The picture is just one instant in an event involving hundreds or thousands of organisms that were all doing a lot of different things, sometimes for just a few seconds. How would you describe it?
Maybe using the number of members present in this community? Or a list of names of attendees? The 16S rRNA gene for prokaryotes, or the 18S rRNA or ITS genes for eukaryotes, for examples, would tell us that. Those genes are found in all types of those organisms, and is a pretty effective means of basic identification. But, it’s only as good as how often that gene is found in the organisms you are looking for. There is no one gene that’s found exactly the same in all organisms, so you might need to target multiple different identification genes to look at all the different types of microorganisms, such as bacteria, fungi, protozoa, or archaea. Viruses don’t share a common gene across types, to look at viruses you’d need something else.
From our identification genes we could identify all the organisms wearing yellow; ex. phylogenetic Family = Ducks. That wouldn’t tell us if they were always found in this ecosystem (native Eugene population) or just passing through (transient population), but we could figure that out if we looked at every home game of the season and found certain community members there time and again.
But knowing they are Ducks doesn’t tell us anything else about that community member. What will they do if it starts raining? Are they able to go mountain biking? Perhaps we could identify their potential for activity by looking at the objects they are carrying? That would be akin to metagenomics, identifying all the DNA present from all the organisms, which tells us what genes are present, but not if they are currently or ever used. It can be challenging to interpret: think of sequencing data from one organism’s genome as one 1,000,000-piece puzzle and all the genomes in a community as 1,000 1,000,000-piece puzzles all dumped in a pile. In the crowd, metagenomics would tell us who had a credit card that was specifically used to buy umbrellas, but not whether they’d actually use the umbrella if it rains (ex. Eugeneans would not).
We could describe what everyone is doing at this moment. That would be transcriptomics, identifying all the RNA to determine which genes were actively being transcribed into proteins for use in some cellular function. If we see someone in the crowd using that credit card for an umbrella (DNA), the receipt would be the RNA. RNA is a working copy you make of the DNA to take to another part of the cell and use as a blueprint to make a protein. You don’t want your entire genome moving around, or need it to make one protein, so you make a small piece of RNA that will only hang around for a short period before degrading (i.e. you crumpling that RNA receipt and throwing it away because who keeps receipts anymore).
Using transcriptomics, we’d see you were activating your money to get that umbrella, but we wouldn’t see the umbrella itself. For that, we’d need metabolomics, which uses chemistry and physics instead of genomics, in order to identify chemicals (most often proteins). Think of metabolomics as describing this crowd by all the trash and crumbs and miscellaneous items they left behind. It’s one way to know what biological processes occurred (popcorn consumption and digestion).
From a technical standpoint, researching a microbiome might mean looking at all the DNA from all the organisms present to know who they are and of what they are capable. It might also mean looking at all the RNA present, which would tell you what genes were being used by “everyone” for whatever they were doing at a particular moment. Or you might also add metabolomics to identify all the chemical metabolites, which would be all the end products of what those cells were doing, and which are more stable than RNA so they could give you data about a longer frame of time. Collectively, -omics are technology that looks at all of a certain biological substance to help you understand a dynamic community. However, it’s important to remember that each technology gives a particular view of the community and comes with its own limitations.
introduce students to basic concepts, laboratory techniques, historical background, terminology, and technology related to microbial ecology in or on mammals,
familiarize students with online resources, including sequence repositories, scientific databases, and analysis tools,
discuss how host-associated microbiomes are shaped by the anatomy and lifestyle of the host, and how the microbiome can reflect onto the health and performance of the host, and
review current literature on host-associated microbial ecology.
Keeping it fresh
While I’ve taught similar material at Montana State University, and have plenty of teaching experience from my graduate teaching assistant days at the University of Vermont, I’ve learned that each student population is different, with a unique core knowledge base and interests. Thus, I developed this course from scratch, and constantly revised it during the semester to adjust to the pace and learning style of my students. A draft syllabus, as well as an example of a student’s final project, can be found on my GitHub.
To improve engagement, I tried to make the course (which did not have a lab section) more interactive. I offered a tour of the molecular biology lab I work in, I brought agar plates to class so students could try culturing their own microbiota, and I dressed up like a dead cat.
These students were not science majors, and had had very little science since high school. Even if they had been science majors, I wanted to give a broader look at the field of science than just giving an overview of current knowledge. At the end of some lectures, I facilitated class discussions on various topics in science: the role of scientists in communicating science and whether we should report only or have an obligation to convince the public; elitism, recognition, and credit for intellectual property in a highly-collaborative working environment; the transfer of maternal microbiota and health status to offspring and how we approach prenatal care and parental leave; air quality (and air microbiota), residential zoning in urban areas, and income inequality; should we eat dirt?, etc. The students enthusiastically participated in class discussions, and — to my surprise — requested more (see below).
Phone a friend
I wanted to highlight current research in host-associated microbiomes, and hosted three mini-lectures from guest researchers; Deepika Sundarraman, a graduate students in UO physics, Dr. Candace Williams, a postdoctoral researcher who Skyped in from Vienna, and Dr. Edward Pajarillo, a postdoctoral researcher who Skyped in from Florida.
I really enjoyed teaching this group of students, and I got regular feedback from them about how the course was going and what was working. More formally, I volunteered the class to participate in a pilot evaluation for my midterm and end of term review, which asked more probing questions of students than typical teaching evaluations. For the midterm, only 4 of 15 students responded, but for the final, 13 of 15 responded and I have decided to share those (anonymous) course evaluations for IMM2018:
Students wanted more in-class discussions, and more group-based work, which was surprising to me as science students tend to prefer fewer of these, or at least the option to opt out. I am already considering additional topics for discussion next year. While there was an option on the final to submit a group project, no one chose to pursue that. Similarly, students were able to work collaboratively on journal article summaries to improve their comprehension, provided each student submitted a unique response. Perhaps this option simply needs to be reiterated.
What surprised me most about the evaluations was that several students replied that (the second half of) the course was not challenging enough. The course content was entirely new to them, and while the assignments drew on skills from their core competency as humanities students (reading and writing), they were required to distill large amounts of scientific information and be able to explain it back to me. It’s a challenge to serve the learning speed and style of all students in a class, and I try to manage this by varying the format of assignments, as well as to teach skills in the first part of the class which can be refined with successive assignments.
An example of this was the final project, for which the students needed to create a public outreach presentation in the format of their choice (essay, poster, pamphlet, presentation), which covered a particular topic or discussion point on host-associated microbial communities. Students were able to draw from scientific article summaries they had previously written, or even material from their exams (take-home essays), provided it was more developed and presented in a new and creative way. This flexibility allowed students to choose topics that they were passionate about, and to focus on the message rather the format. I felt this would help them find their voice, and judging by the final projects I received, it was effective.
That being said, if humanities students thought the material too easy, I take credit for communicating it well. I’m pleased with how the course turned out, as well as with the feedback I received from students. I’ve already begun implementing upgrades to my curricula, and have proposed this course again to the Honors College. Pending approval, I’ll be back at it next year!
Not a day goes by that I don’t search for information, and whether that information is a movie showtime or the mechanism by which a bacterial species is resistant to zinc toxicity, I need that information to be accurate. In the era of real fake-news and fake real-news, mockumentaries, and misinformation campaigns, the ability to find accurate and unbiased information is more important than ever.
Thanks to the massive shift towards digital archiving and open-access online journals, nearly all of my information hunting is done online (and an excellent reason why Net Neutrality is vital to researchers). Most of the time, this information is in the form of scientific journal articles or books online, and finding this information can be accomplished by using regular search engines. In particular, Google has really pushed to improve its ability to index scientific publications (critical to Google Scholar and Paperpile).
However, it takes skill to compose your search request to find accurate results. I nearly always add “journal article” or “scientific study” to the end of my query because I need the original sources of information, not popular media reports on it. This cuts out A LOT of inaccuracy in search results. If I’m looking for more general information, I might add “review” to find scientific papers which broadly summarize the results of dozens to hundreds of smaller studies on a particular topic. If I have no idea where to begin and need basic information on what I’m trying to look for, I will try my luck with a general search online or even Wikipedia (scientists have made a concerted effort to improve many science-related entries). This can help me figure out the right terminology to phrase my question.
How do I know if it’s accurate?
One of the things I’m searching for when looking for accurate sources is peer-review. Typically, scientific manuscripts submitted to reputable journals are reviewed by 1 – 3 other authorities in that field, more if the paper goes through several journal submissions. The reviewers may know who the authors are, but the authors don’t know their reviewers until at least after publication, and sometimes never. This single-blind (or double-blind if the reviewers can’t see the authors’ names) process allows for manuscripts to be reviewed, edited, and challenged before they are published. Note that perspective or opinion pieces in journals are typically not peer-reviewed, as they don’t contain new data, just interpretation. The demand for rapid publishing rates and the rise of predatory journals has led some outlets to publish without peer-review, and I avoid those sources. The reason is that scientists might not see the flaws or errors in their own study, and having a third party question your results improves your ability to communicate those results accurately.
Another way to assess the validity of an article is the inclusion of correct control groups. The control group acts a baseline against which you can measure your treatment effects, those which go through the same experimental parameters except they don’t receive an active treatment. Instead, the group receives a placebo, because you want to make sure that the acts of experimentation and observation themselves do not lead to a reaction – The Placebo Effect. The Placebo Effect is a very real thing and can really throw off your results when working with humans.
Similarly, one study does not a scientific law make. Scientific results can be situational, or particular to the parameters in that study, and might not be generalizable (applicable to a broader audience or circumstances). It often takes dozens if not a hundred studies to get at the underlying mechanisms of an experimental effect, or to show that the effect is reliably recreated across experiments.
Data or it didn’t happen. I can’t stress this one enough. Making a claim, statement, or conclusion is hollow until you have supplied observations to prove it. This a really common problem in internet-based arguments, as people put forth references as fact when they are actually opinionated speeches or videos that don’t list their sources. These opinionated speeches have their place, I post a lot of them myself. They often say what I want to say in a much more eloquent manner. Unfortunately, they are not data and can’t prove your point.
The other reason you need data to match your statements is that in almost all scientific articles, the authors include speculation and theory of thought in the Discussion section. This is meant to provide context to the study, or ponder over the broader meaning, or identify things which need to be verified in future studies. But often these statements are repeated in other articles as if they were facts which were evaluated in the first article, and the ideas get perpetuated as proven facts instead of as theories to be tested. This often happens when the Discussion section of an article is hidden behind a pay wall and you end up taking that second paper’s word for it about what happened in the first paper. It’s only when the claim is traced all the way back to the original article that you find that someone mistook thought supposition for data exposition.
The “Echo Chamber Effect” is also prominent when it comes to translating scientific articles into news publications, a great example of which is discussed by 538. Researchers mapped the genome of about 30 transgender individuals – about half and half of male to female and female to male, to get an idea of whether gender identity could be described with a nuanced genetic fingerprint rather than a binary category. This is an extremely small sample group, and the paper was more about testing the idea and suggesting some genes which would be used for the fingerprint. In the mix-up, comments about the research were attributed to a journalist at 538 – comments that the journalist had not made, and this error was perpetuated when further news organizations used other news publications as the source instead of conducting their own interview or referencing the publication. In addition, the findings and impact of the study were wrongly reported – it was stated that 7 genes had been identified by researchers as your gender fingerprint, which is a gross exaggeration of what the original research article was really about. When possible, try to trace information back to its origin, and get comments straight from the source.
How do I know if it’s unbiased?
This can be tricky, as there are a number of ways someone can have a conflict of interest. One giveaway is tone, as scientific texts are supposed to remain neutral. You can also check the author affiliations (who they are and what institution they are at), the conflict of interest section, and the disclosure of funding source or acknowledgements sections, all of which are common inclusions on scientific papers. “Following the money” is a particularly good way of determining if there is biased involved, depending on the reputation of the publisher.
When in doubt, try asking a librarian
There are a lot of resources online and in-person to help you find accurate information, and public libraries and databases are free to use!
Every scientist I know (myself included) underestimates how long it will take to write, edit, and submit a paper. Despite having 22 publications to date, I still set laughably-high expectations for my writing deadlines. Even though scientists go into a project with a defined hypothesis, objectives, and workflow, by the end of data analysis we often find ourselves surprised. Perhaps your assumptions were not supported by the actual observations, sometimes what you thought would be insignificant becomes a fascinating result. Either way, by the time you have finished most of the data analysis and exploration, you face the difficult task of compiling the results into a meaningful paper. You can’t simply report your data without giving them context and interpretation. I’ve already discussed the portions of scientific manuscripts and how one is composed, and here I want to focus on the support network that goes into this process, which can help shape that context that you provide to your data.
One of the best ways in which we can promote rigorous, thoughtful science is through peer-review, which can take a number of forms. It is worth noting, that peer-review also allows for professional bullying, and can be swayed by current theories and “common knowledge”. It is the journal editor’s job to select and referee reviewers (usually 2 – 4), to compile their comments, and to make the final recommendation for the disposition of the manuscript (accept, modify, reject). Reputation, and personal demographics such as gender, race, or institutional pedigree can also play a role in the quality and tone of the peer-review you receive. Nevertheless, getting an outside opinion of your work is critical, and a number of procedural changes to improve transparency and accountability have been proposed and implemented. For example, many journals now publish reviews names online with the article after it has been accepted, such that the review does not stay blind forever.
Thorough reading and editing of a manuscript takes time. Yet peer-reviewers for scientific journals almost unanimously do not receive compensation. It is an expected service of academics, and theoretically if we are all acting as peer-reviewers for each other then there should be no shortage. Unfortunately, due to the pressures of the publish-or-perish race to be awarded tenure, many non-tenured scientists (graduate students, post-docs, non-tenure track faculty, and pre-tenured tenure-track faculty) are reluctant to spend precious time on any activity which will not land them tenure, particularly reviewing. Moreover, tenured faculty also tend to find themselves without enough time to review, particularly if they are serving on a large number of committees or in an administrative capacity. On top of that, you are not allowed to accept a review if you have a conflict of interest, including current or recent collaboration with the authors, personal relationships with authors, a financial stake in the manuscript or results, etc. The peer-review process commonly gets delayed when editors are unable to find enough reviewers able to accept a manuscript, or when reviewers cannot complete the review in a timely manner (typically 2 – 4 weeks).
I have recently tried to solicit peer-review from friends and colleagues who are not part of the project before I submit to a journal. If you regularly follow my blog, you’ll probably guess that one of the reasons I do this is to catch spelling and grammatical mistakes, which I pick out of other works with hawk-like vision and miss in my own with mole-like vision. More importantly, trying to communicate my work to someone who is not already involved in the project is a great way to improve my ability to effectively and specifically communicate my work. Technical jargon, colloquial phrasing, sentence construction, and writing tone can all affect the information and data interpretation that a reader can glean from your work, and this will be modulated by the knowledge background of the reader.
I’ve learned that I write like an animal microbiologist, and when writing make assumptions about which information is common knowledge and doesn’t need a citation or to be included at all because it can be assumed. However, anyone besides animal microbiologists who have been raised on different field-specific common knowledge may not be familiar with the abbreviations, techniques, or terms I use. It may seem self-explanatory to me, but I would rather have to reword my manuscript that have readers confuse the message from my article. Even better, internal review from colleagues who are not involved with the project or who are in a different field can provide valuable interdisciplinary perspective. I have been able to apply my knowledge of animal science to my work in the built environment, and insights from my collaborators in plant ecology have helped me broaden my approach towards both animals and buildings.
No scientific article would be published without the help of the journal editorial team, either, who proof the final manuscript, verify certain information, curate figures and tables, and type-set the final version. But working backwards from submission and journal staff, before peer-review and internal peer-review, there are a lot of people that contribute to a scientific article who aren’t necessarily considered when contemplating the amount of personnel needed to compose a scientific article. In fact, that one article represents just the tip of the iceberg of people involved in that science in some way; there are database curators, people developing and maintaining open-source software or free analysis programs, laboratory technicians, or equipment and consumables suppliers. Broadening our definition of science support network further includes human resources personnel, sponsored projects staff who manage grants, building operational personnel who maintain the building services for the laboratory, and administrative staff who handle many of the logistical details to running a lab. It takes a village to run a research institution, to publish a scientific article, to provide jobs and educational opportunities, and to support the research and development which fuels economic growth. When it comes time to set federal and state budgets, it bears remembering that that science village requires financial support.
Academics love to keep books, such that they accumulate over the years until, one day, you move offices, change universities, or retire and give them all away. I happened upon one of these give-away treasure troves recently and grabbed several older books. I began my journey with a historical perspective on island biogeography, and I enjoyed it so much I thought I’d write about it.
The book is “The Song of the Dodo: Island Biogeography in an Age of Extinctions”, written in 1996 by David Quammen. David is a science writer, but has also written some fiction, and at the time this book was published lived in Montana, from where I so recently emigrated. It’s written in a meandering way, weaving together textbook information, historical accounts of ecologists from the last few centuries, and his own experiences traveling the world to visit the unique locations that inspire(d) scientists to brilliance. While it certainly helps to have a background in biology or ecology in order to fully appreciate the book, it’s seems interesting enough to grab a more general audience.
Be prepared for a feast of delicious jargon, though:
“The Origin of Species is a book of encyclopedic richness and inexhaustible tediousness, a great potpourri of argument and fact in which a reader can find almost anything a reader might want: Lamarckism, animal husbandry, geology, ethology, experimental botany, the kitchen sink, island biogeography.” pg. 200
So what is island biogeography? It’s the study of how species are distributed across an environment; specifically on islands. Sounds simple enough. Let’s go back to the Age of Exploration (late 1400s to the late 1700s) when new technology and a growing appreciation for the size of the planet gave rise to a burst of exploration. Suddenly- and this historical perspective is very Euro-centric- new lands, geology, peoples, plants, and animals were being discovered, and tales of the exotic made it back to Europe. Sometimes, preserved animal specimens would make it back to Europe, which was extremely tricky as they had to be prepared in the field, usually by skinning or pickling. Often, the heads, feet, tails, or wings would be removed during the process, accidentally or intentionally. This only fueled the mystery more: many species of Birds of Paradise had their feed removed during processing, leading British ecologists, many of whom were working off secondary information and had never traveled to these locales, to believe that these birds had no feet at all and lived entirely among the clouds until their death when they fell to the ground.
The lure of discovering new, fabulous species was irresistible, and naturalists began expeditions all over the globe to make observations and collect specimens. Largely, collectors interested in one particular animal or insect would select a small number of specimens for each species they collected, thus they accidentally missed the natural variations in size or color that one sees in wild animals. After all, one doesn’t always notice little differences when only looking at a few examples. Or, they would fail to record the particular location of their find, often only labeling it only by the continent on which is was collected. But some naturalists were more curious. They collected more specimens, more data, and began to notice patterns.
The most important pattern was that not all animals were found everywhere. Certainly, it was noted that certain animals were specific to a habitat- sharks to the ocean, camels to the desert, etc. But it wasn’t until people discovered animals found exclusively on islands that it really sunk in. And this is extremely important, because it begged the question: why? Why are some animals in one place and not another? How did they get there? The prevailing theories until that point were largely based on stories from the Christian bible, but with the discovery of so many new species, a literal ark was increasingly going to be improbably overcrowded.
Long story short, many ecologists actually began as geologists- Charles Darwin included, and in studying island formation it became understood that some island animals had crossed on land bridges, while others flew, swam, or drifted onto islands. The species and mode of arrival very much determined whether you could then get back off the island, or whether you were stuck. Ok, so now we know that animals can travel and change their own habitat location (which is different from migration), which went against the prevailing theory that animals were located where they had been put during a creation event.
The next important pattern was that multiple, closely-related species could exist in a place at the same time. In the years following his voyage while studying the specimens he collected, Charles Darwin noticed this of the mockingbirds, tortoises, and eventually the finches on the Galapagos, which was just a brief stop on his 5 year geology cruise aboard the Beagle (1831-1836). Again, this was important, because what was the likelihood that all these similar bird species came to the same island chain at the same time? It was more likely that a few birds of a single species had come over, and these birds had changed over thousands of generations into several new species. The accepted notion was that animals didn’t change- they remained as they had been created. The idea that a species could change or evolve over time was, at best, silly and at worst, blasphemous.
Nevertheless, a number of ecologists had made reference to the possibility of change during the Age of Exploration, but lacked solid data and a concrete theory of how. The mockingbirds represented true archipelago speciation; one species came to the Galapagos islands and populations became isolated on separate islands until through genetic drift they became different species, but there were only four mockingbird types and that was little enough to go on. On the other hand, Darwin had 31 individuals representing what he thought was 14 unrelated bird species, but it wasn’t until after his voyage, when an ornithologist properly classified the birds as all being closely-related finches, that Darwin paid any attention to them at all. In fact, Darwin nearly missed the idea of evolution because he failed to label which island his finches came from and very little about their ecology or behavior- he had to gather missing data from other accounts for years before he could see a real pattern. To be fair, the finches are a much more complicated pattern because they display adaptive radiation; one species arrived on the islands, but populations were only transiently isolated and when they crossed paths again they were still similar enough to compete, so different species evolved to fill different ecological roles (niches) in order to avoid starvation due to competition.
Darwin’s first account of his Beagle voyage made just a brief mention of this observation on closely-related species, but it changed the life of Alfred Wallace. Wallace came from a poor background, and eventually paid for his love of naturalism and data collection by selling the specimens he collected. Many British naturalists at the time were wealthy, and selling one’s collection seemed base- thus Wallace, with no title or reputation, was dismissed for most of his early career. Years after Darwin went to the Galapagos, Wallace went to South America and Indonesia and came to the same conclusion about multiple closely related species: that one species had become many. Wallace made the jump to speciation much faster, and sent Darwin a manuscript that was frighteningly similar to the yet-unpublished Origin of Species, which Darwin had worked on for 20 years to gain enough proof to avoid being laughed at. Social politics aside, which are discussed in the book, a joint manuscript was presented, On the Tendency of Species to form Varieties; and on the Perpetuation of Varieties and Species by Natural Means of Selection, and a year later Darwin publishedOn the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, which, incidentally doesn’t even mention Galapagos finches.
The idea of macroorganismal evolution was difficult to come by, largely because it’s a much longer process than a human can witness, and because a possible mechanism for change was completely unknown (genetics was a long way away). By studying islands, ecologists could study evolution in miniature worlds where the pressure to stay alive was great- indeed, many species were marooned on the islands they colonized. Studying this, and the livestock breeding industry, gave rise to the idea in Darwin’s mind of Natural Selection– that external forces could change a species over time by forcing the species to change.
Because animals are isolated on islands, they change to fit that particular ecosystem in a very visible way. Wallace noticed this happening in his travels in South America where large rivers converged: animals that could not cross the river became isolated and there would be similar but distinct species on each side of the river. Again, the whimsical biogeography of a deity became less probable than natural forces (food, geography, predation, competition) driving the distribution of animals and plants. Still, it took decades to iron out the particulars of evolution, and even today people refuse to acknowledge it.
But this book isn’t solely a historical account- all of that is setting the stage for a larger picture: extinction. For even as island pressures select for the creation of species distinct from those found on mainlands, it also selects them for extinction. Islands are partially or completely isolated, and this means any breeding population is small to begin with, and eventually can become inbred. Island populations often collapse: the gene pool becomes too stagnant, a natural disaster hits, food becomes scarce, a predator appears. Because there are only so many individuals, and because they are adapted to a very specific location, island species can’t deal with change. Unfortunately, humans bring nothing but change. As we develop natural land for our own use we fragment habitat, and for animals that can’t cross a city to get to the other populations, their gene pool and food options are limited. They become reliant on very specific living conditions in their small habitat fragments, and they are more susceptible to disease, inbreeding, predators, and climate change. The smaller the habitat, the fewer the individuals, and the ore they struggle to survive. As humans colonize all parts of the globe we are leaving man-made islands in our wake, with marooned populations of plants and animals that find it increasingly difficult to sustain themselves- we are the cause of the mass extinction of animals and plants around the globe that only trickles into our mainstream news.
“We still argue about when it [the dodo] actually became extinct, but it probably disappeared around the 1660s. It’s become the sort of legendary bird of extinction. And a very important bird. There were extinctions before and there’s been lots of extinctions since, but it was an important extinction because that was the first time, the first time in the whole of man’s history, that he actually realized he had caused the disappearance of a species.”
-interviewing Carl Jones about the extinction of the dodo, pg. 277
The level of detail provided in The Song of the Dodo is fascinating, especially because historical accounts so often lose sight of a who a person was and the journey they had to take. Darwin wasn’t always correct, other scientists had the right theories but the wrong data to prove them, and the elitism of early science often led to the adoption of incorrect theories from otherwise brilliant men. The book gives an honest perspective- that all scientists are trying their best to make sense of the information they have, and that it can take an extremely long time to put the entire puzzle together. And it gives cause for hope. While we may not be able to bring back populations of species we have pushed to the brink, life is pluripotent. If we give the natural world some space- it’ll grow back.