyway.

This would be an alternative to a) having to skip several weeks to months of logged data for analysis because latitude could not be determined reliably with GLS and b) calculations/modelling environmental variables recorded during equinoxes/midnight sun to get an idea of likely geographical locations at the time.

The idea crossed my mind in Sept 2015 and I asked around a bit in Dec 2015 at uni, etc. Neither then nor now, have I found literature on anybody having tried/working on this. There is some literature on "combined-" or "double-tagging", but with the purpose of estimating the GLS' s accuracy, not to get data during the equinoxes.

Has anybody tried this? 

What would be obvious pitfalls? (I know, weight of the GPS logger is an issue for smaller species.)

How small can a GPS logger be, when it's necessary to log only about 500 locations? (4 weeks before/after each equinox = 112 d = 224 loggings PLUS midnight sun on Svalbard max. ~ 126 d = 252 loggings. That gives a total of 476 loggings.)

- Getting it to switch on and off at a defined calendar date cannot be too complicated. How about programming it to switch on when there's 24 hrs constant-light conditions?

Which companies/working groups are specialized on non-standard things like that?

(Literature: Afanasyev 2004; Bogdanova et al. 2011; Evans et al. 2013; Frederiksen et al. 2012; Gaston et al. 2015; Gilg et al. 2013; González-Solís et al. 2011; Guilford et al. 2009; Leat et al. 2013; López-López 2016; Millspaugh et al. (date?; Wildlife radio-tracking and remote monitoring); Phillips et al. 2004; Phillips et al. 2007; Ponchon et al. 2013; Reiertsen et al. 2014; Rutz & Hays 2009; Seavy et al. 2012; Wilson et al. 2002).