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This may be a strange question, but does anyone know what kind of tree this could be?
I know, it's just a comic, but these trees, at “walking distance” within that comic are easily identifiable as Grandidier's Baobabs:
(That might indicate, of course, that the above tree also occurs on Madagascar, but it's a comic, so all bets are off. And yes, we know, there are no squirrels on Madagascar.)
It reminds me of the smooth-barked Australian gum trees / eucalyptus, like a salmon gum, ghost gum, etc.
Although there are no squirrels in Australia :)
This photo of a Salmon Gum is from http://www.fpc.wa.gov.au/content_migration/plantations/species/arid/salmon_gum.aspx
As @fileunderwater suggested, this looks like an Acacia. Like many others with OSX, I have this incuded picture of an acacia as one of my screensaver rotations.
It looks very similar in bauplan to the illustration.
As Saxon Druce has pointed out it looks very much like a eucalypt. Specifically a desert or savanna species such as the ghost gum (Corymbia aparrerinja).
Other eucalypts (Eucalyptus and Corymbia spp.) have similar growth forms.
The silhouette is obviously stylised and appears to have less foliage than a real eucalypt in order to make the profile neater. The branching pattern and the way the foliage is clustered in rounded clumps and textured in the image are representative of eucalypts. I would argue it is not an Acacia - they have very distinctive branching patterns and are more spreading with a flatter top than this.
It looks like a pine to me. Might be close to Pinus pinaster but take into account that a) I'm not a botanist. b) I'm only familiar with pines that grow in my area (Catalonia).
Killer Interview Question: What Kind Of Tree Would You Be?
Would you be an Eucalyptus tree? How about a Bottlebrush tree? Maybe you’re more of a Jacaranda tree. We want to find out on this week’s KIQ.
We’ve had quite a few whacky interview questions featured on KIQ, but this one still managed to raise a few eyebrows in the office: “If you were a tree, what kind of tree would you be?”
According to a submission on job interview website Glassdoor, this question was asked by networking vendor Cisco for the role of senior technical writer.
Career coach Peggy McKree at Career Confidential said this question is akin to “What animal would you be?” or “What kind of fruit would you be?” and is used to check a candidate’s creativity. It is also used to gauge an applicant’s ability to think on their feet.
The interviewer doesn’t want to hear that you want to be an apple tree solely because you like apples. Here’s what McKree had to say:
“To answer this question (or any kind of question where you have to choose ‘what would you be?’, think in a broad way about the qualities of whatever it is that you’re going to pick and how you would explain your choice. What character or personality traits would be useful for someone in that role to have? Think in terms of the utilitarian productiveness of your choice as it relates to the job you’re applying for. What does that job require? And then be careful of the nuances.”
For example, you may want to go for an Eucalyptus tree because it grows fast and is extremely hardy.
A data set comprehensively covering the three domains of life was generated using publicly available genomes from the Joint Genome Institute's IMG-M database (img.jgi.doe.gov), a previously developed data set of eukaryotic genome information 30 , previously published genomes derived from metagenomic data sets 7,8,31,32 and newly reconstructed genomes from current metagenome projects (see Supplementary Table 1 for NCBI accession numbers). From IMG-M, genomes were sampled such that a single representative for each defined genus was selected. For phyla and candidate phyla lacking full taxonomic definition, every member of the phylum was initially included. Subsequently, these radiations were sampled to an approximate genus level of divergence based on comparison with taxonomically described phyla, thus removing strain- and species-level overlaps. Finally, initial tree reconstructions identified aberrant long-branch attraction effects placing the Microsporidia, a group of parasitic fungi, with the Korarchaeota. The Microsporidia are known to contribute long branch attraction artefacts confounding placement of the Eukarya 33 , and were subsequently removed from the analysis.
This study includes 1,011 organisms from lineages for which genomes were not previously available. The organisms were present in samples collected from a shallow aquifer system, a deep subsurface research site in Japan, a salt crust in the Atacama Desert, grassland meadow soil in northern California, a CO2-rich geyser system, and two dolphin mouths. Genomes were reconstructed from metagenomes as described previously 7 . Genomes were only included if they were estimated to be >70% complete based on presence/absence of a suite of 51 single copy genes for Bacteria and 38 single copy genes for Archaea. Genomes were additionally required to have consistent nucleotide composition and coverage across scaffolds, as determined using the ggkbase binning software (ggkbase.berkeley.edu), and to show consistent placement across both SSU rRNA and concatenated ribosomal protein phylogenies. This contributed marker gene information for 1,011 newly sampled organisms, whose genomes were reconstructed for metabolic analyses to be published separately.
The concatenated ribosomal protein alignment was constructed as described previously 16 . In brief, the 16 ribosomal protein data sets (ribosomal proteins L2, L3, L4, L5, L6, L14, L16, L18, L22, L24, S3, S8, S10, S17 and S19) were aligned independently using MUSCLE v. 3.8.31 (ref. 34). Alignments were trimmed to remove ambiguously aligned C and N termini as well as columns composed of more than 95% gaps. Taxa were removed if their available sequence data represented less than 50% of the expected alignment columns (90% of taxa had more than 80% of the expected alignment columns). The 16 alignments were concatenated, forming a final alignment comprising 3,083 genomes and 2,596 amino-acid positions. A maximum likelihood tree was constructed using RAxML v. 8.1.24 (ref. 35), as implemented on the CIPRES web server 36 , under the LG plus gamma model of evolution (PROTGAMMALG in the RAxML model section), and with the number of bootstraps automatically determined (MRE-based bootstopping criterion). A total of 156 bootstrap replicates were conducted under the rapid bootstrapping algorithm, with 100 sampled to generate proportional support values. The full tree inference required 3,840 computational hours on the CIPRES supercomputer.
To construct Fig. 2, we collapsed branches based on an average branch length criterion. Average branch length calculations were implemented in the Interactive Tree of Life online interface 37 using the formula:
Average branch length=mean([root distance to tip]–[root distance to node]) for all tips connecting to a node.
We tested values between 0.25 and 0.75 at 0.05 intervals, and selected a final threshold of <0.65 based on generation of a similar number of major lineages as compared to the taxonomy-guided clustering view in Fig. 1. The taxonomy view identified 26 archaeal and 74 bacterial phylum-level lineages (counting the Microgenomates and Parcubacteria as single phyla each), whereas an average branch length of <0.65 resulted in 28 archaeal and 76 bacterial clades.
For a companion SSU rRNA tree, an alignment was generated from all SSU rRNA genes available from the genomes of the organisms included in the ribosomal protein data set. For organisms with multiple SSU rRNA genes, one representative gene was kept for the analysis, selected randomly. As genome sampling was confined to the genus level, we do not anticipate this selection process will have any impact on the resultant tree. All SSU rRNA genes longer than 600 bp were aligned using the SINA alignment algorithm through the SILVA web interface 38,39 . The full alignment was stripped of columns containing 95% or more gaps, generating a final alignment containing 1,871 taxa and 1,947 alignment positions. A maximum likelihood tree was inferred as described for the concatenated ribosomal protein trees, with RAxML run using the GTRCAT model of evolution. The RAxML inference included the calculation of 300 bootstrap iterations (extended majority rules-based bootstopping criterion), with 100 randomly sampled to determine support values.
To test the effect of site selection stringency on the inferred phylogenies, we stripped the alignments of columns containing up to 50% gaps (compared with the original trimming of 95% gaps). For the ribosomal protein alignment, this resulted in a 14% reduction in alignment length (to 2,232 positions) and a 44.6% reduction in computational time ( ∼ 2,100 h). For the SSU rRNA gene alignment, stripping columns with 50% or greater gaps reduced the alignment by 24% (to 1,489 positions) and the computation time by 28%. In both cases, the topology of the tree with the best likelihood was not changed significantly. The ribosomal protein resolved a two-domain tree with the Eukarya sibling to the Lokiarcheaota, while the SSU rRNA tree depicts a three-domain tree. The position of the CPR as deep-branching on the ribosomal protein tree and within the Bacteria on the SSU rRNA tree was also consistent. The alignments and inferred trees under the more stringent gap stripping are available upon request.
We have included names for two lineages for which we have previously published complete genomes 40 . At the time of submission of the paper describing these genomes 40 , the reviewer community was not uniformly open to naming lineages of uncultivated organisms based on such information. Given that this practice is now widely used, we re-propose the names for these phyla. Specifically, for WWE3 we suggest the name Katanobacteria from the Hebrew ‘katan’, which means ‘small’, and for SR1 we suggest the name Absconditabacteria from the Latin ‘Abscondo’ meaning ‘hidden’, as in ‘shrouded’.
NCBI and/or JGI IMG accession numbers for all genomes used in this study are listed in Supplementary Table 1. Additional ribosomal protein gene and 16S rRNA gene sequences used in this study have been deposited in Genbank under accession numbers KU868081–KU869521. The concatenated ribosomal protein and SSU rRNA alignments used for tree reconstruction are included as separate files in the Supplementary Information.
Harmful Insects and Disease
Virulent diseases like Dutch elm disease and the chestnut blight have caused sudden death to entire forests in North America. However, the most common diseases are more subtle in their work, killing many more trees in total than virulent types and cost forest and yard tree owners billions of dollars in forest product and specimen tree value.
These "common" diseases include three bad ones: Armillaria root rot, oak wilt, and anthracnose. These pathogens invade the tree through leaves, roots and bark wounds and damage a trees vascular system if not prevented or treated. In natural forests, prevention is the only economic option available and is a significant part of a forester's silvicultural management plan.
Harmful insects are opportunistic and often invade trees under stress from environmental problems or disease. They not only can directly cause tree death but will spread harmful disease fungi from a host tree to surrounding trees. Insects can attack a tree's cambial layer by boring for food and nesting cavities, or they can defoliate a tree to the point of death. Bad insects include pine beetles, the gypsy moth, and emerald ash borers.
What Could Be Eating the Roots of My Outdoor Plants?
I was recently asked by one of the local master gardeners to do another article on pine vole control. For those of you not familiar with pine voles, these mice burrow under the soil and feed on plant roots and trees. Voles have been known to kill nandinas and fruit trees, and have destroyed hosta plantings. Although voles can be legally poisoned in North Carolina, homeowners have other options in helping to control their populations.
Pine voles like areas that are weedy or that have thick vegetation. Eliminating these sites will reduce their food supply, and expose the voles to predators. Mowing on a regular basis will also help to reduce vole populations.
Mulched areas are also ideal habitats for voles. Try to avoid mulching over a couple of inches deep. If you have a vole problem you may want to consider removing the mulch altogether or at least pulling it away from landscape plants. Research has shown that landscape fabrics may increase vole populations.
Voles can be successfully excluded from individual trees and shrubs using hardware cloth. The cloth should be wrapped around the trunk and it must be buried at least 6 inches below the soil line to prevent the voles from digging under the wire. Make sure that the wire is loose around the trunk so that it does not girdle the tree as the trunk expands.
If you are going to try to kill the voles with poison bait, the North Carolina Extension Service has a couple of tips. First, apply baits only in late fall or winter. Do not apply baits if rain is expected within 3 days of application. Apply baits in midafternoon since voles are active at dusk and dawn. Finally, combine the baits with the other management tactics mentioned above to get better control of vole populations.
Maple Syrup Plantation? New Insights Into Tree Biology Could Radically Change The Industry
New insights into tree biology may be the start of a revolution in the maple syrup industry.
At first, University of Vermont researchers Tim Perkins and Abby van den Berg were just trying to learn more about how sap flows through a maple tree. But what they found eventually blossomed into a new model for syrup production – one where sugarers draw their sap from young trees planted in dense plantations, rather than mature forests.
Perkins and van den Berg were testing a vacuum pump system used to extract sap on a maple tree that had the crown – branches, leaves, and stems – removed. But the vacuum tap kept on pulling sap out long after the researchers expected the flow to stop.
“We got to the point where we should have exhausted any water that was in the tree, but the moisture didn’t drop,” Perkins said in a press release from UVM issued last November. “The only explanation was that we were pulling water out of the ground, right up through and out the stem.”
The discovery led the pair to envision a new method of sugaring. Instead of depending on forest land, a sugarer could use a plantation of young saplings rooted in a farm field.
“Once we saw that we could get yields without tops it was — wow! — this changes the basic paradigm,” van den Berg said in a statement. “It became clear that we could deal with an entirely new framework.”
The plantation model could result in much higher yields, too. The pair estimates that one acre of maple plantation, with 6,000 saplings, could yield 400 gallons of syrup. A traditional “sugarbush” of tapped trees usually yields about 40 gallons of syrup per acre from 80 mature trees.
And efficiency is on the industry’s mind lately. In Nova Scotia, maple syrup trees aren’t yielding up as much sap – a 25 percent drop, on average, from the 1970s, according to the CBC. People are still stumped as to why climate change is high on the list of potential culprits. Others think the trees may just be overworked from decades of use.
"I think subsequent tapping is slightly detrimental to the tree," Keith Crowe, a 62-year maple industry veteran, told the CBC. "I don't think it's ever as productive as it is in the initial stages in spite of the growth that might happen in the meantime."
Maple syrup production is very subject to the whim of the weather, as sap flow requires cold nights, with below-freezing temperatures, followed by warmer days. Sap also stops flowing in spring when the tree’s flower buds expand and leaves develop. In 2013, U.S. maple syrup producers tapped 3.25 million gallons – a 70 percent increase from 2012, according to the U.S. Department of Agriculture [PDF]. Last year the weather was just right for sap production – cool spring months delayed the maple buds from forming, resulting in a longer season. But who can predict how next years’ season will play out?
The plantation model may also be better suited to cope with a changing climate. The smaller saplings freeze and thaw faster than their grown-up counterparts, so they don't need as intense of a freeze and thaw cycle to start the sap flowing.
Planting saplings for syrup seems like a no-brainer, given the prospect of higher yields on smaller parcels of land – but the costs of equipment, maintenance, and labor are also higher with the plantation method. Still, as Modern Farmer points out, there are other business advantages to a maple plantation -- relying on young trees means that producers could bounce back much faster if their trees are damaged by natural disasters. Instead of waiting decades for a forest to mature, the system devised by the UVM researchers would be up and running within seven years.
Overall, it seems that sugar makers are cautious, but open-minded.
“I could see how it would be very efficient and replace the wild crop,” Hillsboro Sugar Works owner Dave Folino told Modern Farmer. “I’m tied to the old images but it is tantalizing the thought of controlling things. In my lifetime, I’ve seen the shrinking of the dairy industry [in Vermont]. I would hate to see the same for the wild crop but it is probably economically inevitable.”
What kind of tree could this be? - Biology
Throughout the laboratory portion of most Biology laboratories, you will be conducting experiments. Science proceeds by use of the experimental method. This handout provides a summary of the steps that are used in pursuing scientific research. This general method is used not only in biology but in chemistry, physics, geology and other hard sciences.
To gather information about the biological world, we use two mechanisms: our sensory perception and our ability to reason. We can identify and count the types of trees in a forest with our eyes, we can identify birds in the rainforest canopy with our ears, and we can identify the presence of a skunk with our nose. Touch and taste help us experience the biological world as well. With the information we gather from our senses, we can make inferences using our reason and logic. For instance, you know that you see palm trees in tropical and subtropical regions and can infer that palm trees will not be found in central Maine because of the harshness of our winter.
Our reason allows us to make predictions about the natural world. Scientists attempt to predict and perhaps control future events based on present and past knowledge. The ability to make accurate predictions hinges on the seven steps of the Scientific Method.
Step 1. Make observations. These observations should be objective, not subjective. In other words, the observations should be capable of verification by other scientists. Subjective observations, which are based on personal opinions and beliefs, are not in the realm of science. Heres an objective statement: It is 58 °F in this room. Heres a subjective statement: It is cool in this room.
The first step in the Scientific Method is to make objective observations. These observations are based on specific events that have already happened and can be verified by others as true or false.
Step 2. Form a hypothesis. Our observations tell us about the past or the present. As scientists, we want to be able to predict future events. We must therefore use our ability to reason.
Scientists use their knowledge of past events to develop a general principle or explanation to help predict future events. The general principle is called a hypothesis. The type of reasoning involved is called inductive reasoning (deriving a generalization from specific details).
A hypothesis should have the following characteristics:
It should be a general principle that holds across space and time
It should be a tentative idea
It should agree with available observations
It should be kept as simple as possible.
It should be testable and potentially falsifiable. In other words, there should be a
way to show the hypothesis is false a way to disprove the hypothesis.
Some mammals have two hindlimbs would be a useless hypothesis. There is no observation that would not fit this hypothesis!
All mammals have two hindlimbs is a good hypothesis. We would look throughout the world at mammals. When we find whales, which have no hindlimbs, we would have shown our hypothesis to be false we have falsified the hypothesis.
When a hypothesis involves a cause-and-effect relationship, we state our hypothesis to indicate there is no effect. A hypothesis, which asserts no effect, is called a null hypothesis. For instance, the drug Celebra does not help relieve rheumatoid arthritis.
Step 3. Make a prediction. From step 2, we have made a hypothesis that is tentative and may or may not be true. How can we decide if our hypothesis is true?
Our hypothesis should be broad it should apply uniformly through time and through space. Scientists cannot usually check every possible situation where a hypothesis might apply. Lets consider the hypothesis: All plant cells have a nucleus. We cannot examine every living plant and every plant that has ever lived to see if this hypothesis is false. Instead, we generate a prediction using deductive reasoning (generating a specific expectation from a generalization). From our hypothesis, we can make the following prediction: If I examine cells from a blade of grass, each one will have a nucleus.
Now, lets consider the drug hypothesis: The drug Celebra does not help relieve rheumatoid arthritis . To test this hypothesis, we would need to choose a specific set of conditions and then predict what would happen under those conditions if the hypothesis were true. Conditions you might wish to test are doses administered, length of time the medication is taken, the ages of the patients and the number of people to be tested.
All of these conditions that are subject to change are called variables. To gauge the effect of Celebra, we need to perform a controlled experiment. The experimental group is subjected to the variable we want to test and the control group is not exposed to that variable. In a controlled experiment, the only variable that should be different between the two groups is the variable we want to test.
Lets make a prediction based on observations of the effect of Celebra in the laboratory. The prediction is: Patients suffering from rheumatoid arthritis who take Celebra and patients who take a placebo (a starch tablet instead of the drug) do not differ in the severity of rheumatoid arthritis. [Note that we base our prediction on our null hypothesis of no effect of Celebra.]
Step 4. Perform an experiment. We rely again on our sensory perception to collect information. We design an experiment based on our prediction.
Our experiment might be as follows: 1000 patients between the ages of 50 and 70 will be randomly assigned to one of two groups of 500. The experimental group will take Celebra four times a day and the control group will take a starch placebo four times a day. The patients will not know whether their tablets are Celebra or the placebo. Patients will take the drugs for two months. At the end of two months, medical exams will be administered to determine if flexibility of the arms and fingers has changed.
Step 5. Analyze the results of the experiment. Our experiment produced the following results: 350 of the 500 people who took Celebra reported diminished arthritis as the end of the period. 65 of the 500 people who took the placebo reported improvement.
The data appear to show that there was a significant effect of Celebra. We would need to do a statistical analysis to demonstrate the effect. Such an analysis reveals that there is a statistically significant effect of Celebra.
Step 6. Draw a conclusion. From our analysis of the experiment, we have two possible outcomes: the results agree with the prediction or they disagree with the prediction. In our case, we can reject our prediction of no effect of Celebra. Because the prediction is wrong, we must also reject the hypothesis it was based on.
Our task now is to reframe the hypothesis is a form that is consistent with the available information. Our hypothesis now could be: The administration of Celebra reduces rheumatoid arthritis compared to the administration of a placebo.
With present information, we accept our hypothesis as true. Have we proved it to be true? Absolutely not! There are always other explanations that can explain the results. It is possible that the more of the 500 patients who took Celebra were going to improve anyway. Its possible that more of the patients who took Celebra also ate bananas every day and that bananas improved the arthritis. You can suggest countless other explanations.
How can we prove that our new hypothesis is true? We never can. The scientific method does not allow any hypothesis to be proven. Hypotheses can be disproven in which case that hypothesis is rejected as false. All we can say about a hypothesis, which stands up to, a test to falsify it is that we failed to disprove it. There is a world of difference between failing to disprove and proving. Make sure you understand this distinction it is the foundation of the scientific method.
So what would we do with our hypothesis above? We currently accept it as true. To be rigorous, we need to subject the hypothesis to more tests that could show it is wrong. For instance, we could repeat the experiment but switch the control and experimental group. If the hypothesis keeps standing up to our efforts to knock it down, we can feel more confident about accepting it as true. However, we will never be able to state that the hypothesis is true. Rather, we accept it as true because the hypothesis stood up to several experiments to show it is false.
Step 7. Report your results. Scientists publish their findings in scientific journals and books, in talks at national and international meetings and in seminars at colleges and universities. Disseminating results is an essential part of the scientific method. It allows other people to verify your results, develop new tests of your hypothesis or apply the knowledge you have gained to solve other problems.
The Future of Crime-Fighting Is Family Tree Forensics
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Former police officer Joseph James DeAngelo, accused of being the Golden State Killer, stands in a Sacramento, Calif., jail court on May 29, 2018, as a judge weighs how much information to release about his arrest. DeAngelo is suspected in at least a dozen killings and roughly 50 rapes in the 1970s and ྌs. Paul Kitagaki Jr./AP
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In April, a citizen scientist named Barbara Rae-Venter used a little-known genealogy website called GEDMatch to help investigators find a man they’d been looking for for nearly 40 years: The Golden State Killer. In the months since, law enforcement agencies across the country have flocked to the technique, arresting a flurry of more than 20 people tied to some of the most notorious cold cases of the last five decades. Far from being a forensic anomaly, genetic genealogy is quickly on its way to becoming a routine police procedure. At least one company has begun offering a full-service genetic genealogy shop to law enforcement clients. And Rae-Venter’s skills are in such high demand that she’s started teaching her secrets to some of the biggest police forces in the US, including the Federal Bureau of Investigation.
Identifying individuals from their distant genetic relatives, a technique called long-range familial searching, is a potent alternative to the types of DNA searches commonly available to cops. Those are typically limited to forensic databases, which can only identify close kin—a sibling, parent, or child—and are highly regulated. No court order is required to mine GEDMatch’s open source trove of potential leads, which, unlike forensic databases, contains genetic bits of code that can be tied to health data and other personally identifiable information.
Currently, there aren’t any laws that regulate how law enforcement employs long-range familial searching, which hobbyists and do-gooders have turned to for years to find the biological families of adoptees. But some legal experts argue its use in criminal cases raises grave privacy concerns. They expect to see a legal challenge at some point, though probably not in the next year. In the meantime, GEDMatch is becoming even more powerful, as it grows by nearly a thousand new uploads every day. And with hundreds more cases currently in the hands of full-time family-tree builders, one thing’s for sure: In 2019, genealogy is going to send a lot more people to jail.
It was the last Saturday of June and CeCe Moore had been working on her couch, hunched over her laptop for 16 hours straight. The month before, the genetic genealogist had been hired by a forensic DNA company in Virginia called Parabon, to lead its new division devoted to long-range familial searching. She was immersed in a case out of Fort Wayne, Indiana In the spring of 1998, eight-year-old April Tinsley went missing from her home. Three days later, a jogger discovered her body in a ditch on DeKalb County Road 68, about 20 miles outside of town. She had been raped and strangled to death.
For years, Tinsley’s killer haunted that northeastern corner of Indiana, leaving messages scrawled on a barn bragging of his crime. In 2004, four threatening notes appeared on bicycles owned by young girls that had been left in their yards. The notes, which were claimed to be written by the same person that killed Tinsley, were placed inside baggies alongside used condoms. The semen matched DNA found in Tinsley’s underwear.
This summer, Indiana investigators extracted DNA from the original crime scene and sent it to Parabon. There, the company reverse-engineered the information into a DNA data profile similar to what you would get back from consumer genetics companies like 23andMe or Ancestry. Then they uploaded it to GEDMatch and waited for a match. They got 12. Twelve relatives, ranging from fifth to third cousins.
So that’s where Moore started, that weekend in June. The cousins represented four different family trees containing thousands of people, all of which somehow had to tie into the Fort Wayne killer. The first thing she did was work backward in time to locate ancestors from whom the suspect and the 12 matches were both descended. Eventually she found four couples, born between 1809 and 1849. Once she had them, she could move forward in history, building out family trees of every generation until the present. She did this by tracking names and faces through census records, newspaper archives, school yearbooks, and social media.
By the time night fell over her home in San Diego, she had begun to close in on a single branch, into which the four genetic tributaries all ran. From there things moved quickly. As the clock ticked past midnight, she found the relatives that had struck out for Indiana. It didn’t take much longer to circle in on two brothers who lived in the area where Tinsley was murdered. Full siblings are as close as genetic genealogy can get. But Moore had a hunch. One brother struck her as a recluse he had no wife or kids, he lived in a trailer, there were no pictures of him anywhere, and his family never mentioned him on Facebook.
Moore laid this all out for the Indiana investigators. A few days later they came back to her with a photo of one of the two brothers, with a hand-written note underneath. She gasped. “I thought it was him, but I wasn’t sure until I saw his writing,” Moore says. “It was the same as those notes and that barn.”
Indiana authorities staked out the trailer the first week of July and collected a piece of trash with the suspect’s DNA on it. Lab tests confirmed that the DNA recovered from the condoms in 2004, and the crime scene in 1988, belonged to the same man: 59-year-old John Dale Miller. Police arrested him July 15th. According to local reports, when the police asked him why they were at his home, Miller replied, “April Tinsley.” On Friday, December 7, Miller pled guilty in the Allen County Courthouse to murder and child molestation, as part of a plea agreement. On December 21, a judge sentenced him to 80 years in prison.
Miller is the first person genetic genealogy has put away for good. There could soon be others. Parabon has made public its involvement in 20 “solved” cases so far, with eight more undisclosed. Of those, at least four of the suspects were already deceased. The company was able to get up and running quickly after the Golden State Killer news broke the ice, because it had already created 100 or so genetic profiles through its phenotyping service, which creates a composite image from DNA for police to circulate in hopes of getting a lead. After hiring Moore, they quickly brought on three more genetic genealogists over the summer, and are in the process of hiring one more. The company says it’s now uploaded 200 profiles to GEDMatch, which represent cold cases from nearly as many law enforcement agencies scattered around the US. Parabon is actively working on 40 such cases.
Some of those include active cases, not just crimes committed decades ago. For example, in April, exactly a week before the Golden State Killer announcement, a man broke into a residence in the red-rocked southern Utah town of St. George, and sexually assaulted the 79-year-old woman who lived there. Three months later, authorities arrested a suspect, Spencer Glen Monnett, based on Moore’s genetic detective work. She says everyone clears their schedules to prioritize any active cases. At the moment, Parabon is working on at least one other active case involving a serial offender, but the company expects it to become a bigger part of what they do in 2019.
“In these active cases that come back with no match in CODIS [the federal offender database], law enforcement are realizing they don’t have to wait until every last avenue has been exhausted before coming to us,” says Ellen Greytak, who runs the company’s advanced DNA services division. “Genetic genealogy can be a tool to use right away.”
Rae-Venter, the genetic genealogist who cracked the Golden State Killer case, has also begun taking on active cases, with a small team of volunteers who mostly work pro bono. Right now she’s spending 12 to 15 hours a day, six days a week trying to track down a serial rapist who is still out there committing crimes. In addition to that one, her consultancy group is working through a backlog of 25 to 30 more cold cases. And she’s still collaborating closely with the Sacramento County detectives she joined forces with on the GSK case. Rae-Venter says a large part of their queue are referrals from the FBI.
Indeed, the feds can’t seem to get enough of her. Earlier this year, The FBI flew Rae-Venter to Houston, Texas to give a seven hour presentation on genetic genealogy to a room of 100 people—mostly federal agents, some local police officers, and even one Texas Ranger in a signature white rancher-style cowboy hat. “It’s really catching people’s attention,” she says. While family historians such as herself may be leading the way in this emerging field, she thinks it makes more sense to train, and perhaps even certify, law enforcement, rather than try to pull from the hobbyist community. Ultimately, she believes every major law enforcement agency will have its own specialists on staff. “I think this belongs to detectives, not genealogists,” says Rae-Venter.
As an example, she points to the arrest in September of the man believed to be the NorCal Rapist, another serial offender who terrorized victims in six California counties over a 15-year period beginning in 1991. Detectives from the Sacramento District Attorney’s office, who Rae-Venter had trained, uploaded a genetic profile of the suspect and built out family trees on their own. According to the DA’s office, they singled out the man arrested, Roy Charles Waller, in just 10 days.
Genetic genealogy alone isn’t enough to make an arrest. Investigators have to do confirmatory DNA testing, by retrieving bits of genetic material from the suspect, usually pulled from his or her trash, and comparing them to DNA found at the crime scene. But legal scholars worry that the widespread adoption of long-range familial searches will expose vast numbers of innocent people to genetic surveillance.
GEDMatch, which currently houses 1.2 million profiles from folks who’ve had their DNA analyzed at places like 23andMe and Ancestry, can now be used to identify at least 60 percent of all Americans with European Ancestry, regardless of whether they themselves have ever been tested. That’s according to two recent analyses by genetics researchers, who expect databases like GEDMatch to grow so big in the next few years that it will be possible to find anyone from just their DNA, even if they haven’t voluntarily put it in the public domain.
“You can’t claw back the profile of your third cousin once removed who you don’t even know exists,” says Erin Murphy, a law professor at New York University Law School and an expert on familial DNA searches. If someone gets ensnared in a long-range familial search, she says, they’re going to have very little legal recourse. “These searches throw into sharp relief how current privacy protections under the 4th Amendment are insufficient to contend with what technologies are available to police in 2018.”
The Tree of Life
What did the two trees in the Garden of Eden symbolize?
The book of Genesis shows that God put Adam and Eve in the Garden of Eden. They were allowed to eat the fruit of all trees, including the tree of life, but not the tree of the knowledge of good and evil (Genesis 2-3). Eating the fruit of the tree of life represented choosing total reliance on God to show what is good or evil (through His law and Holy Spirit). Eating the fruit of the latter tree represented human beings choosing for themselves what is good and evil, rejecting any direction from God.
The tree of life! What a poetic, almost romantic name for a tree. It fires the imagination and produces wonderful images of energy, health, a bright future and good times.
The tree of life may call to mind man’s quest for the proverbial fountain of youth, with the promise of never-ending joy and happiness.
But the skeptic is likely to exclaim, “There simply is no such thing!”
Looking for the tree of life
Most of us familiar with the term know that the tree of life is mentioned in the Bible in the early chapters of the book of Genesis. We associate it with Adam and Eve and their sin that separated them from God.
We may not be as aware that this tree is mentioned in other Bible passages and that from them we can draw some conclusions about the value of the tree and its properties. Could it be that we would make better life choices if we understood what Adam rejected?
The Garden of Eden
First, let’s look at the earliest account of the tree of life in the Garden of Eden. We read that God planted a garden and filled it with a variety of plants to supply the needs of man. These were “pleasant to the sight and good for food” (Genesis 2:8-9).
Next we read, “The tree of life was also in the midst of the garden, and the tree of the knowledge of good and evil” (verse 9).
The Bible does not say that these were not trees that produced fruit that could be used as food. In fact, we later find Eve reasoning that the tree of the knowledge of good and evil was “good for food, that it was pleasant to the eyes, and a tree desirable to make one wise” (3:6).
We can easily see that these two trees were also fruit trees. Yet they had special importance to our first parents and the future of humanity. In fact, the choice that Adam made to eat of the forbidden fruit has a far-reaching impact on our world today.
The purpose of the two trees
What was the purpose of these two trees? Why are they singled out and why were Adam and Eve given special instructions about their use?
Notice: “And the LORD God commanded the man, saying, ‘Of every tree of the garden you may freely eat but of the tree of the knowledge of good and evil you shall not eat, for in the day that you eat of it you shall surely die” (Genesis 2:16-17).
It is clear that this was the only forbidden tree, or what is commonly called the forbidden fruit. The life-giving tree, by contrast, was free for the taking.
It should be plain, therefore, that the evil was not in the fruit itself, but in the choice to eat it, against God’s clear command: “You shall not eat.”
God had placed Adam and Eve in the Garden of Eden, knowing full well that Satan, the “god of this age” (2 Corinthians 4:4), would attempt to bring them under his influence and control. God wanted them to remain loyal and faithful to Him, in order that He might give them every good thing, including eternal life if they accepted His rule over them. His intent was to bring them into His spiritual family in due time.
He gave them a choice between the tree of life and the tree of the knowledge of good and evil. Can we see that these two trees represented a choice between obeying God’s command and ignoring God’s authority in order to pursue the false goal offered by the devil?
In rejecting God’s instruction and taking of the wrong tree, they surrendered their fate to Satan and took themselves out of God’s protection and provision. In short, they chose Satan’s way of life, which is the opposite of God’s way.
Choosing between life and death
A brief review of the Scriptures shows that “sin is the transgression of the law” (1 John 3:4, King James Version), that “the wages of sin is death” (Romans 6:23) and that “there is a way that seems right to a man, but its end is the way of death” (Proverbs 14:12).
When God commanded Adam not to take of the tree of the knowledge of good and evil, He was showing him what choice he should make. God wanted him to choose life, not death.
Much later, when God brought Israel out of Egypt, He gave them a similar choice: “I have set before you life and death, blessing and cursing therefore choose life, that both you and your descendants may live” (Deuteronomy 30:19).
The tree of death?
Why did God call one of these trees the tree of the knowledge of good and evil, instead of just calling it the tree of death? Clearly, it was the opposite of the tree of life.
Why did God call one of these trees the tree of the knowledge of good and evil, instead of just calling it the tree of death? Clearly, it was the opposite of the tree of life. Still, using this name gives us insight into how God thinks and how He works with mankind. He gives all men the choice of whom to obey, whether Satan or God. When Adam and Eve ate the fruit in defiance of God’s command and warning, they declared themselves independent from God and His law. They proclaimed by their actions that they would decide for themselves what is good and what is evil.
It is evident that the tree did not contain any knowledge at all. Rather, the very act of eating from it was a choice to trust in themselves, though in reality they were enslaving themselves to Satan the devil.
Adam and Eve accepted Satan’s lies and influence. They apparently believed that God was keeping something from them. Yet their action cut them and their descendants off from God, the only source of true knowledge and wisdom. The long-term result was the proliferation of sin and death.
Later in man’s sordid history, wise King Solomon, inspired by the same God, again expressed the choice put before man through all time. He tells us, “Trust in the LORD with all your heart, and lean not on your own understanding in all your ways acknowledge Him, and He shall direct your paths. Do not be wise in your own eyes fear the LORD and depart from evil” (Proverbs 3:5-7).
The key to successful living is to look to our Creator for guidance and strength to live according to His will. The life-giving tree surely must have represented God’s law and His Holy Spirit, which Jesus said “will guide you into all truth” (John 16:13). How many of us today are rejecting God’s wisdom and leaning on our own understanding, as Adam and Eve did?
Two trees revisited
A natural question is, “What would have happened if Adam and Eve had eaten of the other tree?” Again, the Bible gives the answer. Jesus Christ, the Son of God, who came to save man from sin, made some powerful statements about our choices. He said, “It is the Spirit [that] gives life the flesh profits nothing. The words that I speak to you are spirit, and they are life” (John 6:63).
Here Christ’s commands and His Spirit are shown as the source of life. Would we not conclude that they are represented in the tree of life?
Jesus also said, “I am the way, the truth, and the life” (John 14:6). So the tree would have included Christ’s words, which are the truth that leads to life. Had Adam and Eve eaten of the life-giving tree, they would have been granted God’s true knowledge of right and wrong and a reliance on God to teach them how to live.
One of the most profound lessons given by Jesus came during His confrontation with the devil during His temptation in the wilderness. He gives this powerful instruction in defense of His refusal to compromise: “Man shall not live by bread alone, but by every word that proceeds from the mouth of God” (Matthew 4:4).
Tree of life in the future
Will this tree of life, from which man was banished, appear again? The book of Revelation contains prophecies of the end of this age. It points to the presence of a tree of life among the righteous who yield themselves to God’s authority.
“He who has an ear, let him hear what the Spirit says to the churches. To him who overcomes I will give to eat from the tree of life, which is in the midst of the Paradise of God” (Revelation 2:7).
And in the final chapter of the Bible it says, “Blessed are those who do His commandments, that they may have the right to the tree of life, and may enter through the gates into the city” (Revelation 22:14).
The tree of life never died. Humanity was cut off from the tree because they chose the other and could not have both.
The knowledge and Spirit represented by the life-giving tree are available to us today in the words and power of Jesus Christ.
Will you make the same old mistake our ancestors have made down through the centuries and choose the tree of the knowledge of good and evil? Or will you search out the tree of life and eat of it, that you may have eternal life? To do so, you must ask God to reveal His ways to you and commit to following them when He does.
The researchers then compared their results to previous data on carbon storage from monoculture plantations in China. (In the past few decades, China has invested more in afforestation than any other country.)
The comparison showed that introducing additional tree species to monoculture plantations could greatly improve carbon storage, the researchers say in their paper:
“Overall, for each additional tree species, the total [carbon] stock increased by 6.4%.”
Most monoculture plantations in China tend to be made up of eucalyptus, bamboo or Japanese cedar trees. The new study does not explore what types of trees could be used alongside these plants, but does advocate that a mix of plant species is more likely to boost carbon stocks.
There are several reasons why tree species diversity could improve carbon storage, the researchers say. For example, different tree species occupy different heights and spaces in the canopy – meaning a diverse canopy is better able to capture incoming sunlight.
In addition, diverse forests attract a greater range of animals – many of which act as pollinators, aiding plant reproduction. A higher rate of pollination enables a forest to grow faster, and, thus, absorb CO2 more quickly, the researchers say.
Overall, the results suggest that afforestation programmes should “switch” from growing monoculture plantations to more diverse forests, says Schmid:
“Our recommendation is that afforestation programmes should switch from focusing on monocultures to mixtures. Until we know more about the contribution of each particular species, the best approach is simply to plant several species in mixtures. This will help both carbon storage and the preservation of biodiversity.”
The findings are “interesting” and suggest that including more than one tree species in afforestation programmes could boost carbon storage productivity, says Dr Charlotte Wheeler, a forests researcher from the University of Edinburgh, who was not involved in the research. She tells Carbon Brief:
“However, the main problem I see with it is it uses particularly small plots. Previous research shows that, over larger areas of land, the relationship between tree species diversity and productivity sort of levels off. The main reason for that is, over a small area, a diverse mix of trees make better use of resources – but this effect plateaus in larger areas, and other factors become more important.”
Agreeing with Wheeler, Dr Martin Sullivan, a tropical forests researcher from the University of Leeds, who was also not involved in the research, tells Carbon Brief:
“There is some evidence that diversity-carbon relationships are scale-dependent and the plots used here are quite small, so it is possible that relationships will be weaker, or absent, if larger plots were used.
“Also, I think all plots used in this study were recovering from past disturbance [deforestation] and a recent study found that diversity-carbon relationships were positive in disturbed forests, but absent in intact forests.”
Liu, X. et al. (2018) Tree species richness increases ecosystem carbon storage in subtropical forests, Proceedings of the Royal Society of London B, doi/10.1098/rspb.2018.1240