Zabin C.J.,Smithsonian Environmental Research Center |
Zabin C.J.,University of California at Davis |
Obernolte R.,University of California at Davis |
Mackie J.A.,San Jose State University |
And 3 more authors.
Marine Ecology Progress Series | Year: 2010
A non-native bryozoan, Schizoporella errata, forms extensive patches of free-living balls and reef-like structures (bryoliths) on the mudflats in south San Francisco Bay, California. The ball-like bryoliths range from 2 to 20 cm in diameter, and the reef-like structures can be nearly 1 m across. While S. errata is known to form bryoliths in other locations, free-living aggregations like these have not been reported. Colony morphology appears to be a plastic trait as analysis of relationships among forms using cytochrome oxidase subunit I (COI) nucleotide sequence data revealed no genetic separation. We recorded >50 species of algae and invertebrates living on and in the bryoliths and determined the invasion status for 34 of the 50 species. Of the 34, 25 (74%) were non-natives and included fouling species that require hard substrate. The bryoliths may thus facilitate colonization by invaders on the mudflats and serve as stepping stones between the limited hard substrate habitats in the Bay. © Inter-Research 2010, www.int-res.com.
A plethora of images from live-bearing brittle stars allows a 3D look inside these unique starfish relatives and an insider's view of their soon-to-be offspring. Published in GigaScience is an article that describes high-resolution 3D images, data, and videos of five individuals from three different species of live-bearing brittle stars. The entire associated 100GB of data is freely available in the GigaScience database, GigaDB. These data, generated using non-invasive micro X-ray computed tomography (microCT), were used to study the development of young brooded inside the brittle star, but the value of these data -- besides being cool to look at -- is in their suitability for broad sharing for other researchers to use to examine juveniles within the adult as well as to carry out comparative morphological or anatomical analyses. Large-data sharing is an essential part of making research both reproducible and reusable in the broadest sense. Enabling better understanding of the complex interplay between internal structures can also help throw new insight into how species interact with their environments. Brittle stars are a class of organisms that are closely related to starfish. While most members of this group reproduce externally, there are some species that develop their young internally, and then 'give birth' to live young. While sonograms are the means by which humans can get a look at their developing offspring, live-bearing brittle stars have not been so lucky, as researchers primary means to investigate the brooding chambers and juveniles of brittle stars has been via dissection. This technique destroys the sample, thus eliminating the possibility of further study and sharing of samples for others to use. Here, by using microCT scanning, the authors were able to visualize in 3D the brooding chambers (bursae) and juveniles inside the brittle star, providing an in situ view of the developing young and the position of the bursae inside the adult. Further, because the process doesn't damage the brittle star, additional analyses can be carried out on the same individual. First author Jannes Landschoff from the Applied Marine Science Institute at the University of Cape Town states: "Our goal was to visualise the very large brooded juveniles inside the adults without disturbing the surrounding tissues. At first, we purely wanted to show the feasibility, but we soon realised how amazing the three-dimensional visualisations looked and that our rotation movies attracted much interest". Recognizing the extremely high quality of the images they used to study brittle star development, and that the data included much more information than they actually used, they made all these data available to others in a fully open-access format through GigaScience's repository, GigaDB. The data includes videos and projection, reconstruction images and an additional volume file for easy viewing.
These data, generated using non-invasive micro X-ray computed tomography (microCT), were used to study the development of young brooded inside the brittle star , but the value of these data—besides being cool to look at—is in their suitability for broad sharing for other researchers to use to examine juveniles within the adult as well as to carry out comparative morphological or anatomical analyses. Large-data sharing is an essential part of making research both reproducible and reusable in the broadest sense. Enabling better understanding of the complex interplay between internal structures can also help throw new insight into how species interact with their environments. Brittle stars are a class of organisms that are closely related to starfish. While most members of this group reproduce externally, there are some species that develop their young internally, and then 'give birth' to live young. While sonograms are the means by which humans can get a look at their developing offspring, live-bearing brittle stars have not been so lucky, as researchers primary means to investigate the brooding chambers and juveniles of brittle stars has been via dissection. This technique destroys the sample, thus eliminating the possibility of further study and sharing of samples for others to use. Here, by using microCT scanning, the authors were able to visualize in 3D the brooding chambers (bursae) and juveniles inside the brittle star, providing an in situ view of the developing young and the position of the bursae inside the adult. Further, because the process doesn't damage the brittle star, additional analyses can be carried out on the same individual. First author Jannes Landschoff from the Applied Marine Science Institute at the University of Cape Town states: "Our goal was to visualise the very large brooded juveniles inside the adults without disturbing the surrounding tissues. At first, we purely wanted to show the feasibility, but we soon realised how amazing the three-dimensional visualisations looked and that our rotation movies attracted much interest". Recognizing the extremely high quality of the images they used to study brittle star development, and that the data included much more information than they actually used, they made all these data available to others in a fully open-access format through GigaScience's repository, GigaDB. The data includes videos and projection, reconstruction images and an additional volume file for easy viewing. More information: 1. Jannes Landschoff et al. A dataset describing brooding in three species of South African brittle stars, comprising seven high-resolution, micro X-ray computed tomography scans, GigaScience (2015). DOI: 10.1186/s13742-015-0093-2 3. J Landschoff et al. Three-dimensional visualisation of brooding behaviour in two distantly related brittle stars from South African waters, African Journal of Marine Science (2015). DOI: 10.2989/1814232X.2015.1095801
Biology attracts all sorts, from number crunchers to big-picture dreamers. These days in science, there's no escape from maths in any scientific discipline, even in one like marine biology, historically lighter on sums than, say, molecular biology or quantitative genetics. But nobody should let maths jitters deter them if their call is to study ocean life. Although marine biology is built on a foundation of numbers — from the concentration of pores on a shark's snout to the survival rates of seal pups or worm distribution in sea-floor sediments — not every successful marine biologist is a whiz with numbers. Milton Love at the Marine Science Institute at the University of California (UC), Santa Barbara, readily acknowledges that maths is his biggest weakness. “I failed eighth-grade algebra,” he says. “And I failed calculus as an undergraduate at UC San Diego. There was a point where I thought I'd have to take calculus 800 times to finally pass.” He ended up squeaking through a lower-level calculus course, and went on to build a fulfilling career in research without ever feeling comfortable with the numerical side of his work. “I always managed to finesse the whole thing,” he says. Like many other scientists who struggle with a particular aspect of their research, he simply refused to let a deficiency derail his ambition — an ambition that he had harboured from childhood. “Nobody ever told me that I couldn't be a scientist because I was bad at math,” he says. “I just bullied ahead. I was driven.” In Love's — and other researchers' — opinion, almost anyone who is truly committed to science can find a niche, even if maths feels like a foreign language. Marine scientists for whom maths is not a strong point need a mix of determination and collaboration to go with their calculations — and the willingness to read a few books, download a video or two and maybe take an online maths and statistics course. Tammy Horton, a marine biologist at the National Oceanography Centre in Southampton, UK, often shares a not-so-secret confession with her students. “I'm very honest,” she says. “I say I'm rubbish at maths. A lot of them breathe a sigh of relief.” As it happens, Horton's speciality, the taxonomy of small deep-sea crustaceans, does not require much quantitative skill. To sort out one species from another, she often measures limb lengths or counts hairs, but that is a long way from differential calculus. It is also a long way from the types of multivariate analyses that ecologists, for example, face routinely. “I'm very lucky that I don't have to use much maths,” she says. “A lot of marine biologists use a huge amount of maths, and it's getting more mathematical all the time.” Horton stresses that she did not get into taxonomy because she was trying to avoid hard-core statistics. Instead, she ended up diving into the tiniest details of already tiny creatures because that was what she really wanted to do — study the diversity and adaptations of deep-sea denizens at a very fundamental level. Career paths, she says, should be based on strengths, not on weaknesses. “You shouldn't choose a career because you have anxiety about statistics,” she says. In her experience, determination can overcome most deficiencies. “The best thing to do is to recognize that maths doesn't come easily for you,” she says. Armed with that self-awareness, she says, it's possible to learn skills, erase deficits and find a place in science. Kathy Conlan, who researches marine life in the Arctic and Antarctic at the Canadian Museum of Nature in Ottawa, also feels disadvantaged when it comes to maths. “It doesn't come easy for me,” she says. She is not above asking other people for help with statistics or programming, but she often just ploughs ahead on her own. That is partly because she works at a small institution with fewer options for collaboration, but also because she thinks it is better to “face the hurdles head on”. Before using the statistical package PERMANOVA for analysis of multiple variables in a recent paper, she took a university course on the programme. Even then, she says, analysing the data was somewhat of a struggle. “I was reading and rereading the manual,” she says. “I had to go back and look at university statistics books.” Conlan's maths issues go back to her master's degree, when she had to use punch cards to program the university's computer (it was the 1970s). She says that young researchers today probably face greater expectations when it comes to mathematical ability. But they do have more resources, including online maths and statistics courses to make up the gaps (see 'Resources for mathophobes'). “There are so many more ways now to help yourself,” she says. Statistics programs such as PERMANOVA, and the increasingly popular R, have levelled the playing field, says Steve Haddock, a marine biologist at the Monterey Bay Aquarium Research Institute in Moss Landing, California, and co-author on a book on computing for biologists. “You don't have to type in all of the equations, and you don't have to do the math yourself,” he says. But he warns that canned programs also open the door for big mistakes if users are not thinking carefully about their data — detritus in, detritus out. Scientists who do not feel comfortable with numbers need at least to develop an intuitive sense of the problem that they are trying to address, he says, so that they know which part of the program to use. And, he adds, they need to have at least a general feeling for the data so that they can sort out the plausible results from the outlandish. “If you can't do all of the calculations, you should at least be able to make a ballpark estimate,” he says. Haddock, who used to program his own simple adventure games when he was a kid, says that his proficiency with computers has been a big asset in his career. But he knows that many early-career researchers are not so well prepared. In his view, anxiety about maths and computing should not keep anyone from pursuing science. “It's easy to think, 'Other people are better at this than I am',” he says, “but these things can be overcome.” Besides, he says, fears about maths are often misguided. “It makes me sad to think about people who tell themselves that they're not good at math,” he says. He believes that many junior scientists who feel that they have a maths deficiency could become fluent with the right encouragement and practical instruction. From his own experience and conversations with other scientists, Haddock believes that many biologists get counterproductive instruction that erodes their confidence with numbers. “I would blame math anxiety more on their educational history and less on their innate abilities,” he says. He recalls, for example, a poorly run biology statistics class in his graduate programme. Instead of introducing the students to the stats that they might need to describe their data, the instructor started by mathematically deriving the rationale for the t-test — the classic statistical method for determining whether two sets of data differ significantly from one another — which they were unlikely to understand and even less likely to use in the future. Similarly, he believes that many programming classes for scientists dwell on esoteric computing topics instead of on skills that researchers need, such as writing and debugging code to sort through large data sets. Love says that many of the required or core maths courses for both undergraduate and graduate students seem designed more to weed out degree candidates or to complete a rite of passage than to prepare students for scientific careers. “The first couple of years as a biology major has nothing to do with a career in biology,” he says. “If you can survive the first couple of years, you can find out what biology is all about. It's not about calculus and physics.” When students come to him with concerns about maths or other parts of their education, he encourages them to look at the big picture. “If they say they like algae, I tell them to hang in there long enough to take an actual algae class,” he says. Many researchers have found that a little outside assistance can go a long way when facing mathematical obstacles. Horton says that she sought advice from members of the statistics department when she was getting her PhD, and she still depends on collaboration today. There is a particular statistics-minded person in her department who is always glad to answer a question or give her much-needed feedback. “People are going to be willing to help you, and they'll do it for free,” she says. Like Horton, Love counts on outside support for his maths. Most of his recent grants have included earmarks — typically about US$10,000 at a time — specifically for statistical help. As he explains, his main areas of research, such as measuring fish productivity around oil platforms, require a level of analysis that is beyond his reach. He uses that grant money to rent the brainpower of people such as his colleague Mary Nishimoto at the UC Santa Barbara Marine Science Institute or Jeremy Claisse, a biologist at Occidental College in Los Angeles, California. “If I could actually do the statistics myself, which I can't, it would be more efficient,” Love says. “But because I'm not doing it, I can do other stuff.” Still, as the importance of maths continues to grow — especially in big-data areas such as ecology, genomics and molecular biology — a little self-sufficiency can go a long way, says Elena Sarropoulou, a marine biologist at the Hellenic Centre for Marine Research in Crete, Greece. “I tell all undergrads and grad students to take a statistics class and to learn the programming language Python,” she says. “Just the basics, in order not to be addicted to your bioinformatician in your lab.” She maintains that marine biologists do not have to aspire to mathematical greatness. But they do need to know enough to be able to design an experiment with the appropriate sample size and other parameters to address the problem that they are trying to solve. In her own speciality of molecular biology, she says that researchers too often fail to consider statistical analysis when designing an experiment. She adds that relying solely on a maths expert to interpret results can be risky, because maths-minded people do not always see “the biology behind the data”. A biologist with sufficient maths skills will be in the best position to see experiments through from beginning to end, she says. Until the perfect scientist is invented, every researcher will have some gap in their skill set. The key, Love says, is to find ways to compensate, collaborate and, ultimately, to persevere. Not every researcher can, or even should, hire someone else to do their statistical analyses, he says, but they can find a way to match their aptitudes to their careers and vice versa. “Unless you're just not cut out for the academic life, keep going,” he says. “Almost anyone can become a researcher. It's not magic.”
However, new research reveals—at least for a Pacific marine reef species—that fluctuating food supplies and competition can alter survival of adult fish and be a major cause of fish populations fluctuating in abundance through time. Daniel Okamoto earned his doctorate at UC Santa Barbara in part by analyzing records collected over more than a quarter century by Russell Schmitt and Sally Holbrook, professors in UCSB's Department of Ecology, Evolution, and Marine Biology and the campus's Marine Science Institute. The analyses showed that, for black surfperch (Embiotoca jacksoni), survival of adults from year to year was strongly linked to both the amount of prey available and the number of fish sharing that food. The findings appear in the journal Ecology Letters. "We found that the survival rate varies through time and is driven by local-scale processes of food variability and competition for that food supply," said lead author Okamoto, now a postdoctoral scholar at Simon Fraser University in British Columbia. "That can have major implications for how we think about the impact of fishing. "Our results demonstrate that mortality from fishing or other human activities can greatly amplify fluctuations in the number of fish in a population over time," Okamoto added. "This runs counter to all management and conservations goals for harvested species." The time series used in the synthesis came from the Santa Barbara Coastal Long Term Ecological Research (LTER) project at UCSB. Schmitt and Holbrook began surveying the food supply of surfperch on Santa Cruz Island in the early 1980s. Year after year, they returned to the same locations and meticulously surveyed the prey, their habitat and the different age classes of fish. "The nature of the time series data that we collected was shaped by the conceptual ideas we ultimately wanted to test, which in general sets LTER time series data apart from those typically collected by monitoring programs," Schmitt explained. "In our case, we wanted to know how much the dynamics of food supply influenced the population dynamics of a fish. While everyone knows that food matters, we were surprised just how important it was compared to other well-known causes of variation in the number of adult fish on a reef." Longevity also makes the LTER data ideal for answering questions about fluctuations in species abundance over time. In addition, its data are designed to help understand the interactions among species. Okamoto used the data to perform sophisticated statistical modeling of the fish populations and examined interactions among the survival rate, the number of fish present and abundance in their food. "We've been able to pinpoint the factors that cause populations to vary without a lot of other confounding effects like fisheries," Okamoto said. "We were able to find that there were strong interactions between the amount of food and the survival rate as well as the number of fish. More fish leads to less survival because they're competing for limited prey resources." Although the study targeted a single species, the research generalized the results for other fish populations. "The degree to which survival rates vary through time is huge compared to what people generally tend to expect from fish populations in the ocean," Okamoto said. "Competition between adult fish tends to be a stabilizing force in populations because if there are too many fish, survival decreases and their numbers decline. And if there are too few, those fish do better and the population can grow." In fact, the researchers found that harvesting fish reduces the stability of that population by weakening the stabilizing force of competition, making the population much more susceptible to environmental variability. "It's known that species of fish that are harvested tend to fluctuate much more through time compared to species that are not fished, and scientists have speculated about what can cause fishing to amplify population fluctuations," said Holbrook. "Our analyses provide a general mechanism by which added mortality from fishing or other sources can destabilize a fish population." Long-term studies like this, Okamoto noted, which examine the processes that give rise to variability, can affect how we think about sustainable fisheries or conservation measures going forward. "We recommend greater investment in strategic monitoring of animal populations together with their food and natural enemies," Schmitt said. "We also suggest adopting more precautionary approaches in fisheries until more is known about the complex relationships that shape their dynamics." Explore further: Scientists capture clues to sustainability of fish populations More information: Daniel K. Okamoto et al. Stochastic density effects on adult fish survival and implications for population fluctuations, Ecology Letters (2015). DOI: 10.1111/ele.12547