(Birds chirping)
(鳥叫聲)
What you're hearing is the sound of a native forest in Southern Europe. The calm, tranquil feeling we all get is not a coincidence. We all evolved in ecosystems like this, where the sounds of birds and insects indicated the possibility of food, medicines and all the resources we need for survival. Ecosystems and their biodiversity still hold the key to life on this planet.
各位聽到的是南歐 一座原生森林的聲音。 我們所感受到的平靜、安詳 並不是巧合。 我們都在這樣的生態系統中演化; 鳥類和昆蟲的叫聲 代表那裡可能有食物、藥物, 及各種我們生存所需要的資源。 生態系統及其生物多樣性 仍然是地球上生命存在的關鍵。
I'm obsessed with this biodiversity, the magic of the infinite network, where every species depends on others to survive. For most of my career, I focused on just one of those fascinating connections between insects and fungi in the soil. I longed to understand the scale of these networks and to understand how they might help us with one of the greatest challenges facing humanity: our rapidly warming planet.
生物多樣性讓我深深著迷, 這無限大的網路有種魔力, 當中的每個物種 都要仰賴其他物種才能生存。 我的職涯大多都專注在 昆蟲及土壤裡的真菌類 之間神奇的連結。 我渴望能了解這些網路的規模 及它們能如何幫助我們 迎接人類所面臨的最大挑戰之一: 地球快速暖化。
The problem is clear. We know we need to reduce our emissions and draw the existing carbon out of the atmosphere, stop the damage and start the repair. And this is where forests can help. Like all plants, trees capture carbon from the atmosphere, and they use it for growth. And some of that carbon enters the soil, where it can stay for hundreds or even thousands of years. If we could stop the losses of forests around the world, we could directly help to cut our annual emissions. And if we could start to tip the balance in the other direction, we might even help the repair process. But if people were really going to invest their valuable time and energy in a solution like this, we needed to comprehend the size of this opportunity and understand the impacts that we can have as individuals. But comprehending something of this scale was a completely new challenge for me and my colleagues.
問題很清楚。 我們知道我們得減少排放, 並將大氣中既有的碳移除; 停止破壞、開始修復。 這就是森林能幫上忙的地方。 和所有的植物一樣, 樹木能從大氣中捕集碳,用於生長。 而部分的碳會進入土壤, 並在那裡待上數百甚至數千年。 如果我們能阻止 世界各地的森林消失, 我們就能直接協助降低年排放量。 如果我們能開始扭轉情勢, 我們甚至可以 在修復的過程中有所幫助。 但如果真的要大家 把可貴的時間、心力 投入在像這樣的解決方案中, 我們就必須理解這個機會有多大, 並了解我們每一個人 能夠造成的影響。 但對我及我的同事來說, 理解這麼大規模的東西 完全是個全新的挑戰。
For this, we needed the knowledge of experts all over the world. So we began building a new network. The more people we contacted, the more data we received, and the more clearly patterns began to emerge. With data from over 1.2 million forests, we were able to build new machine learning models to predict forest structure around the world. For the first time, we could see that our earth is home to just over three trillion trees, almost half of what existed before human civilization. We could see where the different species are distributed and how carbon is stored in this massive system. But this approach could also show us something more transformative. Using the same models, we could begin to see where trees might naturally grow under the existing climate. And this suggested that outside of urban and agricultural areas, there's 0.9 billion hectares where trees would naturally exist. And this is room for just over one trillion new trees.
為達此目的,我們需要 全世界專家的知識。 所以我們開始建造一個新網路。 我們接觸越多人,獲得的數據就越多, 模式就會更清楚地浮現。 有了來自一百二十萬座森林的數據, 我們得以建立新的機器學習模型, 來預測世界各地的森林結構。 我們頭一次看到了 地球上有超過三兆棵樹木, 跟人類文明出現之前相比, 接近其半數。 我們可以看到不同樹種的分佈, 以及碳如何在這個巨大的系統中貯存。 這個方法還能讓我們看到 自然的變化怎麼發生。 用同樣的模型,我們能開始看到 在既有的氣候下, 樹木可以在哪裡自然生長。 結果發現,在都市及農業地區之外, 樹木可以自然存在的區域 有九億公頃的面積, 足夠讓一兆棵樹生長。
We estimated that if we could protect these areas in the long term, then the soils and vegetation might capture up to 30 percent of the excess carbon in the atmosphere, capturing decades of human emissions. We now have a wealth of ongoing research to refine these initial estimates. But the scale of this potential suggests that along with all the other benefits these ecosystems provide, they might also represent a valuable role in our fight against climate change.
我們估計,如果能長期保護這些區域, 大氣多餘的碳中高達 30% 可能會被土壤和植披捕集。 這等於人類數十年的排放量。 現在有許多研究 正在校準這些初始估計值。 但這潛力的規模之大, 代表著這些生態系統 除了能提供各種益處之外, 它們可能在我們 對抗氣候變遷的奮戰中 也扮演一個重要的角色。
When our research was accepted to be published in the journal Science, nothing could have prepared us for the media explosion that followed. Suddenly, it seemed like the whole world was talking about the potential of trees. Under the umbrella of the UN Decade on Ecosystem Restoration, the World Economic Forum launched their Trillion Trees Campaign to go alongside similar efforts from the WWF and United Nations. Suddenly, governments and companies all around the world were pledging their commitment to the restoration of earth's forests. And with the job creation that would result, the idea of a global restoration movement was becoming a reality.
當《科學》期刊刊載我們的研究時, 我們完全沒料到後續 會在媒體上爆紅。 突然,好像全世界 都在談樹木的潛力。 在「聯合國生態系復原 十年計畫」的推動下, 世界經濟論壇推出了「兆樹計畫」, 世界自然基金會及聯合國 也都推出了類似方案。 突然,世界各地的政府和企業 都許下承諾要恢復地球的森林。 因為也能帶來大量的工作機會, 全球森林復原運動的想法就成真了。
But in the excitement of it all, and with the chance to make that positive impact I'd always dreamed of, I made some naive and stupid mistakes in communication that threatened the entire message. The simplicity of our message was its strength, but it came at the expense of nuance that is so important. And as the headlines began to emerge, I desperately just wanted to pull them back in. Because to some, it seemed like we were proposing restoration as the single solution to climate change. And this is the opposite of what this movement needs. When viewed through this lens, restoration just seems like an easy way out, a chance for us to "offset our emissions" by planting a few trees and ignore the very real and urgent challenges of cutting emissions and protecting the ecosystems that we currently have.
我有機會帶來夢寐以求的正面影響, 但卻在興奮之際, 犯下了溝通上天真又愚蠢的錯誤, 進而威脅到我們想傳達的訊息。 我們的訊息很簡單,這是個優點, 但代價就是犧牲了非常重要的細節。 隨著新聞標題逐一出現, 我恨不得將這訊息收回來。 因為在有些人耳裡,我們似乎是在說 只要復原森林 就能解決氣候變遷的問題。 這完全不是這個運動所需要的。 從這個角度來看, 復原森林似乎是個簡單的解套方式, 好像種一些樹,就有機會 「抵消我們的排放」, 就可以忽視非常真實且迫切的挑戰: 減少排放以及保護目前的生態系統。
Restoration is not a silver bullet. There is no silver bullet. It is just one of a huge portfolio of solutions that we so desperately need. And this view of trees as an easy way out is such a tempting perspective, but it is a real threat to the climate change movement and to the ecosystems that still remain.
復原森林並非萬靈丹。 萬靈丹並不存在。 這只是我們迫切需要的 多種解決方案中的其中一種。 將種樹視為唯一的方式 是種非常誘人的觀點, 但這麼做反而會威脅到氣候變遷運動 以及目前尚存的生態系統。
(Faint sounds)
(微弱的聲音)
This is also the sound of trees. It's a eucalyptus plantation that exists just a couple of miles away from where we began. Notice how there were no sounds of birds or insects. The songs of biodiversity are gone. That's because what you're hearing is not an ecosystem. It's a monoculture of one single tree species planted for rapid tree growth. Along with the biodiversity that used to live here, this local community has now lost the benefits those ecosystems provided, like clean water, soil fertility, and most urgently, protection from the intense fires that now threaten the region every summer.
這也是樹木的聲音。 這是個人造桉樹林,距離一開始 提到的那座森林只有幾哩路。 注到聽,沒有蟲鳴鳥叫。 生物多樣性的歌聲不見了。 那是因為各位聽到的不是生態系統。 它是單一樹種的栽培, 因為桉樹成長快速。 這個地方已經失去 曾經擁有的生物多樣性, 當地居民也失去了 那些生態系統所提供的益處, 比如乾淨的水、土壤肥沃度, 還有最迫切的, 防止現在每年夏天 都會威脅該地區的烈火。
The UN suggests that almost half of reforested areas around the world are monocultures just like this, planted for rapid timber production or carbon capture. Just like a farm, these plantations may be valuable for timber, but they are not the restoration of nature. And monocultures are just one of the many ways we can damage ecosystems when we offset our emissions without considering the local ecology or the people that depend on it.
聯合國指出, 世界各地重新造林的區域, 近半數都是像這樣的單一樹種栽培, 目的在快速生產木材或碳捕集。 就像農場一樣, 這些人造林可能有生產木材的價值, 但它們無法找回大自然。 而單一栽培是一種 傷害生態系統的方式。 這種方式抵消了我們的排放, 但未考量當地生態, 也不顧仰賴當地生態的人。
Following these mistakes, a second wave of articles flooded in, warning of the risks of restoration done wrong. And this criticism was so painful because it was entirely correct. But most of all, I was terrified that we would squander this incredible opportunity, because restoration has such enormous potential for positive impact. But just like every good idea, it only works if we get it right.
在這些錯誤之後,第二波文章湧入, 警告若沒有把復原的方法做對 會產生什麼風險。 這批評讓我非常痛苦, 因為它完全正確。 但我最害怕的是 我們會浪費掉這個大好機會, 因為復原生態系具有 產生正面影響的極大潛力, 但和所有的好點子一樣, 要做對才有用。
But as the dust settled, we realized that this was actually a time when the entire movement gained real momentum. More people than ever were interested in global restoration, and with messages flooding in about the successes and failures of restoration projects around the world, we had access to the lessons that can help us to get it right. Every new criticism offered incredible opportunities to learn and grow. Every failed restoration example was a lesson on how to improve future projects. These learnings were an entirely new source of data -- data from the real heroes of this movement, from the people on the ground who were conserving and managing ecosystems around the world. No one knows their ecosystems more, and no one is more aware of the risks of restoration done wrong and the need for accurate ecological information to show the best areas to focus on, which species can exist in those regions, and what benefits those species can provide to the community.
塵埃落定後,我們才發現這段時期 其實是這整個運動 真正氣勢大增的時期。 以前從來沒有這麼多人 對全球性生態系復原感興趣。 隨著世界各地復原計畫 成功或失敗的訊息不斷湧入, 我們也得以汲取這些經驗, 把事情做對。 每一個批評都是 學習和成長的極佳機會。 每一次復原失敗的例子 都讓我們上了一堂課, 教我們如何改善未來的計畫。 這些學習的過程是全新的數據來源, 這個運動背後有一群真正英雄 讓我們有這些數據, 他們在全世界各地付出, 實地從事保育和管理生態系統的工作。 他們最了解他們的生態系統, 最清楚復原失敗的風險是什麼。 他們也知道正確的生態資訊 才能讓他們知道該著重哪些區域、 哪些物種可以在該地生存, 以及那些物種怎麼嘉惠當地居民。
Historically, these are questions that have been addressed through years of rigorous trial and error. But we started wondering: What if we fed this deep on-the-ground knowledge back into our machine-learning models to learn from the thousands of successes and failures? Could this help us to identify which strategies are working and failing around the world? And about a year ago, we started working with Google to help build and scale this idea into a functioning online ecosystem, where projects from around the world can learn and grow together. By pairing Google's technology and our models, this ever-growing network of scientists, restoration projects, and NGOs could now build the platform that could serve the restoration movement. And I am so excited to give you a first glimpse of what we've been working on.
在歷史上,處理這些問題的方式 是用經年不斷的嘗試錯誤。 但我們開始納悶: 要是我們把這些實地獲得的知識 用在我們的機器學習模型上, 從數以千計的成功和失敗 當中學習呢? 這樣做能否協助我們找出世界各地 哪些策略行得通、哪些行不通? 大約一年前, 我們開始和 Google 合作, 協助建立並將規模擴大成 能運作的線上虛擬生態系統, 讓世界各地的計畫 能夠一起學習與成長。 將 Google 的技術 和我們的模型結合, 這個不斷成長, 由科學家、復原計畫、 非政府組織組成的網路 現在能建立平台 來協助生態系復原運動。 我很興奮能帶大家先睹為快, 看看我們在做些什麼。
This is Restor, an open data platform for the restoration movement, providing free ecological insights to show which species of trees, grasses, or shrubs might exist in that region, monitoring of projects so that we can all see the developments happening on the ground. And most importantly, for the sharing of ecological information so that restoration organizations can learn one another and so that funders can find and track projects to support. Restor is a digital ecosystem for restoration. The more data the community uploads, the stronger the predictions get and the more informed action we can all take. Putting the learnings of thousands of projects into the hands of people everywhere.
這是 Restor, 它是復原運動的開放資料平台, 能提供免費的生態系解析, 呈現某區域可能會有 哪幾種樹木、草,或灌木, 並監控各地的計畫, 讓我們大家都能看見實地的進展。 最重要的是, 它也能分享生態資訊, 讓復原組織能彼此學習, 出資者也能找到想資助的計畫, 並加以追蹤。 Restor 是一個數位生態系統, 目的在協助生態系復原。 各地上傳的資料越多, 預測能力就會越強, 我們也越能採取有效的行動, 並將從數以千計的計畫中獲得的知識 交到各地民眾的手上。
And this ecosystem is much bigger than just planting trees. Trees are just the symbol for entire ecosystem restoration. Restor is for the protection of land so trees can recover, for the amendment of soil so vegetation can return, and for the thousands of other approaches used to promote the health of grasslands, peatlands, and all other ecosystems that are equally important for life on earth. Whether you want to support a wetland conservation project with huge carbon potential or simply find which species of plant might exist in your garden and how much soil carbon they could accumulate, with this tool, we hope that everyone everywhere will have a chance to engage in the restoration movement.
這個數位生態系統的目的 不只是種樹而已。 樹木只是整個生態系統恢復的徵兆。 Restor 的目的是保護土地, 讓樹木可以復原; 改善土壤,讓植被能夠再出現; 也能協助其他數以千計的方法, 來促進草地、泥炭地等 對所有生命都很重要的 生態系統的健康。 不論你想要支持減碳潛力 很大的濕地保育計畫, 或只是想知道你的花園中 種得活哪幾種植物、 這些植物能累積多少土壤碳量, 有了這項工具,我們希望各地的所有人 都有機會參與這個生態系復原運動。
The word "restore" is defined as the act of returning something back to its original state, but it's also the act of returning it back to its original owners. The restoration of nature is for the local biodiversity and the communities that depend on it. And as that network grows, the collective action benefits everyone. And these benefits go far beyond the threat of climate change. Even if climate change stopped right now, the protection and rebuilding of earth's biodiversity would still be a top priority because it underpins all life on earth. It can help us with all other global threats, including extreme weather events, droughts, food shortages and global pandemics.
「復原」一詞的定義 是將某種東西還原到原始狀態, 也是交還給原始的擁有者。 復原大自然是為了當地的生物多樣性 以及仰賴當地生態的居民。 隨著交流網路的成長, 集體的行動會讓每個人都受益。 而所帶來的益處遠超過 因應氣候變遷的威脅。 就算氣候變遷現在就停止了, 地球生物多樣性的保護和重建 都仍應擺在第一優先, 因為它是地球上所有生命的基礎。 它能協助我們處理 所有其他的全球性威脅, 包括極端天氣事件、乾旱、 食物短缺,及疾病的全球疫情。
But global restoration won't be easy, and it will not be solved by tech solutions alone. These tools can inform us, but ultimately the challenge is one that can only be addressed by us, by all of us. Just like the interdependent species that make up natural ecosystems, we humans are deeply dependent on one another. We need the immense network of limitless connections, the farmers and project leaders on the ground who need local markets and industries to make use of sustainable products.
但全球性的生態系復原並不容易, 且不能單靠科技方案來解決。 這些工具能提供我們資訊, 但最終, 能處理這難題的還是我們, 我們所有人。 就如同自然生態系統中 相互依賴的物種, 我們人類彼此之間也有很深的依賴。 我們需要無限連結 所形成的巨大網路: 集結農民、實地的計畫領導人, 他們需要當地的市場和產業 來使用永續產品;
The scientists, governments, NGOs, businesses, you, me, we are all needed to keep this movement going. We need the whole ecology of humanity.
集結科學家、政府、企業、 非政府組織、你、我, 我們都必須參與才能 讓這個運動持續下去。 人類的整個生態都必須參與。
Thank you.
謝謝。