Author Archive
May 22nd, 2015
Via
n early October, after the main rainy season, Ethiopia’s central Rift Valley is a study in green. Fields of wheat and barley lie like shimmering quilts over the highland ridges. Across the valley floor below, beneath low-flying clouds, farmers wade through fields of African cereal, plucking weeds and primping the land for harvest
IIn the paved and wired developed world, it’s hard to imagine a food emergency staying secret for long. But in countries with bad roads, spotty phone service and shaky political regimes, isolated food shortfalls can metastasize into full-blown humanitarian crises before the world notices. That was in many ways the case in Ethiopia in 1984, when the failure of rains in the northern highlands was aggravated by a guerrilla war along what is now the Eritrean border.
Senay, who grew up in Ethiopian farm country, the youngest of 11 children, was then an undergraduate at the country’s leading agricultural college. But the famine had felt remote even to him. The victims were hundreds of miles to the north, and there was little talk of it on campus. Students could eat injera—the sour pancake that is a staple of Ethiopian meals—just once a week, but Senay recalls no other hardships. His parents were similarly spared; the drought had somehow skipped over their rainy plateau.
That you could live in one part of a country and be oblivious to mass starvation in another: Senay would think about that a lot later.
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Yields Of Dreams: A Technology Drive Agriculture Revolution?
April 21st, 2015
Via Foreign Affairs, a detailed look at how technology is transforming agriculture:
Thousands of years ago, agriculture began as a highly site-specific activity. The first farmers were gardeners who nurtured individual plants, and they sought out the microclimates and patches of soil that favored those plants. But as farmers acquired scientific knowledge and mechanical expertise, they enlarged their plots, using standardized approaches—plowing the soil, spreading animal manure as fertilizer, rotating the crops from year to year—to boost crop yields. Over the years, they developed better methods of preparing the soil and protecting plants from insects and, eventually, machines to reduce the labor required. Starting in the nineteenth century, scientists invented chemical pesticides and used newly discovered genetic principles to select for more productive plants. Even though these methods maximized overall productivity, they led some areas within fields to underperform. Nonetheless, yields rose to once-unimaginable levels: for some crops, they increased tenfold from the nineteenth century to the present.
Today, however, the trend toward ever more uniform practices is starting to reverse, thanks to what is known as “precision agriculture.” Taking advantage of information technology, farmers can now collect precise data about their fields and use that knowledge to customize how they cultivate each square foot.
One effect is on yields: precision agriculture allows farmers to extract as much value as possible from every seed. That should help feed a global population that the UN projects will reach 9.6 billion by 2050. Precision agriculture also holds the promise of minimizing the environmental impact of farming, since it reduces waste and uses less energy. And its effects extend well beyond the production of annual crops such as wheat and corn, with the potential to revolutionize the way humans monitor and manage vineyards, orchards, livestock, and forests. Someday, it could even allow farmers to depend on robots to evaluate, fertilize, and water each individual plant—thus eliminating the drudgery that has characterized agriculture since its invention.
ACRE BY ACRE
Someday, farms might be filled with hundreds of small autonomous robots.
The U.S. government laid the original foundations for precision agriculture in 1983, when it announced the opening up of the Global Positioning System (GPS), a satellite-based navigation program developed by the U.S. military, for civilian use. Soon after, companies began developing what is known as “variable rate technology,” which allows farmers to apply fertilizers at different rates throughout a field. After measuring and mapping such characteristics as acidity level and phosphorous and potassium content, farmers match the quantity of fertilizer to the need. For the most part, even today, fields are tested manually, with individual farmers or employees collecting samples at predetermined points, packing the samples into bags, and sending them to a lab for analysis. Then, an agronomist creates a corresponding map of recommended fertilizers for each area designed to optimize production. After that, a GPS-linked fertilizer spreader applies the selected amount of nutrients in each location.
Over 60 percent of U.S. agricultural-input dealers offer some kind of variable-rate-technology services, but data from the U.S. Department of Agriculture indicate that in spite of years of subsidies and educational efforts, less than 20 percent of corn acreage is managed using the technology. At the moment, a key constraint is economic. Because manual soil testing is expensive, the farmers and agribusinesses that do use variable rate technology tend to employ sparse sampling strategies. Most farmers in the United States, for example, collect one sample for every two and a half acres; in Brazil, the figure is often just one sample for every 12 and a half acres. The problem, however, is that soil can often vary greatly within a single acre, and agricultural scientists agree that several tests per acre are often required to capture the differences. In other words, because of the high cost of gathering soil information, farmers are leaving productivity gains on the table in some areas of the field and overapplying fertilizer and other inputs in others.
Researchers are beginning to tackle the problem, developing cheap sensors that could allow farmers to increase their sampling density. For example, one new acidity sensor plunges an electrode into the soil every few feet to take a reading and records the GPS coordinates; manually sampling on that scale would be far too costly. Such sensors have not yet arrived at most farms, however. Some haven’t proved reliable enough, breaking after a few acres of use, whereas others aren’t accurate enough. But several research groups around the world are working on developing sturdier ones.
More practical are sensors that look at the color of plants to determine their nutritional needs. Plants with too little nitrogen, for example, tend to turn pale green or yellow, whereas those with enough appear dark green. Several U.S. and European companies have developed sensors that detect greenness, generating measurements that can be used to generate a map recommending various amounts of nitrogen to be applied later. Alternatively, the measurements can be linked directly to the nitrogen applicator to change the application rate on the go. A tractor may have a sensor mounted on the front and an applicator on the back; by the time the applicator reaches a point that the sensor has just passed, an algorithm has converted the readings into settings for how much fertilizer to apply. Because research in this area has focused mainly on small grains, such as wheat, barley, rye, and oats, the technology is mostly limited to the parts of the United States and Europe that grow those crops. According to a 2013 survey by Purdue University, only seven percent of agricultural-input dealers offer plant-color sensors. Given the number of start-ups in this area, however, it is clear that many investors see the technology as a potential gold mine.
FIELDS AND YIELDS
The government’s GPS decision also enabled another revolutionary technology to emerge: yield monitoring. Most harvesters in the United States and Europe are outfitted with special sensors that measure the flow rate of grain coming in. An algorithm specific to the crop then converts the resulting data into a commonly used volume or weight, such as bushels per acre or kilograms per hectare. That information is then turned into colorful maps that show the variation within fields.
These maps have become a staple of farming magazines and trade shows, and for good reason: they have given farmers unprecedented insight into the effects of various production techniques, weather conditions, and soil types. Such a map can help a farmer arrive at yield numbers for the purpose of insurance or government programs, measure the results of experiments that test the qualities of genetically modified crops or the effectiveness of various cultivation practices, and reveal which parts of a field aren’t living up to their potential. In the eastern United States, it was only through yield monitoring that farmers were able to convince landlords that flood-related crop losses were not limited to completely submerged parts of the field; they also extended to a ring around those spots. In response, farmers installed more subsurface drainage systems. In Argentina, the technology has taken off because most managers of large farms there, unlike their U.S. counterparts, rarely operate vehicles themselves (a consequence of the peculiar history of landownership there). For them, yield maps offered on-the-ground insight into productivity they couldn’t otherwise get.
When it comes to the quality of the data, however, yield-monitoring technology still has a long way to go. In most cases, the algorithms that convert data about flow into volume or weight measurements must be calibrated annually for each crop and farm, and many farmers don’t bother to do so. The data can also be affected by how fast a harvester is driven and other idiosyncrasies. And although research studies can rigorously analyze data from yield monitoring, farms and agribusinesses typically lack the necessary statistical skills and software. The next step in yield monitoring is for agribusinesses to adopt the statistical techniques now used mainly by researchers; since their findings would be spread across millions of acres, they should be able to justify the cost.
PLOW BY WIRE
The most common use of precision-agriculture technology is for guiding tractors with GPS. Manually steering farm equipment requires skilled operators and is a tiring endeavor. And even the best drivers often overlap their passes by as much as ten percent to avoid skipping parts of the ground. The late 1990s saw the introduction of LED light bars, each a series of LED lights in a foot-long plastic case that is mounted in front of the operator of a tractor, harvester, or other vehicle. If the lights in the center are lit up, then the equipment is on track. If those on the left or the right are illuminated, then the driver needs to correct the steering.
Increasingly, farmers are taking this technology to its next logical step, replacing the light bars with automatic guidance systems that link GPS data directly to a vehicle’s steering mechanism. Although an operator still needs to sit on the equipment, for the most part, it can be driven hands-free. The technology first gained widespread use in the 1990s in Australia, where clay-rich soils—plus a lack of freezing and thawing—make fields particularly vulnerable to compaction from wheeled vehicles. Australian farms used GPS automated guidance to concentrate equipment traffic on narrow paths, preventing the rest of the soil from getting compacted. Today, about 40 percent of fertilizer and other agricultural chemicals are applied with automated guidance in the United States.
Such systems have led to numerous spinoffs. One category is mechanisms that track the path of a tractor and automatically shut off its seed-planting and chemical-spraying functions when it passes over parts of the field that have already been covered or are environmentally sensitive. The technology is especially useful for irregularly shaped fields, which are vulnerable to overplanting and overspraying.
Geospatial data aren’t just for plowing straight lines, however. For decades, NASA and some of its foreign counterparts have encouraged farmers to use their satellite imagery. Along with aerial photography, these images form the basis for “geographic information systems,” which enable farmers to store and analyze spatial data. The technology has proved particularly useful in areas where multiyear data are available, since it allows growers to divide large fields into zones that receive different seeds, fertilizers, and herbicides.
Some managers of farms are even using GPS to keep an eye on their employees in the field, especially in the former Soviet Union and particularly in Ukraine. Since the biggest farms there—many of which cover over 100,000 acres—tend to rely on hired staff and not owner-operators, farm managers like to track all field operations in real time. If a tractor stops for more than a few minutes, for example, the head office will notice and can call the driver to inquire about the problem. The tracking technology also allows managers to crack down on employees who use company machines on their own farms.
YIELD OF DREAMS
Precision agriculture has already turned one of the oldest sectors into one of the most high-tech, but the best is yet to come. The next step likely involves “big data.” Farmers and agribusinesses are increasingly considering how to best take advantage of their treasure troves of data to boost profits and make agriculture more sustainable. In 2013, for example, the agriculture giant Monsanto acquired the Climate Corporation, a start-up founded by two Google alumni to use weather and soil data to create insurance plans for farmers and generate recommendations for which crop varietals are best suited to a particular plot of land. Another low-hanging fruit for big data is research on how to use equipment. For example, it’s not clear how fast a tractor should be driven when planting corn: too slow makes for an inefficient process, but too fast results in uneven planting, which hurts yields. After collecting data on the tractor’s speed, the eventual yield of the crop, and other factors, however, one could determine the optimal speed for planting.
In order to harness big data’s power, companies will probably have to pool information across farms. In the United States and Europe, individual farms are too small to generate a meaningful quantity of data, and even the very large farms in Latin America and the former Soviet Union would benefit from combining data with their neighbors. The problem, at the moment, is that farmers have little incentive to collect quality data. In the United States, some start-ups have tried to pay farmers for data, without much success. So far, it is the agricultural-input suppliers and agricultural cooperatives that have been able to collect the most data. But even their data sets are relatively small.
Some of that big data may come from drones. With the United States largely out of Afghanistan and Iraq, some suppliers of military hardware have turned their attention to the agricultural market. The move might be smart: small, unmanned aircraft can capture regular images of crops to guide irrigation, pesticide application, and harvesting. And unlike satellites, drones are largely unaffected by cloud cover. Given the operating expense and expertise required, drones will most likely be used commercially at first only for high-value crops, such as wine grapes. And in the United States, the Federal Aviation Administration will first have to open up the skies to commercial drones.
The technology that would truly transform agriculture as we know it is robotics. The rapid adoption of GPS guidance has opened the door to more autonomous farm equipment, and most major manufacturers have already tested driverless versions of their tractors. Once the driver is removed from the picture, the design criteria for a piece of equipment change radically: it can become far smaller. It’s possible to imagine farms someday filled with hundreds of small autonomous robots, doing everything from planting to harvesting. Robots could scout fields continuously and identify pest and disease problems at the earliest possible stages. They could apply pesticides in tiny doses, targeting individual insects or diseased plants. They could efficiently manage small and oddly shaped fields, such as those common in the eastern United States, which are hard to farm profitably with conventional equipment driven by humans. In the United States, by reducing the need for Mexican laborers, robots might even affect immigration policy.
When it comes to emerging technologies, it is a fool’s errand to pick winners. But the history of farming in the twentieth century offers some clues to its future. Almost all the agricultural technologies that were widely adopted in the twentieth century were characterized by what economists call “embodied knowledge,” meaning that the scientific advancements were contained within them. Farmers didn’t have to know how pesticides killed insects or how a gasoline tractor worked; they just needed to know how to spray the chemical or drive the vehicle.
Likewise, the tools of precision agriculture will gain widespread use only once they are sold in easy-to-use forms. That’s why GPS guidance has become so widespread: farmers don’t need to understand it to use it. And so variable rate technology for fertilizer, to take one example, will take off the day a farmer can trigger it with the mere push of a button. Eventually, precision agriculture could take humans out of the loop entirely. Once that happens, the world won’t just see huge gains in productivity. It will see a fundamental shift in the history of agriculture: farming without farmers.
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The Connected Forest: How Your Used Mobile Phone Can Help Save Rainforests
March 16th, 2015
Via Sustaining People, a look at how recycled cell phones can be used as in an innovative network of sensors:
In 2012, a small group in Borneo and now in the US have found a way to use recycled mobile phones to stop illegal deforestation around the world.
Deforestation accounts for more greenhouse gas emissions than all of our planes, trains and automobiles (as well as ships – don’t forget the ships) combined, and around 90% of this deforestation is caused by illegal logging. A recent TED talk from environmental technologist and CEO of Rainforest Connection Topher White shows us how recycling our old phones is helping to stop this at a micro level.
According to White, rainforests often have surprisingly strong phone reception, even out in the middle of nowhere. Essentially White put together a head of old phones and tuned them to hear certain types of noises (like the whine of a chainsaw). The device then alerts those on the ground via email, enabling them to keep track of an entire forest, and arrive in time to interrupt and stop illegal loggers.
White’s amazing creation and the story behind it is fascinating; what is more fascinating is how White describes the reactions to his recycled tech, and the real effect it is now having around the world.
Rainforest Connection built a strong following on Kickstarter, surpassing their target fund by over 60% mid last year. They are going from strength to strength, and they are now installing their technology in the rainforests, of Indonesia, the Amazon and Africa.
This story teaches us that the solutions to our problems (and to sustainability issues) are all around us; it just takes a creative mind and real life experiences out in the world to shape and change our world.
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Google-Powered Maps Fight Deforestation
March 11th, 2015
Via the Guardian, another look at how Global Forest Watch, a mapping platform powered by Google, is using technology to keep an eye on the world’s forests:
The forestry website Mongabay recently reported that United Cacao, a London-listed company that promises to produce ethical, sustainable chocolate, had “quietly cut down more than 2,000 hectares of primary, closed-canopy rainforest” in the Peruvian Amazon. The company claimed that the land had been previously cleared, but satellite images showed otherwise.
The satellite images came from an online platform called Global Forest Watch, which provides reliable and up-to-date data on forests worldwide, along with the ability to track changes to forest cover over time.
Launched a year ago by the World Resources Institute (WRI), the platform has brought an unprecedented degree of transparency to the problem of deforestation, pointing to ways in which big data, cloud computing and crowdsourcing can help attack other tough sustainability problems.
Before Global Forest Watch came along, actionable information about forest trends was scarce. “In most places, we knew very little about what was happening to forests,” said Nigel Sizer, the global director of the forests program at WRI. “By the time you published a report, the basic data on forest cover and concessions was going to be years out of date.”
Several technology revolutions have changed that. Cheap storage of data, powerful cloud computing, internet connectivity in remote places and free access to US government satellite images have all made Global Forest Watch possible. None were widely available even a decade ago.
Governments and NGOs are both using Global Forest Watch, as are companies like Unilever, Asia Pulp, and Paper and Wilmar, all of which have made commitments to stop deforestation.
“Global Forest Watch revolutionizes the way we are able to monitor and engage with our suppliers,” says Alexandra Experton, who oversees Cargill’s supply chain sustainability from her base in Singapore. Cargill has set a goal of arriving at 100% sustainable palm oil in the next few years.Glenn Hurowitz, the chair of Forest Heroes and a veteran forests campaigner, says Global Forest Watch is “our go-to source as we make efforts to police deforestation”, particularly when it is backed up by on-the-ground observations from local groups.
Glenn Hurowitz, the chair of Forest Heroes and a veteran forests campaigner, says Global Forest Watch is “our go-to source as we make efforts to police deforestation”, particularly when it is backed up by on-the-ground observations from local groups.
An ambitious undertaking, Global Forest Watch brought together a broad coalition of NGO, corporate and government partners. Working closely with WRI are more than 60 partners, including Google (which supported the software development and provides computing power), ESRI (a privately-held mapping company), the University of Maryland’s department of geographical sciences (home to mapping and land-use expert Matt Hansen), Brazil-based Imazon, the Center for Global Development (a Washington DC-based think tank), and the UN Environment Programme. The multimillion dollar program is funded by governments like Norway, the US and UK.
Google provides computing power, storage and software engineering, according to Rebecca Moore, the engineering manager for Google Earth Engine. Moore and other Google engineers, in a collaboration led by Maryland’s Matt Hansen, built the world’s first high-resolution map of global forests, which was published in the journal Science in 2013 and became part of Global Forest Watch.
Global Forest Watch updates its data and images frequently – daily in the case of fire alerts; every few weeks otherwise. Satellite images track tree cover loss or gain at a 30-metre resolution for the entire world, and to a finer resolution in key spots.
Since the launch, governments, companies, nonprofits and individuals have layered on additional, valuable information. The governments of Indonesia and some central African nations, for example, have made data about land ownership and regulations governing forest use available. (Here is a detailed profile of forestry in Indonesia.) The platform also allows users to upload and share information. For example, local NGOs have recently posted stories about threats to caribou habitat in Canada and forests being harvested for charcoal in Cambodia.
New features are frequently added to the platform. Software developers are building applications with a specialized focus, notably Global Forest Watch Commodities, which includes data about commodity production and processing locations. There are also annual and monthly tree cover loss alerts, and active forest and peatland fires.
“This allows you to analyze what’s happening at the end of a supply chain,” Sizer explains. “For now, it focuses on palm oil because that’s the highest priority of the industry.”
WRI and its partners also are working to deliver sharper, more timely imagesand instant alerts so those who want to protect forests can respond in a timely way to threats. “We’re going to be continually refining the freshness of the information, the accuracy, the resolution and the ease of getting into people’s hands,” Google’s Moore says.
Users are eager to see the platform evolve. Cargill hopes to support the addition of social indicators to complement the environmental data on the platform. Gemma Tillack, a forest campaigner with the Rainforest Action Network, which is now using Global Forest Watch to identify “bad actors” in Sumatra, says she’d like all the major palm oil companies to provide data on their landholdings and mills, and require the same from their suppliers.
Meanwhile, it’s easy to imagine how the technology behind Global Forest Watch could help deal with other sustainability issues. Already, several NGOs working in the Democratic Republic of the Congo are using satellite imagine and predictive analytics to assist park rangers who are trying to halt an unprecedented slaughter of elephants for ivory in Garamba National Park. Oceans could be monitored to track illegal fishing, or a map or database of the world’s factories could allow laborers to provide feedback on working conditions.
Information, as they say, is power. Perhaps this mapping project will help NGOs figure out how to wield more of that power in favor of the environment.
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Drones: Latest Tool In Conservation Science
March 9th, 2015
Via the Sacramento Bee, a look at how drones are revolutionizing conservation:
When the rain finally came to Sacramento in early February, Nature Conservancy scientist Chris McColl needed to quickly assess whether water had overflowed the banks of the Cosumnes River and filled a floodplain the organization is trying to restore.
Planes are expensive, and it takes hours to hire one and get it in the air. So McColl deployed a drone instead.
Cheap, fast and flexible, drones are quickly becoming a favored tool for organizations conducting scientific research. The Nature Conservancy has four drones operating from San Diego to the northern Sierra. The remote aircraft count sandhill cranes, survey flood restoration projects and perform other tasks.
McColl said the conservancy would double its California drone arsenal within the next year.
At the Cosumnes River Preserve south of Sacramento, where a levee was recently removed to allow flooding to resume its natural, historic pattern, scientists use a drone to see if their efforts are paying off. They previously would have had to eyeball the flooding from the ground – not the most accurate way to measure it – or hire an airplane to fly over.
“If we had to hire a pilot, the time flexibility might not be there,” McColl said. “The drones allow us to be really responsive after storm events because we need to be there within hours to catch certain flood levels.”
At the Cosumnes River Preserve, the conservancy is using a Phantom Vision 2 drone that sports four propellers and a GoPro camera attached to a gimbal.
Total cost: $1,400. The costs of repeat flights are minimal: manpower and battery juice. In contrast, hiring a pilot to fly over the site can run anywhere from $1,500 to $3,000 per trip.
The drone has the potential of paying for itself in just one trip. It also gives the conservancy complete control over the images captured. The only limitations are short battery times and noise levels.
Although small, the Phantom Vision 2 emits a high-pitch whirring sound that scares off sandhill cranes, McColl said. Quieter drones are available in the form of a fixed-wing model that is quiet and has not scared birds, but those drones cost $10,000 to $30,000 each.
Another scientist who has been using drones for research is Christopher Zappa, ocean and climate researcher at the Lamont-Doherty Earth Observatory at Columbia University.
Zappa has deployed drones since 2011 to test new instruments that measure ocean temperature and ocean waves. He also uses drones to drop off micro-buoys that can measure water temperature and salinity.
“We’re looking at the marginal ice zone, where the ocean meets the edge of the ice, seeing how fast and how slow the melting is occurring,” Zappa said. “Monitoring ice melt in the Arctic, drones will fly to places that icebreakers and manned aircraft don’t dare venture.”
Drones are not limited to the air. Recently, the Woods Hole Oceanographic Institution started monitoring polar ice with underwater drones. A similar drone is being used to observe the deep-water habits of great white sharks.
The technology is still in its infancy, as are the laws that regulate its use. Last month, the Federal Aviation Administration issued a ruling on allowing commercial use of drones, under strict guidelines.
The ruling, which needs final approval, allows drones to be flown for recreational purposes. For commercial use, a pilot’s license is required.
The new FAA rules allow the operating of drones under 55 pounds. The drones must be flown below 500 feet, kept 5 miles from an airport, and are not to be flown directly overhead of people. The drone operator must also maintain a constant visual line of sight with the drone.
With the Cosumnes flyovers, no pilot’s license was necessary since the conservancy was flying over its own land.
The river and adjacent fields are a living floodplain laboratory unusual in California, since the Cosumnes is one of the last rivers without a dam.
“The river is pretty dramatic because it’s a seasonal river that goes from completely dry to flooded in winter,” said Judah Grossman, project manager with the Nature Conservancy. “This is unique to the Cosumnes.”
“We’re hoping that allowing the river to overtop more frequently into a larger area will let floodwater percolate down and recharge the aquifer,” Grossman said. “And, hopefully, this will bring groundwater levels up again.”
Groundwater recharge is a big issue for a thirsty state in a multiyear drought. Last month, the U.S. Geological Survey reported that California is depleting its groundwater faster than any other state in the country.
The drones capture time-lapse photos and video that will help show whether the conservancy’s efforts are succeeding.
Read more here: http://www.sacbee.com/news/local/environment/article12964940.html#storylink=cpy
Read more here: http://www.sacbee.com/news/local/environment/article12964940.html#storylink=cpy
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A Virtual Dragnet: Using Satellites To Combat Illegal Overfishing
January 31st, 2015
Via The Economist, a report on a new satellite-based surveillance system keeping a close eye on illegal overfishing:
THE Yongding is something of a ghost ship, disappearing and changing her name many times, along with her flag of registration. The 62-metre vessel was last spotted on January 13th in a marine conservation area in the Southern Ocean, blatantly hauling up outlawed gill nets laden with toothfish, a catch so prized that it is known as “white gold”. Interpol is seeking information about who operates the ship and profits from its activities, as well as those of two accompanying vessels, Kunlun (pictured above, landing a toothfish) and Songhua. In the vastness of the open ocean, policing vessels like Yongding, Kunlun and Songhua is hard. But it is about to get easier—for with just a few mouse clicks a satellite-based monitoring system, unveiled this week, will be able to compile a dossier of evidence about even the most clandestine fishing operations.
The scale of illegal and unreported fishing is, for obvious reasons, difficult to estimate. The Pew Charitable Trusts, an American research group, has nevertheless had a stab at it. It reckons that around one fish in five sold in restaurants or shops has been caught outside the law. That may amount to 26m tonnes of them every year, worth more than $23 billion. This illegal trade, though not the only cause of overfishing, is an important one. Stamping it out would help those countries whose resources are being stolen. It would also help to conserve fish stocks, some of which are threatened with extinction. It might even (if the more apocalyptic claims of some ecologists are well founded) slow down the journey towards a wider extinction crisis in the oceans.
The new monitoring system has been developed by the Satellite Applications Catapult, a British government-backed innovation centre based at Harwell, near Oxford, in collaboration with Pew. In essence, it is a big-data project, pulling together and cross-checking information on tens of thousands of fishing boats operating around the world. At its heart is what its developers call a virtual watch room, which resembles the control centre for a space mission. A giant video wall displays a map of the world, showing clusters of lighted dots, each representing a fishing boat.The data used to draw this map come from various sources, the most important of which are ships’ automatic identification systems (AIS). These are like the transponders carried by aircraft. They broadcast a vessel’s identity, position and other information to nearby ships and coastal stations, and also to satellites. An AIS is mandatory for all commercial vessels, fishing boats included, with a gross tonnage of more than 300. Such boats are also required, in many cases, to carry a second device, known as a VMS (vessel monitoring system). This transmits similar data directly to the authorities who control the waters in which the vessel is fishing, and carrying it is a condition of a boat’s licence to fish there. Enforcement of the AIS regime is patchy, and captains do sometimes have what they feel is a legitimate reason for turning it off, in order not to alert other boats in the area to profitable shoals. But the VMS transmits only to officialdom, so there can be no excuse for disabling it. Switching off either system will alert the watch room to potential shenanigans.
The watch room first filters vessels it believes are fishing from others that are not. It does this by looking at, for example, which boats are in areas where fish congregate. It then tracks these boats using a series of algorithms that trigger an alert if, say, a vessel enters a marine conservation area and slows to fishing speed, or goes “dark” by turning off its identification systems. Operators can then zoom in on the vessel and request further information to find out what is going on. Satellites armed with synthetic-aperture radar can detect a vessel’s position regardless of weather conditions. This means that even if a ship has gone dark, its fishing pattern can be logged. Zigzagging, for example, suggests it is long-lining for tuna. When the weather is set fair, this radar information can be supplemented by high-resolution satellite photographs. Such images mean, for instance, that what purports to be a merchant ship can be fingered as a transshipment vessel by watching fishing boats transfer their illicit catch to it.
As powerful as the watch room is, though, its success will depend on governments, fishing authorities and industry adopting the technology and working together, says Commander Tony Long, a 27-year veteran of the Royal Navy who is the director of Pew’s illegal-fishing project. Those authorities need to make sure AIS and VMS systems are not just fitted, but are used correctly and not tampered with. This should get easier as the cost of the technology falls.
Enforcing the use of an identification number that stays with a ship throughout its life, even if it changes hands or country of registration, is also necessary. An exemption for fishing boats ended in 2013, but the numbering is still not universally applied. Signatories to a treaty agreed in 2009, to make ports exert stricter controls on foreign-flagged fishing vessels, also need to act. Fishermen seek out ports with lax regulations to land illegal catches.
Preserving Nature’s bounty
One of the most promising ideas for using the watch room is that shops could employ its findings to protect their supply chains, and thus their reputations for not handling what are, in effect, stolen goods. Governments sometimes have reason to drag their feet about enforcing fisheries rules. Supermarkets, though, will generally want to be seen as playing by them. The watch room’s developers say they are already in discussions with a large European supermarket group to do just this.
The watch room will also allow the effective monitoring of marine reserves around small island states that do not have the resources to do it for themselves. The first test of this approach could be to regulate a reserve of 836,000 square kilometres around the Pitcairn Islands group, a British territory in the middle of the South Pacific with only a few dozen inhabitants.
The Pitcairn reserve, which may be set up later this year, will be one of the world’s largest marine sanctuaries. By proving that the watch room can keep an eye on such a remote site, its developers hope other places with similar requirements will be encouraged to get involved.
The watch-room system is, moreover, capable of enlargement as new information sources are developed. One such may be nanosats. These are satellites, a few centimetres across, that can be launched in swarms to increase the number of electronic eyes in the sky while simultaneously reducing costs. Closer to the surface, unmanned drones can do the same. The watch room, then, is a work in progress. But in the game of cat and mouse that enforcing fishing regulations has become, it will give the cat an important advantage.
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