We are searching data for your request:
Upon completion, a link will appear to access the found materials.
As far as I know, humans are the only animals that use visual references to track prey that is not immediately visible to them.
Do any other animals do this?
I'm not referring to stalking prey that the predator already has in sight, like many big cats do, and not tracking prey, that is out of sight, by scent or other means, before switching to visual before the final attack.
Are there any other animals that primarily use visual information, such as tracks, shed fur, broken foliage, disturbed earth, etc., to follow or approach a prey animal that they can't already see?
Here we include publishers that were not originally on the Beall’s list, but may be predatory.
- , Prime Publications (also here ) (child of Academic Publications Ltd. and Dynamic Publishers, both on the Beall’s list) (ARSSS) (website is not working, so I have listed all their journals in the Standalone Journals section) (previously Penerbit Akademia Baru) (Antjournals) (related to Nobel International Journals) (BookPI) (linked to ScienceDomain International, another predatory publisher) (British BioMedicine Publishers, BBM Publishers) (BSCint) (CSP) (CAR) (linked to RIPK) (CCR) (linked to RIPK) (CPER) (CRIBFB) (new website here) (also Cloud Publications) (inactive) (EAS Publisher) (see also International Scholarly Open Access Research) (ENGII) (eSciRes) (EUROPA) (FM Journals, Frontiers Meetings) (G J Publications) (GPH) (the group’s journals are already on the Beall’s list, but the group didn’t have a website before) (Global Publication House International Journals) (connected to EPH Journal) (Hilaris SRL) (connected to OMICS) (related to ABC Journals) Incessant Nature Science Publishers (INSPublishers) (ISI) (Innovationinfo) (inactive) (IPRPD) (IARAS) (IAENG) (IASTED) (IBAC) (USA) (ICPK) (IIERD) (IISES) (IJMRND) (IPRJB) (ISJ) (links to Bosal) (ITS) (IMM) (IPN Publishing, related or a rebrand of International Postgraduate Network) (Innovative Research Developers and Publishers) (InformTechCell)
- Leon Publications (publisher of the Chemistry Research Journal, the Pharmaceutical & Chemical Journal, and the Journal of Scientific and Engineering Research) (see also Open BioMedical Publishing Corporation) (MMC) (also here) (connection to Statperson Publishing Corporation)
- Modern Business Press (see also OMICS) (relation to SERSC) (NSSEL Publishing) (publishes IJNTR) (Onomy Journals) (PRADEC) (RCES) (RNP) (SOAOJ) (Scientific and Academica Editores Publication house, SAEP) (new website of The Scientific Pages) (SAS Society) (SciAccess Publishers) (UTM Publication) (SPG) (spg.ltd) (Scimaze Publishers) (SciVision Publishing Group) (a website created by three predatory publishers) (TAPH) (VSR, see also Universe Scientific Publishing)
Last updated March 7, 2021
Fossil Record Examples
The human fossil record is perhaps one of the best documented, due in part to the historical contention that has surrounded the debate of evolution. Nearly every “missing link” in the chain has been unearthed, revealing a solid chain of fossils from modern humans to our earliest ape-like ancestors. The fossils can be differentiated by their distinct features, and can be dated using radioactive isotopes for very accurate dating. The oldest fossils of members of the Homo genus were found to be around 1.5 million years old. These belonged to Homo ergaster. It is believed that Homo ergaster spread from Africa and diverged into the species seen below.
Homo erectus and Homo neanderthalensis both have a distinct fossil record, and it is likely that they competed with modern Homo sapiens. Genetic analysis have confirmed that modern human genomes contain traces of genes from the Neanderthals, suggesting that the two species interbred at some point in the past. The fossil record of humans can be traced back even further, all the way to very ape-like ancestors which still climbed trees.
Surprisingly enough, the fossil records of many animals have been assembled in near completion as well. The fossil record of whales, for instance, has a set of several well-defined members that lead inevitably to modern whales. Fossils have been found of coyote-sized semi-aquatic predators which were thought to live amphibious life-styles near the shore. Later fossils reveal a much more aquatic predatory animal, still resembling a dog, but with a much larger tail and a head adapted to hunting in the water. Around 35 million years ago, an animal existed which was almost fully aquatic and had lost its hind limbs. 5 million years later, the fossils of what appear to be modern whales start to appear.
The Oldest Fossils
When talking about the fossil record of life on Earth, the record goes back much further. The oldest known rocks that have been analyzed are around 3.8 billion years old. Tracing the minerals and hydrocarbons present in certain rocks has led to the conclusion that some form of single-celled life was present around 2.7 billion years ago. Fossil impression of single celled organisms, thought to be some early ancestor of plant and animal cells, can be found around 1.6 billion years ago in the fossil record.
1. A new fossil is found, which appears to be some sort of human ancestor. How will scientists know how to place it into a human phylogeny?
A. DNA analysis
B. Radiometric Dating
C. Comparative Anatomy
D. All of the Above
2. How do we know how old the oldest fossils are?
A. Radiometric Dating
C. Historical References
3. Why is the fossil record for vertebrates so much better than the fossil record for jellyfish?
A. Jellyfish have been around longer
B. Vertebrates preserve better
C. There have been more vertebrates
PARTS OF A TRACK
When a track is made, the heel slides into the ground, registers and pulls out. No track will register straight down. There is always some angled component (looking at the track cross-section) either from the foot entering or the foot leaving.
The softer the soil, the greater the slope of the wall creating a larger distortion between the overall track and the true track. Most people don't read the true track. They read the horizon cuts (overall track) which does not give the true track measurement. The true track is the only real measurement for tracking. If you read the overall track you could not tell the difference between a dog track and a coyote track. E.g. on a dog the inner toes are larger than the outer toes on a coyote the outer toes are larger. But this distinction will not show on the overall track.
MEASURING A TRACK
You need to measure the length and width of all four tracks (2 in humans). When measuring animal tracks the length readings between tracks are measured from toe to toe because animals hit first with their toes. In humans it is measured from heel to heel because we land heel first.
- Establish the Line of Travel- This can be done by eye if the tracks are clear or by placing popsicle sticks at the heel of the tracks and connecting a string to the sticks.
- Length of Track - measure the length of the true track.
- Width - measure the widest part of the track.
- Stride - is measured from the heel of one foot to the heel of the other foot (i.e. right heel line to left heel line).
- Straddle - if you draw a line of travel between the left heels and a line of travel between the right heels the distance between these two lines is the straddle. There is zero straddle and positive straddle.
- Pitch - is the degree to which the foot angles out from the line of travel (pitched out). At the widest point of the track, draw a line bisecting the track along its long axis. The distance from where the line exits the front of the foot to the heel line is the overall pitch.
Overall Pitch - 1/2 track width = True Pitch
Ex. 4" wide track, 3" overall pitch 3 - (1/2 * 4) = 1" = true pitch
This is because if there is no pitch there would still be 2" from the line through the track to the heel line. So this measurement must be subtracted.
CLASSIFICATION OF TRACKS
5% 1) Clear Print - when you can see the track clearly in soft soil, all toes visible.
95% 2) Pattern Classification - no clear print, you must tell track by general shape and size of track
CLEAR PRINT CLASSIFICATION
The front and rear tracks on one side will be near each other. You need to note the number of toes in the front track and the rear track. Looking at the track you will also note the type of preferred gait used by the animal (in order to differentiate between front and rear tracks).
- Track Shape - the track shape is the overall shape of the track pattern.
- Direct Register - as the front foot is lifted up the rear foot on that side drops directly into the front track (cats and foxes). Also called perfect walking.
- Indirect Register - as the front foot is picked up the rear foot on that side drops slightly behind and to the right or left of the front track (depending on the sex of the animal).
- Ground Bird - spend most of their time on the ground and show a "walking" gait
- Perching Bird - spends most time in the trees - shows a "hopping" gait
- Mixed - if the track shows both walking and hopping it is probably a bird that splits its time between trees and the ground e.g. Crow
There are a number of different types of locomotion patterns. 90 - 95% of the time an animal will use this method of locomotion. In each case below the gait described is the normal walking pattern for that animal. As the animals speed changes this pattern will change (ex. moving slowly, in pursuit, being chased).
RF = right front LR = left rear, etc.
1) Continuum of Speed:
2) Diagonal Walkers - the animal moves the opposite sides of the body at the same time (e.g. RF & LR move simultaneously)
Deer Dog Cat - cat and fox direct register by being completely off the ground at one point
3) Bound Walkers - the front feet land together, then the rear feet behind 99.9% of the time these animals use this pattern even when moving slow or fast. Stride measured from rear toes to rear toes.
Weasel Family - All Members Except Skunks & Badgers
4) Gallop Walkers - the front feet land first, then the rear feet come on the outside of the front feet and land ahead. 99.9% of the time these animals use this pattern even when moving slow or fast. Stride measured from rear toes to rear toes. The pattern doesn't change with speed. The distance between sets of tracks increases.
Rabbits Hares Rodents - Except Porcupine & Ground Hog
If the front feet hit at a diagonal = ground dwelling rodent e.g. Rabbit, and the front foot that is further back is the one that hit first - sidedness (punch step). If the front feet hit side by side, it is a tree dweller e.g. Squirrel (just like tree dwelling birds - "hoppers")
5) Pacers - move the same side of the body at the same time (e.g. RF & RR) - these animals have wide, rotund bodies. These are the exceptions from the other groups. 95% of the time these animals use this pattern. As speed increases, they change their pattern.
Badgers Skunk Porcupine Oppossum Raccoon Bear
6) Variations on Pattern Classifications - 5% of the time. All animals can change their gait. In particular, Diagonal Walkers and Pacers will change their pattern as their speed increases.
In between these major patterns there is a continuum of discernable pattern variations.
- From Pacer to Diagonal = 16 patterns
- From Diagonal to Bounder = 32 patterns
- From to Galloper = 16 patterns
- For speed, a slow walk for a Pacer is faster than a slow walk for a Diagonal Walker.
- A stalk is generally the slowest pattern and is slower for both a Pacer and a Diagonal Walker.
- Slow Walk - animal pushes body weight forward.
SUMMARY OF CLASSIFICATIONS & VARIATIONS
Tracking by patterns allows you to track over hard ground over a long distance.
1. Diagonal Walkers
- Slow Walk
- Pace when bored, annoyed, aggravated
- Rarely hold a bound except in soft or rocky terrain - prefer to gallop on clear terrain hold a bound on for a few patterns before going into a gallop - prefer to trot or lope - can go straight from a walk to a gallop (e.g. if suddenly frightened)
Species Note: Deer prefer to gallop for high speed except for the Black Tail Deer and the Mule Deer that prefer to bound because they live in rocky areas.
2. Bound Walkers
- For a shear burst of speed will gallop - seen just before a kill
- Will diagonal walk when approaching hunting territory e.g. slowing down to be more quiet
- Will stalk when hunting game
- Will pace when aggravated, bored or agitated, threatening, seen just before going out on hunt
Note: This is an example of how you can tell the "emotional state" of an animal by looking at its tracks.
3. Gallop Walkers
- Prefer to gallop but will bound in soft terrain i.e. snow, mud or rocky terrain
- Will diagonal walk if it needs to cover a shorter distance than a hop would cover, e.g. rabbit moves 2" over to feed
- Will stalk when moving away from danger
- Will pace when aggravated, threatening or bored
1) Sidedness - if one front foot is behind the other over 4 - 5 tracks that foot is on the dominant side. The animal will have a tendency to circle in that direction.
2) Sex - (this works for diagonal walkers only). Deer for example, just because a track is deep or splayed wide does not mean that animal is male. There are variations in the size of animals of the same species from location (different amounts of feed). Male deer (bucks) and female deer (does) have different bone structure. Doe - pelvic girdle > shoulder girdle (for birthing). Buck - shoulder girdle > pelvic girdle (to support antlers). In order to tell the sex of the animal you must compare the animal to itself. Find the front track on one side. The look for the rear track on that side. If the rear track is to the inside of the front track = male, a rear track to the outside = female. This system works only for adult animals. Immature animals have not finished bone development and may have rear track falling exactly behind front track.
Cats are another example because they direct register. Then how do you tell whether the rear foot is inside or outside the front? In cats (and foxes) the front foot is larger (by 1/3) that the rear foot. Thus the rear track will fall in the front track and be to the inside or the outside. Inside = male Outside = female.
1) The single most important factor in track degradation (and thereby aging) is weather and weather fluctuations.
2) Gravity is the second major factor in track degradation.
3) The third factor is the type of soil. The only way to learn to age tracks is to observe a track degrade over time with given soil conditions and weather conditions. Soils are classified from 1 to 10 with 1 being sand and 10 being clay (soft to hard). You must estimate the soil classification first. Then keep an accurate record of weather changes and by observing a track you will develop a sense of how a track degrades in that type of soil with those weather conditions. Weather conditions to be aware of are temperature, humidity, wind, precipitation, and hours of direct sunlight on the tracks.
4) Wisdom of the Marks - Do this once a month for three months and you will cover all seasons for the type of soil in your area (if possible do it with various types of soil). Clean out rectangular area of soil. Remove all rocks, transplant plants etc. Dig down 2 inches, break up soil into smooth texture, pat it down smooth and leave it to settle for 24 hours. Using a stick or object approximately 1/2 inch diameter make 5 marks in a row in the soil with varying pressure from a touch to enough to go 1/2 inch deep. Look at the marks carefully for 10 minutes to ingrain into your subconscious what they look like. Write down weather conditions. Come back 6 hours later and repeat the entire process making the new marks with the same implement and the same pressures in a row next to the first marks. You will now have fresh marks and 6 hour old marks to compare. Study both for 10 minutes. Come back in 6 hours and again 6 hours after that and again in 6 hours. This will give you a comparison of track degradation at 6 hours, 12 hours, 18 hours and 24 hours. Then go back every 24 hours for 6 days and you will see the track age and degrade over a week. After doing this summer, fall, winter, and spring you will begin to learn how to age tracks to within 2 hours of their being made. It is also advisable to do this whenever you move into a new area for tracking.
1) File card learning Method - Read about an animal in the Peterson's field guide an prepare a scan card on a 3 x 5 index card. By scanning these cards during "blow off time," you will quickly learn to recognize tracks.
2) Tracking Stick - This can be either primitive ( a stick with notches cut into it) or advanced a dowel with rubber bands ("O" ring washers work great). The stick should be about 3' x 1/4" and very straight. The tip should be sharpened to give a point. The stick is used to measure a track and give you a standard for comparing and looking for the next track.
- Tip to 1st mark = length
- 1st to 2nd = width
- Tip to 3rd = stride
- 3rd to 4th = straddle
- 4th to 5th = true pitch
Since animals walk 95% of the time the tracking stick is a useful way to find the next track. If you lay the 3rd mark over the center of the last track the stick will point to the center of the area where the next track will be. To find the track add the straddle. If you don't find the track, ask yourself what does the landscape tell you? Uphill, downhill will shorten the stride debris - does the animal understep or overstep it? Soft earth will have an effect on stride length.
3) Track Pack - Carrying these items with you will help in learning to track.
- Magnifying glass - large 2-4 x, jewelers loop 10x
- Tape measurer - thin, metal 8'- to measure stride, straddle etc.
- 6" plastic ruler - to measure track
- Small notebook
- Ziplock bags - for scat, bones etc.
- Peterson's Field Guides
- File Cards
- Popsicle sticks and string
- Price tags - for labeling.
All the information you need to find the next track is within the one you have. Never skip a track (cross-tracking) it doesn't teach you anything. If you hit "the wall" and can't find the next track, work at it, analyze it. This is how you learn to be a good tracker. If you spend 2 hours to find the next track, your skill will grow to a higher level.
TRACKING ENVIRONMENTAL HAZARDS
In any tracking situation you need to be aware of what the local environmental hazards are in order to avoid accidents. This is a general list for a typical mid-Atlantic forest region.
Sacramento Bee Exposé on Wildlife Services Leads to Call for Congressional Investigation
We worked for several years with Tom Knudson, a Pulitzer Prize-winning journalist from the Sacramento Bee, on an exposé on USDA Wildlife Services' out-of-control "predator control" program. The Bee came through with an impressive, in-depth piece of investigative journalism indicting this brutal government program, along with a number of insightful editorials and features linked below:
Sacramento Bee Exposé
- - Wildlife Services is a federal agency that operates in secrecy, using brutal traps, poison and aerial gunning to kill thousands of animals, with accidental victims that include federally protected species, family pets and injured people. Sacramento Bee, Apr. 28, 2012 - Wildlife Services' predator control is coming under fire from scientists, former employees and others, who say it is expensive, ineffective and can set off a chain reaction of unintended, often negative, environmental consequences. Sacramento Bee,Apr. 30, 2012
- >Suggestions in changing Wildlife Services range from new practices to outright bans(part 3 of 3) - Critics of Wildlife Services suggest solutions that include nonlethal control curtailing aerial gunning a ban on leg-hold traps, neck snares and cyanide poison more transparency cutting its budget and perhaps eliminating the agency altogether. Sacramento Bee, May 6, 2012
Sacramento Bee Editorials
Sacramento Bee Follow-up Articles
- - details just one of the indiscriminate and deadly killing techniques used by Wildlife Services. Sacramento Bee, published April 30, 2012 - Shows renewed attention is being drawn to the federal government's wildlife damage control program as a result of: (1) a bipartisan letter from four U.S. Representatives requesting a congressional investigation, and (2) a "notice of violation" and $2,400 fine issued to a Wildlife Services' employee for placing a spring-loaded sodium cyanide ejector (M-44) near a family's home in Texas that killed their dog, Bella. Sacramento Bee, June 25, 2012. (See special note* below regarding Predator Defense's focused work on these two projects.) - Sacramento Bee, June 30, 2012 - Sacramento Bee, July 19, 2012 - Sacramento Bee, Nov. 2, 2012 - Sacramento Bee, Nov. 18, 2012 - Sacramento Bee, Nov. 18, 2012 - Sacramento Bee, Jan. 31, 2013
- Federal agency gives few answers on months-long probe of alleged animal cruelty - FOXnews.com, June 12, 2013
- Documents show questions about Wildlife Services probe in animal cruelty - Sacramento Bee, June 15, 2013
Sacramento Bee Videos
- - includes three videos of our work at Predator Defense, helping human and animal victims of Wildlife Services. Sacramento Bee, Apr. 30, 2012
*NOTE: The request for a Congressional investigation and oversight hearings on Wildlife Services mentioned above is an effort we have worked on intensively for many years. In their letter to the Chairman of the Committee on Oversight and Goverment Reform, the two U.S. Representatives we've been working with—Peter DeFazio (D-Oregon) and John Campbell (R-Irvine)—cite the program's waste of federal dollars, harm to ecosystems, and secrecy regarding practices and spending. Read letter to Committee Chairman, Darrell Isssa. We also worked for over a year with the family in Texas who lost their dog to the M-44 placed by the Wildlife Services employee being fined. Read Bella's story
Understanding movement patterns and the factors that affect animal distribution are integral components of behavioural ecology, conservation and protected area management. Conventional animal biotelemetry systems, such as radio and satellite transmitters, have revolutionised the ability to track wildlife movement over vast spatial and temporal scales (Maehr et al., 2002, Luschi et al., 2003, Sale et al., 2006, Sims et al., 2006). Despite this, variable accuracies and infrequent intervals between fixes (Hays et al., 2001, Hulbert and French, 2001) limit their application at finer spatial resolutions, and when quantifying movement patterns in relation to biophysical parameters at small scales (Wilson et al., 2004, Bradshaw et al., 2007). However, the acquisition of high resolution tracking information may be important in formulating rational, adaptive and dynamic management decisions for nature reserves, endangered species and related conservation policies (Argardy, 1994, Castilla, 2000, Thompson et al., 2000, Parra et al., 2006).
Loggers based on the Global Positioning System (GPS) are an important new technology allowing wildlife to be studied with unparalleled accuracy, often to within ranges of 10 m (Moen et al., 1997, Hulbert and French, 2001). However the level of accuracy has been found to vary among animals depending on terrain, habitat and behaviour (Moen et al., 1997, Friar et al., 2004). While GPS loggers, some linked to transmitters to relay the positional data, are routinely used for terrestrial and aerial animals (Douglas-Hamilton et al., 2005, Biro et al., 2006), tracking marine vertebrates with GPS loggers has proved more problematic. This is because infrequent surfacing behaviour limits the time when loggers are available for acquiring satellite signals. For marine species therefore, the current challenge is, in as short a time possible, to acquire sufficient information in order to calculate GPS positions when an animal surfaces. There are several initiatives underway to achieve this goal and some limited success has been achieved, depending on species and surfacing interval (Sisak, 1998, Jay and Garner, 2002, Ryan et al., 2004, Yasuda and Arai, 2005, Petersen et al., 2006, Sheppard et al., 2006).
While satellite and VHF telemetry studies have been effectively used to investigate sea turtle oceanic migratory routes (Luschi et al., 2003, Hays et al., 2004b, Sale et al., 2006) to coastal foraging or breeding grounds, details about behaviour and habitat use at these regions of seasonal residency remain limited (Heithaus et al., 2002a, Heithaus et al., 2002b, Houghton et al., 2002, Seminoff et al., 2002, Hopkins-Murphy et al., 2003, Yasuda and Arai, 2005). Existing studies of female sea turtles at breeding areas using remote technology have been primarily conducted following the onset of nesting (Hays et al., 1991, Hays et al., 2002, Houghton et al., 2002, Hays et al., 2003a, Hopkins-Murphy et al., 2003). These studies indicate that inter-nesting females tend to inhabit sea depths of 15 m or less, and may be found as much as 10 km from the nesting beaches, often exhibiting movements parallel to the coast.
Laganas Bay, on the island of Zakynthos in Greece, is the largest loggerhead sea turtle (Caretta caretta) rookery in the Mediterranean (Margaritoulis, 2005). It is visited by several hundred sea turtles and several hundred thousand tourists each summer (Arianoutsou, 1988). Sea turtles often begin residency in Laganas Bay as early as April, before nesting starts in late May, and are frequently observed in close proximity to shore (Schofield et al., 2006). Nesting beach locations and relative nesting densities were used to delineate the degree of protection offered by marine protection zones in Laganas Bay (Arapis and Margaritoulis, 1994). The no-boating zone encompassing three nesting beaches (out of a total of six), which account for about 70% of nesting activity (Margaritoulis, 2005). Since establishment of the National Marine Park of Zakynthos (NMPZ) in 1999, stricter regulation of near-shore tourism and turtle-watching activities in the two boating zones has been introduced, however empirical data about in-water sea turtle movement is necessary to validate and improve existing management actions.
Many coastal regions are subject to anthropogenic pressure, in the form of fisheries, coastal development and tourism (Arianoutsou, 1988, Hays et al., 2003b, Parra et al., 2006). It is therefore important to obtain information about where, when and why endangered species, such as sea turtles, use these areas, in order to implement rational and effective protective legislation and management of human activities (Argardy, 1994, Thompson et al., 2000). The aim of this study was to investigate sea turtle movement and habitat use at the internationally important rookery of Zakynthos. We used recently developed, low-powered, TrackTag™ GPS loggers to follow individual sea turtle movements and evaluate the effectiveness of existing marine protection zones.
Predator Prey Relationship and Population Dynamics
In some predator prey relationship examples, the predator really only has one prey item. In these scenarios, it is easy to see how the predator prey relationship affects the population dynamics of each species. A simple example is the predator prey relationship between the lynx and the snowshoe hare. The hare forms a large staple in the lynx diet. Without the hare, the lynx would starve. However, as the lynx eats the hare, or many hares, it can reproduce. Thus, the lynx population expands. With more lynx hunting, the hare population rapidly declines. Look at the graph below.
The blue shows the population of lynx, while the red shows the population of hares. At the start of the graph, the lynx population was very high, which the hare population was relatively low. As the lynx started to migrate away, or die off, the hare population rebounded. Since 1845, this 10 year pattern has continued to repeat itself, with a lynx die off coming right after the hare die off. The predator prey relationship between the hare and the lynx helps drive this pattern. However, if you average out the peaks of the population, both populations would hold stable or show only a slight increase or decrease over time.
Remember also that the hare also has a predator prey relationship with the organisms it feeds on, which happen to be plants. As the hares explode, they eat more than the vegetation can support, and they are driven into starvation. That, plus their predator prey relationship with the lynx, makes for very volatile shifts in population.
Grothues TM. A review of acoustic telemetry technology and a perspective on its diversification relative to coastal tracking arrays. In: Tagging and Tracking of Marine Animals with Electronic Devices. New York, NY: Springer 2009. p. 77–90.
Hammerschlag N, Gallagher AJ, Lazarre DM. A review of shark satellite tagging studies. J Exp Mar Biol Ecol. 2011398:1–8.
Boyd IL, Kato A, Ropert-Coudert Y. Bio-logging science: sensing beyond the boundaries. Mem Natl Inst Polar Res. 200458:1–14.
Rutz C, Hays GC. New frontiers in biologging science. Biol Lett. 20095:289–92.
Heithaus MR, Marshall GJ, Buhleier BM, Dill LM. Employing Crittercam to study habitat use and behavior of large sharks. Mar Ecol Prog Ser. 2001209:307–10.
Danylchuk AJ, Suski CD, Mandelman JW, Murchie KJ, Haak CR, Brooks AML, et al. Hooking injury, physiological status and short-term mortality of juvenile lemon sharks (Negaprion bevirostris) following catch-and-release recreational angling. Conserv Physiol. 20142:cot036.
Gallagher AJ, Serafy JE, Cooke SJ, Hammerschlag N. Physiological stress response, reflex impairment, and survival of five sympatric shark species following experimental capture and release. Mar Ecol Prog Ser. 2014496:207–18.
Thomson JA, Heithaus MR. Animal-borne video reveals seasonal activity patterns of green sea turtles and the importance of accounting for capture stress in short-term biologging. J Exp Mar Biol Ecol. 2014450:15–20.
Sundström LF, Gruber SH. Effects of capture and transmitter attachments on the swimming speed of large juvenile lemon sharks in the wild. J Fish Biol. 200261:834–8.
Gleiss A, Norman B, Liebsch N, Francis C, Wilson R. A new prospect for tagging large free-swimming sharks with motion-sensitive data-loggers. Fish Res. 200997:11–6.
Lingham-Soliar T. Dorsal fin in the white shark, Carcharodon carcharias: a dynamic stabilizer for fast swimming. J Morphol. 2005263:1–11.
Anderson SD, Chapple TK, Jorgensen SJ, Klimley AP, Block BA. Long-term individual identification and site fidelity of white sharks, Carcharodon carcharias, off California using dorsal fins. Mar Biol. 2011158:1233–7.
Chapple TK, Jorgensen SJ, Anderson SD, Kanive PE, Klimley AP, Botsford LW, et al. A first estimate of white shark, Carcharodon carcharias, abundance off Central California. Biol Lett. 20117:581–3.
Towner AV, Wcisel MA, Reisinger RR, Edwards D, Jewell OJ. Gauging the threat: the first population estimate for white sharks in South Africa using photo identification and automated software. PLoS One. 20138:e66035.
Hammerschlag N, Cooke SJ, Gallagher AJ, Godley BJ. Considering the fate of electronic tags: interactions with stakeholders and user responsibility when encountering tagged aquatic animals. Methods Ecol Evol. 20145:1147–53.
Jewell OJ, Wcisel MA, Gennari E, Towner AV, Bester MN, Johnson RL, et al. Effects of smart position only (SPOT) tag deployment on white sharks Carcharodon carcharias in South Africa. PLoS One. 20116, e27242.
Towner A, Smale MJ, Jewell O. Boat-strike wound healing in Carcharodon carcharias. In: Global Perspectives on the Biology and Life History of the White Shark. Boca Raton, FL: CRC Press 2012. p. 77–84.
Liebsch NS. Hankering back to ancestral pasts: constraints on two pinnipeds, Phoca vitulina & Leptonychotes weddellii foraging from a central place. Kiel: Univ., Diss 2006. p. 2006.
Prey speed influences the speed and structure of the raptorial strike of a ‘sit-and-wait’ predator
Predators must often employ flexible strategies to capture prey. Particular attention has been given to the strategies of visual predators that actively pursue their prey, but sit-and-wait predators have been largely overlooked, their strategies often characterized as stereotyped. Praying mantids are primarily sit-and-wait predators that often employ crypsis to catch their prey using a raptorial strike produced by their highly modified forelimbs. Here, we show that the raptorial strike of the Madagascan marbled mantis (Polyspilota aeruginosa) varies in duration from 60 to 290 ms due to the tibial extension alone slower strikes involve slower tibial extensions that may also be interrupted by a pause. The success of a strike is independent of its duration or the presence of these pauses. However, prey speed affects the duration of tibial extension and the probability of a pause occurring, both increasing at slower prey speeds. Adjusting the duration of the tibial extension according to prey speed allows mantids to time the final downward sweep of the tibia to their prey's approach. The use of visual inputs to adjust the motor pattern controlling forelimb movements shows that not all aspects of the strike are stereotyped and that sit-and-wait predators can produce behavioural flexibility.
Many predators hunt and capture moving prey that are, in some cases, actively attempting to avoid or escape from them . Catching such prey requires that predators show considerable behavioural flexibility, which is often associated with higher cognitive abilities and relatively large-brained vertebrates . Yet insects with relatively small brains can use simple behavioural rules to produce effective attack strategies that may seem superficially complex [3–6]. The majority of studies of insect predators have focussed on the flexibility of those that chase prey [6–10] rather than those that ‘sit-and-wait’ for prey. If such sit-and-wait predators, which may have just a single opportunity to capture prey, can adjust their hunting behaviour, then they may improve their success.
Although capable of chasing prey when hungry [11–13], praying mantids are primarily sit-and-wait predators employing crypsis to catch a variety of animals, including some vertebrates [14–17]. Mantids are visual predators, whose visual system shows numerous adaptations for prey capture including regions of high spatial acuity and binocular distance estimation [18–21]. Similarly, the mantid's forelimbs are highly adapted for prey capture, featuring movable and immovable spines on the femur and tibia, which facilitate prey capture both mechanically and behaviourally [22–24]. The raptorial strike of praying mantids can be divided into two behavioural phases, the approach and the sweep, and it has been studied in terms of both kinematics and mechanics [25–28]. The strike is often characterized as stereotypical but both phases of the strike are variable in duration, the approach being more variable than the sweep . Although the source of variability has not been identified in the approach, variability in the duration of the sweep has been linked to the distance between predator and prey. This suggests that praying mantids may be a valuable model in which to study behavioural flexibility in relatively small-brained, sit-and-wait predators. Here, we study the behavioural flexibility of the predatory strike of praying mantids in response to the speed at which their prey are moving. We show that praying mantids adjust the speed and structure of their strike duration in relation to prey speed.
2. Material and methods
Madagascan marbled praying mantids (Polyspilota aeruginosa)  were purchased from a local supplier (BugzUK, Norwich, Norfolk, UK) and maintained in individual cages at the University of Sussex, UK. They were fed with live crickets and maintained in a 12 h : 12 h light : dark cycle at room temperature (21–23°C).
(b) Animal preparation, stimulus presentation and videography
To record strikes, mantids were placed on a black 10 × 10 cm cardboard platform, fixed on a 26 × 26 cm raiseable metal plate, in the middle of a 75 × 60 × 60 cm white arena illuminated from overhead (electronic supplementary material, figure S1). A target attached to a transparent fluorocarbon wire with a diameter of 0.16 mm (Airflo Fishing, Sightfree G3) was moved at constant speeds of either 200, 330 or 730 mm s −1 (referred to hereafter as slow, medium or fast prey speeds) near one end of the platform using a motor (MFA Como Drills, RE—385). These speeds were representative of air speeds of flying insects such as fruit flies  and blowflies . Targets were either 6 mm diameter dark plastic beads, blowflies or cricket nymphs ensuring the mantids were hungry while still being rewarded occasionally for hunting.
The animals were filmed through a circular aperture in the arena wall with a high-speed video camera (GC-PX100 JVC Ltd, Yokohama, Japan) at 200 frames per second. The analysis was performed offline using ImageJ (National Institutes of Health, Bethesda, MD, USA). The attacks were divided in phases based on femoral and tibial movements (see Results). The number of frames in each phase was then used to calculate the duration. Joint angles were measured on the limb closer to the camera, either directly with the inbuilt angle tool, or limb segments were tracked using the MTrackJ plugin  (electronic supplementary material, figure S2).
(c) Statistical analysis
Statistical tests were implemented using R studio software, v. 1.0.136, and R software, v. 3.3.2 (R Core Team, 2013). The median (med) and interquartile range (IQR) were calculated using the ‘pastecs’ and ‘stats’ package. Assumptions of normality were tested using the Shapiro–Wilk test in the ‘pastecs’ package. Assumptions of equality of variance were tested using the Levene's test in the ‘car’ package. Correlations were tested using Pearson's r-test, implemented in the ‘Hmisc’ package. Logistic regressions were implemented using generalized linear models in the ‘stats’ package. Linear mixed-effects models were implemented using the ‘lmerTest’ package. These models incorporated both random effects (individual, trial number) and fixed effects (phase category, phase duration, target speed, prey type). Effects that did not significantly improve our models (trial number, prey type) were not included in the final models (electronic supplementary material, table S1), except for ‘individual’, which was kept as a random effect due to experimental design. Interactions between fixed effects did not significantly improve any of our models. Models were compared using an analysis of variance (ANOVA), in the ‘stats’ package. Variability was compared using an asymptotic test for equality of coefficient variation , in the ‘cvequality’ package. For comparisons of non-normally distributed data with heterogeneous variance among the groups, we used a Friedman rank-sum test  in the ‘stats’ package. Post hoc comparisons were made using two-tailed, paired-sample Wilcoxon signed-rank tests in the ‘stats’ package, with Hommel's adjusted p-values. Where appropriate, p-values were adjusted to account for multiple testing in post hoc tests.
(a) Forelimb movements during a raptorial strike
Upon detecting a potential prey item, mantids prepared for a strike by raising their prothoracic tarsi from the ground and reducing the angles of thoraco-coxal, coxo-femoral and femoro-tibial (F-T) joints. After these preparatory movements, the animals performed raptorial strikes with paired forelimb movements (figure 1 electronic supplementary material, figure S3). The approach phase of the strike was characterized by tibial extension. Coxal protraction and femoral depression marked the end of the approach and the onset of the sweep phase. During the sweep, the femur was depressed thrusting the distal forelimb forward towards the prey but the F-T joint angle initially showed no notable change. The tibia was subsequently flexed, terminating upon full flexion against the femur or against the target if one was caught. If the strike was successful, the forelimb was retracted and the prey brought towards the mouthparts.
Figure 1. The predatory strike of P. aeruginosa. (a) The sequence of prothoracic limb movements during a strike. The main phases of the strike (approach, thrust, capture, retraction) are indicated. (b) The change in angles between the different prothoracic joints during a typical strike.
(b) Variability in the duration of the approach but not the sweep phase during strikes
We measured the duration of each strike recorded, and the duration of its component phases . The duration of raptorial strikes showed considerable variability (med = 100, IQR = 40 ms n = 96, N = 8) due to variability in the duration of the approach phase, which was significantly more variable than that of the sweep phase (med = 67.5, IQR = 40 ms and med = 35, IQR = 6.3 ms, respectively asymptotic test for equality of coefficient of variation, D′AD = 72.7, p < 0.001). This difference was particularly pronounced when comparing the movements of the tibia during strikes of varying durations, the tibial extension being slower and more variable than tibial flexion (figure 2a). Strike duration was correlated significantly with the approach but not sweep duration (Pearson correlation, r = 0.99, p < 0.001 r = −0.12, p = 0.225, respectively figure 2b).
Figure 2. Strike duration is adjusted to prey speed. (a) The F-T joint angles of five strikes superimposed upon one another. The pauses in two strikes are highlighted in dark red. (b) Above: schematic of the movements of the mantid forelimb. Below: strike duration is correlated with the duration of tibial extension and pauses. (c) Strike duration and the duration of tibial extensions and pauses decreases with increasing prey speed. Phase durations are plotted on a log scale. Significance values: * = p < 0.05, ** = p < 0.01, n.s. = p > 0.05.
Tibial extension during the approach phase lasted 65 ms (med, IQR = 35), however, in 30% of strikes, a distinct pause lasting 20 ms (med, IQR = 25) occurred during which the tibia was stationary, interrupting the extension. Pauses were more frequent in the early stages of a strike. By contrast, during the sweep, the thrust of the distal forelimb towards the prey and the subsequent tibial flexion to capture the prey were brief and showed little variability (med = 10, IQR = 5 ms and med = 20, IQR = 5 ms, respectively). Strike duration was determined by the duration of both tibial extension and the pauses (fixed effect tests, t92.9 = 37.4, p < 0.001 t91.1 = 28.6, p < 0.001, respectively) but not by thrusts and captures (fixed effect tests, t92.9 = 1.23, p = 0.222 t90.5 = 1.43, p = 0.157, respectively). Tibial extensions and pauses were positively correlated with one another, slower extensions being accompanied by longer pauses (Pearson correlation, r = 0.5, p < 0.001). Therefore, strike duration is primarily determined by the components (extensions and pauses) of the approach phase.
(c) Adjustment of approach duration to prey speed
One possible cause of the differences in strike duration is the speed at which the prey is approaching the mantid. We analysed the durations of strikes elicited by prey moving at three different speeds (see Material and methods). Strike duration differed significantly with prey speed (Friedman's ANOVA χ 2 2 = 20.12 , p < 0.001, figure 2c) strikes to fast prey were faster than those to prey moving at medium speed (post hoc test, p = 0.022), and strikes to prey moving at medium speed were faster than those to slow prey (p = 0.002).
The duration of the components of the approach phase differed significantly (fixed effect tests, t182 = 18.5, p < 0.001) but were also affected by the approach speed of the prey (fixed effect tests, t182 = 5.46, p < 0.001). When attacking slow prey, tibial extension paused in 56% of the strikes, compared to 25% of the strikes in response to medium prey speed, and 9.4% in response to fast prey. This suggests that the structure of the behavioural sequence producing a strike is dependent upon the approach speed of the prey. Indeed, prey speed predicted the presence of a pause during tibial extension, slower speeds predicting a significantly greater probability of pausing (logistic regression, χ 1 2 = 15.7 , p < 0.001). Our model shows that the probability of pause occurrence, P(pause), depends on prey speed, v: P(pause) = 1/(1 + e −0.93+0.005v ).
Prey speed also affected the probability of a successful strike (logistic regression, χ 1 2 = 20.0 , p < 0.001), the probability of success, P(success), depending upon prey speed, v, in the following way: P(success) = 1/(1 + e −1.82+0.012v ). The presence or absence of a pause did not affect the probability of a strike being successful (ANOVA, χ 1 2 = 0.0185 , p = 0.892).
Predators often show considerable flexibility during prey capture [37–39] but the raptorial strikes of ‘sit-and-wait’ predators are often characterized as ballistic and stereotyped [40–42]. We investigated whether sit-and-wait predators show behavioural flexibility and whether such flexibility is related to their prey's behaviour using praying mantids as a model. We focussed on the movements of the forelimb tibia during the strike, which executes the final sweep that will trap the prey between the tibia and femur. Our analysis shows that the mantid's raptorial strike is flexible both in speed and in structure, and that this flexibility depends in part upon the speed of the approaching prey.
Flexibility within the tibial movements of the strike is found in the slower approach phase, which is highly flexible in duration, whereas the faster sweep phase shows little variability and high stereotypy. In many cases, flexibility is also evident in the behavioural structure of the strike a pause is incorporated into the motor pattern, interrupting the extension of the forelimb's tibia after it has begun. Furthermore, the duration of these pauses can be varied by individuals. This contradicts early reports of stereotypy in the strike, which reported that the strike was too fast to be modified and even suggested it might be ballistic [43–45]. However, a previous study also found that behavioural phases of the mantid's strike differ in their variability, the approach being more variable than the sweep .
At least part of this variability is related to the speed at which the prey approaches the waiting mantid when prey approach slowly, the approach phase of the strike is slower and incorporates pauses, whereas when prey approach quickly the approach is fast and pauses are absent. Such flexibility allows the mantid to adjust its motor programme to prey velocity, even after the strike has been initiated. This may be important when hunting small flying animals with erratic flight paths that can be difficult to predict. Indeed, for sit-and-wait predators like mantids that may have just one opportunity to capture prey it is important to match the timing of the strike to their prey's behaviour.
Strikes can be aborted after they have been initiated (electronic supplementary material, figure S4), providing further evidence of flexibility . Why such strikes are abandoned is unclear but given the relationship between the strike and the prey's approach speed, aborting a strike may relate to the mantids' ability to capture prey. Indeed, all the abandoned strikes we observed occurred when the prey was approaching at high speed, suggesting that they may be aborted when prey is travelling too fast to be caught.
The need for flexibility may explain why no power amplification has been found in the forelimb of praying mantids . Indeed, the extension and flexion of the forelimb tibia are under direct muscular control (Rossoni S, Niven JE 2016, unpublished observation). Consequently, mantids’ flexibility in the approach phase of their strike is likely due to the direct muscular control. This would allow mantids to detect approaching prey and prepare the forelimb for the strike early, adjusting the approach phase to time the final rapid sweep phase of the strike. It is possible that mantids determine the duration of the tibial extension (approach phase) prior to initiating the strike, based on the approach velocity of their target. However, pauses during tibial extension and abandonment of the strike once initiated suggest such feed-forward control of flexibility is unlikely. Instead, it seems more likely that mantids adjust their raptorial strike through visual inputs allowing them to determine prey speed, among other possible variables. By contrast, mantis shrimps use power-amplified appendages to strike prey . The movements of the mantis shrimp's raptorial appendage joints during the strike are flexible due to feed-forward motor commands [48,49], contrary to praying mantids.
Both desert locusts and horse-head grasshoppers use visual inputs to target the movements of their forelimbs [50–53]. In locusts, once these visually targeted forelimb movements are initiated, they cannot be terminated and redirected until after the target has been missed . Our evidence shows that mantids can adjust the timing of their strike motor pattern to match prey speed even after the strike has initiated. This suggests that, in terms of behavioural flexibility, the mantid strike exceeds that of the visually targeted forelimb movements of locusts. In horse-head grasshoppers, reaches are highly flexible and the forelimb movements adapted to the specific locations of targets within their frontal visual field . However, it is unclear whether the mantid strike is so flexible in terms of spatial accuracy.
This work complied with relevant regulations and laws of the UK, where the work was conducted.
Decisions to control wildlife should be informed by the range of community values alongside scientific, technical, and practical information. Decisions on whether and how to control wildlife usually involve balancing benefits and harms. Scientific and technical information can inform decision making, for example, by clarifying the potential benefits, the consequences of acting or failing to act, and the types of (and likely variation in) harm to target and nontarget animals. Nonetheless, decisions regarding wildlife control inevitably involve human values, which differ from person to person and across communities. For example, different people assign different weights to protection of property or livelihoods, to native species, and risks to human safety. People also differ in how they prioritize harms to affected animals such as suffering and loss of life.
This diversity of interests calls for an open process of community engagement informed by the relevant science, a transparent approach often overlooked by some government and academic research (Brook et al. 2015 ). An ethical review process with proper governance and resources, similar to that used by animal ethics committees when assessing the acceptability of scientific research involving animals and people, could be a way to include scientific and technical expertise while ensuring community values inform decisions (Warburton & Norton 2009 ).
The case of Little Penguins on Middle Island in Australia illustrates the value of including social acceptability in decision making (Warrambool City Council 2016 ). The island, managed by a local council, is a tourist destination for people wishing to visit the penguin colony. When foxes predated the penguins, controversial lethal control methods (shooting, fumigation) were applied, but penguin depredation continued because new foxes crossed to the island during low tide (King et al. 2015 ). Then, through a collaborative community effort, Maremma guard dogs were deployed and the island was temporarily closed to visitors. Subsequently, the penguin population increased, the dogs themselves became a source of interest and community pride, and tourism on the island during the nonbreeding season was boosted (King et al. 2015 ). The success of this program resulted from a combination of scientific and practical information and strong support from the community, local council, businesses, and volunteers.
Camouflage is an adaptation that is used both by predators and by prey. Nature provides many ways for animals to make themselves hard to see. Both predators and prey use camouflage. Prey use it to hide themselves from predators, and predators use it to keep their prey from knowing they're coming after them! See how camouflage works at The Exploratorium.
- One type of camouflage is when an animal's coloring is similar to its surroundings. Now you know why desert animals are often brown and jungle animals are often green.
Some animals change color with the season. This helps them to blend in with their surroundings when their surroundings change.
Imitation, or mimicry, is another form of camouflage. This is when an animal looks like a member of another species or like an object in its environment, such as when a grasshopper mimics a dry leaf.