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An hour or so north of New York City, where the skyline is still visible from mountain peaks, bobcats, black bears, rattlesnakes, and turkeys roam. They all thrive in what ecologists call young forest, an ecosystem halfway between grassland and what comes to mind when thinking of a forest.
Unfortunately, their landscape is threatened. And virtually the only way to make room for a young forest is to cut down an old one. This is a tough sell in an eco-conscious world. No one wants to see a single tree cut down, let alone an entire woodlands. Ecologists are frustrated.
“I blame Dr. Seuss for ‘The Lorax,’” said Michael Burger, the managing director of Audubon New York.
But an interactive project that involves counting animals in the young forest has found a way to get through to a skeptical public. Furthermore, it has enlisted said public to help with the work.
The project, Canid Camera, asks online volunteers to participate in a census of the young forest. Biologists and undergraduates from the SUNY College of Environmental Science and Forestry have set up camera traps in Putnam and Dutchess Counties in the Hudson Valley and are relying on the volunteers to label the hundreds of thousands of photos snapped by the rigs to get a sense of what animals are there.
Users log on to the Canid Camera website and browse through each photo and describe what they see: what animal is in the frame, and how many. The process is hypnotic, like scrolling through an Instagram feed of forest creatures going about their daily lives. So far, thousands of volunteers have labeled 200,000 shots, with a new set of 50,000 to be released this month.
The byproduct of this census is to draw volunteers in, which makes the project easier to understand.
Young forests were once plentiful across the Northeast, but now they cover only a fraction of their former range. At least 100 species, including cottontail rabbits, foxes, otters and muskrats, are in decline because of its loss.
The New York State Department of Environmental Conservation has introduced an effort to restore young forest areas, although the goal seems counterintuitive, cutting down forests to make room for new ones.
“We can’t rely on Mother Nature to create young forests like she has for every century before this one,” said Amanda Cheeseman, a postdoctoral associate at SUNY-ESF, where she oversees Canid Camera.
That’s because the department is unlikely to allow the natural methods like fires and flooding, especially in such a populous region as the Hudson Valley. So to create forest diversity, most biologists maintain that clear-cutting acreage is necessary. Yet despite the endorsement of groups like the Audubon Society to do just this, Mr. Burger said that local residents were attending public meetings and pushing back. Some, worried about climate change, don’t want to see the clearances happen since trees are particularly good at storing carbon.
“Their hearts are in the right place,” Mr. Burger said. “But that’s not sustainable forestry.”
Studies find that mixed-aged forests make the environment more resilient against pest outbreaks, weather events, even climate change. That’s in addition to sustaining species that do best in young forest areas.
And that’s where the camera traps come in. Motion-sensing rigs the size of lunchboxes are attached to trees about a foot and a half off the ground. The traps take a snap anytime something moves, like a family of bears clambering through the frame. But a strong breeze may be enough to trigger it.
Once the photos are uploaded, volunteers can click through as many as they care to, choose a label from a premade list of a few dozen options. There is even a field guide with details on how to tell similar species apart, like gray and red squirrels. Individual pictures are screened 15 times before being marked done. For images with conflicting information — three volunteers see a turkey, say, and the rest see a ruffed grouse — Dr. Cheeseman and her interns weigh in.
“There is a learning curve,” said William McShea, an ecologist at the Smithsonian Conservation Biology Institute, where he helps run eMammal, another camera trap project that relies on volunteers. “People get better at it as they go along.”
Those volunteers do get something in return: a sense of being part of a team. They want to see the best images, interact with researchers on tough photos, and learn something. Some projects even include volunteer names on research papers.
“They are doing you a favor,” Mr. McShea said. “You have to be giving them feedback. They want to be part of the project.”
Not everyone interested in the forest health of the Hudson Valley is a New Yorker. Claire Sylvestre, a web developer who lives in Quebec, may be the leading wildlife spotter on Canid Camera. According to the site’s statistics, she has labeled nearly 45,000 images so far. Ms. Sylvestre, 64, came across Canid Camera after working on another project called Exoplanet Explorers. Some of the favorite photos she’s labeled have been of predators, including a bobcat with a gray squirrel in its mouth or a coyote that had killed a fawn.
“Of course, the rarer the animal, the more exciting it is. The holy grail — gray fox — remains elusive,” Ms. Sylvestre said.B:
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（【四】【百】【九】【十】【三】） 【当】【时】，【叶】【文】【玉】【心】【想】，【离】【开】【林】【庭】【风】，【并】【不】【是】【因】【为】【蔡】【文】【川】，【而】【是】【自】【己】【想】【开】【始】【崭】【新】【的】【人】【生】，【过】【得】【有】【尊】【严】，【自】【由】【自】【在】，【独】【立】【体】【面】。 【与】【人】【生】【有】【关】，【与】【爱】【情】【无】【关】。 【到】【了】【傍】【晚】【的】【时】【候】，【继】【父】【王】【叔】【下】【班】【了】，【张】【素】【素】【在】【外】【面】【叫】【叶】【文】【玉】【吃】【饭】。【她】【便】【从】【自】【己】【的】【房】【间】【里】【跑】【出】【来】，【一】【家】【人】【张】【罗】【着】【准】【备】【吃】【饭】。 【看】【到】【继】【父】
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“【呦】，【这】【下】【可】【有】【好】【戏】【可】【以】【看】【了】。”【陆】【飞】【冷】【笑】【一】【声】，【不】【用】【去】【猜】【也】【知】【道】【发】【生】【了】【什】【么】【事】，【恐】【怕】【是】【身】【体】【的】【正】【主】【反】【噬】【来】【寻】【仇】【了】！ “【你】，【你】【不】【是】【已】【经】……”【神】【识】【之】【中】【传】【来】【的】【竟】【然】【是】【吞】【心】【炎】【龙】【的】【声】【音】！【尹】【正】【惊】【骇】【万】【分】。 “【已】【经】【什】【么】，【已】【经】【被】【你】【抹】【杀】【了】【是】【吗】？【你】【未】【免】【有】【些】【太】【小】【瞧】【我】【这】【万】【年】【祖】【龙】【之】【灵】【了】【吧】？” 【原】【来】【吞】【心】【炎】【龙】【意】【识】【并】【未】【被】www.tb883.com【姚】【远】【开】【了】【自】【己】【那】【辆】【面】【包】【车】，【带】【着】【媳】【妇】【抗】【抗】，【还】【给】【张】【代】【表】【带】【了】【不】【少】【的】【土】【特】【产】，【当】【天】【下】【午】【就】【去】【了】【省】【城】。 【他】【们】【到】【了】【张】【代】【表】【家】【里】【的】【时】【候】，【天】【已】【经】【黑】【下】【来】。 【夏】【末】【秋】【初】【的】【天】【气】，【天】【还】【很】【长】。【可】【那】【时】【候】【去】【省】【城】【没】【有】【高】【速】，【省】【道】【也】【是】【坑】【坑】【洼】【洼】，【四】【百】【多】【里】【地】【跑】【了】【六】【个】【小】【时】，【到】【了】【也】【就】【天】【黑】【了】。 【姚】【远】【已】【经】【提】【前】【给】【张】【代】【表】【家】【打】【了】【电】
【所】【以】【只】【过】【了】【半】【个】【时】【辰】，【他】【就】【顺】【利】【闯】【过】【了】【关】【卡】。 【关】【卡】【中】【的】【怪】【物】【消】【散】，【一】【张】【榜】【单】【出】【现】【在】【眼】【前】。 【北】【堂】【弈】【兴】【奋】【地】【往】【上】【看】【去】，【上】【面】【是】【密】【密】【麻】【麻】【的】【姓】【名】，【只】【是】【大】【多】【不】【认】【识】。 【一】【直】【到】【榜】【单】【最】【上】【方】【尽】【头】，【他】【终】【于】【看】【到】【了】【自】【己】【的】【名】【字】。 【然】【而】，【这】【一】【看】【之】【下】，【让】【他】【猛】【然】【瞪】【大】【眼】【睛】，【露】【出】【难】【以】【置】【信】【的】【表】【情】。 【第】【一】【名】：【叶】【良】【辰】
【俞】【承】【麻】【木】【又】【茫】【然】【地】【跟】【着】【护】【士】【进】【了】【手】【术】【室】，【夏】【晴】【天】【欲】【言】【又】【止】，【想】【要】【阻】【止】，【但】【还】【是】【将】【要】【阻】【拦】【的】【话】【咽】【了】【回】【去】。 【他】【是】【韵】【儿】【的】【丈】【夫】，【不】【管】【他】【们】【感】【情】【如】【何】，【总】【归】【还】【是】【她】【最】【亲】【近】【的】【人】。 【夏】【晴】【天】【垂】【下】【眼】【睫】，【有】【些】【疲】【惫】【地】【靠】【在】【了】【墙】【壁】【上】。 【赵】【心】【之】【看】【着】【夏】【晴】【天】【神】【色】【疲】【倦】【的】【样】【子】，【在】【嘴】【边】【的】【安】【慰】【的】【话】【又】【咽】【了】【回】【去】。 “【你】【的】【脸】【怎】【么】