Ecology

Ambitious new targets are needed to conserve nature by protecting parks and species.Credit: Tang Dehong/VCG/Getty

It will take ample time and money to slow the world’s catastrophic loss of plant and animal species — and right now, both are running dangerously low. This year, nations are due to agree to an action plan to protect global biodiversity at the 15th Conference of the Parties (COP15) to the United Nations Convention on Biological Diversity. But the meeting is already two years late because of the pandemic, and China, which will host the conference in Kunming, has yet to set a new date.Now, conflicts over financing are adding to the tension. Conservation groups and advocates suggest that rich nations must donate at least US$60 billion annually to help less-affluent ones to fund projects such as protecting areas where wildlife can thrive and tackling the illegal wildlife trade that is driving hundreds of species to extinction. This is much more than the $4 billion to $10 billion that they are estimated to be spending today, and well below the amount they are giving low- and middle-income countries (LMICs) to fight climate change, which reached around $50 billion in 2019 according to one estimate. Yet limited overseas development funds are spread ever thinner as donors deal with the pandemic and now the fallout from Russia’s invasion of Ukraine. This is where COP15 is meant to deliver: as well as agreeing to the action plan, called the Global Biodiversity Framework, nations will be encouraged to pledge more money.A mix of public and private money has started to trickle in. Currently, biodiversity funding on the table ahead of COP15 amounts to roughly $5.2 billion per year, according to estimates by a group of five leading conservation organizations. Most comes from six governments, including France, the United Kingdom and Japan, and the European Union. In April, the Global Environment Facility (GEF) — a multilateral fund to support international environmental agreements — announced that, over the next four years, around $1.9 billion will go to projects dedicated to biodiversity. However, it’s unclear how much of this will come from the coffers that donor countries have already pledged.Some cash for conservation is coming from private philanthropic donors — such as $2 billion committed by entrepreneur Jeff Bezos last year. And starting in 2020, a group of financial institutions (now 89 of them) promised to annually report their financing activities and investments that affect biodiversity, and to move away from those that do harm — a form of ecological accounting that could help to shrink the budget needed to protect biodiversity. Donors will need to reach much deeper into their pockets to meet the demands of LMICs, the custodians of much of the world’s biodiversity. In March, a group of LMICs, led by Gabon, asked for $100 billion per year in new funding when officials met in Geneva, Switzerland, to discuss progress on the Global Biodiversity Framework. The LMICs want the money placed in a new multilateral fund for biodiversity, separate from, but complementary to, the GEF.Aside from cash, the fund will need to find a new home and structure — and there are a few options. A proposal from Brazil, circulated at the Geneva meeting, suggests the fund be governed by a board of 24 members, with an equal number from rich and lower-income nations. The board would be responsible for funding decisions and would prioritize projects that help to achieve the biodiversity convention’s goals. The pitch generated interest among some countries, but also concerns that it’s an attempt by Brazil to divert attention from its failure over the past few years to protect the Amazon rainforest and prevent other environmental harm.Another option is the Kunming Biodiversity Fund, which China announced in October last year to help LMICs to safeguard their ecosystems. It allocated 1.5 billion yuan (US$223 million) to seed the fund and invited other countries to contribute, but so far none has. Sources knowledgeable about the fund say that donor countries are reluctant to pitch in because China is holding on too tightly to the reins and is not involving others in its deliberations. Details of how the fund will operate are scarce, but Nature has learnt that China is floating the idea of housing it at the Asian Infrastructure Investment Bank (AIIB), based in Beijing. Set up in 2016, the AIIB has $100 billion in total capital and 105 members, including Germany, France and the United Kingdom. The AIIB has big green plans. By 2025, it wants half of all infrastructure projects it finances to focus on climate issues. With rigorous oversight and transparency, the AIIB would make a good home for the Kunming fund.As countries prepare to meet in Nairobi on 20–26 June in a last-ditch attempt to push the biodiversity framework forwards before COP15, China, as the host, must urgently provide stronger leadership on financing, including more transparency and engagement. Progress will require quick, generous contributions from donor nations — which should prioritize grants, not loans, for biodiversity projects.Holding the COP15 meeting must be a priority, too. As China tightens restrictions in the face of a COVID-19 surge, some researchers fear that delays will stretch on, stalling conservation work and leaving less time to meet biodiversity targets. China must either commit to holding the meeting this year or let it proceed elsewhere. One option being quietly discussed is moving the meeting to Canada — home of the United Nations biodiversity convention’s secretariat — and this deserves consideration. The world needs an ambitious biodiversity plan now — nature cannot wait. More

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Mesocosm experimentsSi:Nexport measurementsBetween 2010 and 2014, we conducted five in situ mesocosm experiments to assess impacts of OA on natural plankton communities. Study sites covered a large latitudinal gradient (28 °N–79 °N) and diverse oceanic environments/ecosystems (Extended Data Fig. 1 and Extended Data Table 1). Sample collection and processing was conducted every 1 or 2 days throughout the experiments. Sinking particulate matter was obtained from sediment traps attached to the bottom of each mesocosm, thereby collecting the entire material sinking down in the enclosed water column36. Processing of sediment trap samples followed a previous protocol37. Samples for particulate matter suspended in the water column were collected with depth-integrating water samplers (HYDRO-BIOS) and filtered following standard procedures. Biogenic silica was leached from the sediment trap samples and filters by alkaline pulping (0.1 M NaOH at 85 °C). After 135 min the leaching process was terminated with 0.05 M H2SO4 and dissolved silica was measured spectrophotometrically38. Carbon and nitrogen content were determined using an elemental CN analyser (EuroEA)39.Analysis of OA impactsTo test for a systemic influence of OA on Si:Nexport, we synthesized the datasets from the different experiments and (i) conducted a meta-analysis to quantify effect sizes, and (ii) computed probability density estimates. Because the experimental design, the range of CO2 treatments, and the time periods for our analysis of Si:Nexport varied to some extent among experiments (Extended Data Table 1), we pooled mesocosms for ambient conditions and in the ({{p}}_{{{rm{CO}}}_{2}}) range of ~700–1,000 μatm (‘OA treatment’), corresponding to end-of-century values according to RCP 6.0 and 8.5 emission scenarios15. Effect sizes were calculated as log-transformed response ratios lnRR, an approach commonly used in meta-analysis40:$${rm{l}}{rm{n}}{rm{R}}{rm{R}}={rm{l}}{rm{n}}{X}_{{rm{O}}{rm{A}}}-{rm{l}}{rm{n}}{X}_{{rm{c}}{rm{o}}{rm{n}}{rm{t}}{rm{r}}{rm{o}}{rm{l}}},$$where X is the arithmetic mean of Si:Nexport ratios under OA and ambient conditions (Extended Data Table 1). Effect sizes 0 indicate that the effect was positive. Effects are considered statistically significant when 95% confidence intervals (calculated from pooled standard deviations) do not overlap with zero. The overall effect size across all studies was computed by weighing individual effect sizes according to their variance, following the common methodology for meta-analyses40. In addition, we computed probability densities of Si:Nexport based on kernel density estimation, which better accounts for data with skewed or multimodal distributions41. Another advantage of this approach is that it does not require the calculation of temporal means. Instead, the entire data timeseries can be incorporated into the analysis, thus retaining information about temporal variability. Confidence intervals of the density estimates were calculated with a bootstrapping approach using data resampling (1,000 permutations)41. The resulting probability density plots can be interpreted analogously to histograms. Differences among ambient and OA conditions are considered statistically significant when confidence intervals of the probability density distributions do not overlap. Numbers for suspended and sinking Si, C and N (and their respective ratios) for the analysis period are given in Extended Data Table 2.Analysis of pH effects on Si:N in global sediment trap dataWe analysed a recent compilation of global sediment trap data (674 locations collected between 1976 and 2012)35. The aim of this analysis was to assess the influence of pH on opal dissolution in the world ocean. In contrast to the mesocosm experiments, where export fluxes were measured only at one depth, the global dataset provides depth-resolved information, enabling us to examine the vertical change in the Si:N ratio of sinking particulate matter and how this correlates with pH. It has long been known that the silica content of sinking particles increases with depth, as opal dissolution is less efficient than organic matter remineralization25,42. The resulting accumulation of Si relative to N can be quantified as the change in Si:N with increasing depth, that is, the slope of the relationship of depth versus Si:N (ΔSi:N, in units of m−1). Our approach is analogous to previous studies, which used vertical profiles of Si:C as a proxy for differential dissolution/remineralization of opal and organic matter, and its regional variability in the ocean24,42. We extracted all data that (I) included simultaneous measurements of Si and N, and (II) contained vertical profiles with at least three depth levels (so that ΔSi:N [m−1] can be calculated). We then calculated linear regressions for individual Si:N profiles and subsequently extracted those for which Si:N displayed a statistically significant relationship with depth (p  More

In this International Year of Sustainable Mountain Development, we call for transdisciplinary research by Chilean scientists and for concerted action among all stakeholders to address the complex factors responsible for the degradation of Chile’s mountains. Mountains cover 64% of Chile’s surface and are a crucial source of water, food, energy, minerals and biodiversity.
Competing Interests
The authors declare no competing interests. More

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In this study, we aimed to determine if tropical cyclones in the northwestern GOM differentially affected mesozooplankton community structure. We found that multivariate community structure varied between storm and non-storm years. However, among the three hurricanes, only the post-Harvey mesozooplankton communities were distinct from years where no storms occurred. Multivariate dispersion, a measure of variance within community structure, did not differ between storm and non-storm years. This result refutes our hypothesis that variability in zooplankton community structure would be higher during storm years opposed to non-storm years. Our prediction that post-storm mesozooplankton communities would differ from non-storm communities was supported, as was our expectation that mesozooplankton community structure varied among storms. We hypothesized that due to the major flooding and rainfall of Harvey, reduced salinity would likely be the main driver of mesozooplankton community differences relative to non-storm years. This expectation was partially met; differences in mesozooplankton community structure between Harvey and years with no storms were driven by salinity, stratification, and ‘distance-from-shore’ rather than solely salinity. This indicates that NWGOM zooplankton community structure varies holistically with biophysical conditions rather than being primarily driven by one or two dominating factors24. Moreover, we found that the presence of Hurricane Harvey, rather than temperature, explained the second greatest amount of variance in zooplankton community structure reflecting the importance of considering how complex disturbance mechanisms might compound and result in a unique ecological responses following a tropical cyclone. The overall PSEM showed that high salinity was directly associated with reduced fluorescence and depressed zooplankton abundance. Higher abundances were found to result in higher community dominance (i.e., lower evenness). Conversely, high salinities indirectly reduced zooplankton evenness via greater water column stratification. Lower fluorescence at higher salinities supports the spatial patterns in NWGOM phytoplankton identified by Kurtay et al.20 following Hurricane Harvey. Those authors observed declines in overall phytoplankton abundance and communities increasingly dominated by cells  More