Ecology

1.
Schröder, P. & Chillcott, V. The politics of marine plastics pollution. In The Circular Economy and the Global South: Sustainable Lifestyles and Green Industrial Development 43–46 (2019). https://doi.org/10.4324/9780429434006
2.
Jambeck, J. R. et al. Plastic waste inputs from land into the ocean. Science 347, 768–771 (2015).
ADS  CAS  Article  Google Scholar 

3.
Rochman, C. M., Cook, A. & Koelmans, A. A. Plastic debris and policy: Using current scientific understanding to invoke positive change. Environ. Toxicol. Chem. 35, 1617–1626 (2016).
CAS  Article  Google Scholar 

4.
Vince, J. & Hardesty, B. D. Plastic pollution challenges in marine and coastal environments: from local to global governance. Restor. Ecol. 25, 123–128 (2017).
Article  Google Scholar 

5.
Clapp, J. & Swanston, L. Doing away with plastic shopping bags: international patterns of norm emergence and policy implementation. Environ. Polit. 18, 315–332 (2009).
Article  Google Scholar 

6.
Xanthos, D. & Walker, T. R. International policies to reduce plastic marine pollution from single-use plastics (plastic bags and microbeads): a review. Mar. Pollut. Bull. 118, 17–26 (2017).
CAS  Article  Google Scholar 

7.
Ten Brink, P. et al. Circular economy measures to keep plastics and their value in the economy, avoid waste and reduce marine litter. Econ. E-J. 1–12 (2018).

8.
Willis, K., Maureaud, C., Wilcox, C. & Hardesty, B. D. How successful are waste abatement campaigns and government policies at reducing plastic waste into the marine environment?. Mar. Policy 96, 243–249 (2018).
Article  Google Scholar 

9.
Gove, J. M. et al. Prey-size plastics are invading larval fish nurseries. Proc. Natl. Acad. Sci. 201907496 (2019). https://doi.org/10.1073/pnas.1907496116

10.
Asakura, H., Matsuto, T. & Tanaka, N. Behavior of endocrine-disrupting chemicals in leachate from MSW landfill sites in Japan. Waste Manag. 24, 613–622 (2004).
CAS  Article  Google Scholar 

11.
Bejgarn, S., MacLeod, M., Bogdal, C. & Breitholtz, M. Toxicity of leachate from weathering plastics: an exploratory screening study with Nitocra spinipes. Chemosphere 132, 114–119 (2015).
ADS  CAS  Article  Google Scholar 

12.
Li, W. C., Tse, H. F. & Fok, L. Plastic waste in the marine environment: a review of sources, occurrence and effects. Sci. Total Environ. 566–567, 333–349 (2016).
ADS  Article  Google Scholar 

13.
Gregory, M. R. The hazards of persistent marine pollution: drift plastics and conservation islands. J. R. Soc. N.. 21, 83–100 (1991).
Article  Google Scholar 

14.
Wright, S. L., Thompson, R. C. & Galloway, T. S. The physical impacts of microplastics on marine organisms: a review. Environ. Pollut. 178, 483–492 (2013).
CAS  Article  Google Scholar 

15.
Cartraud, A. E., Le Corre, M., Turquet, J. & Tourmetz, J. Plastic ingestion in seabirds of the western Indian Ocean. Mar. Pollut. Bull. 140, 308–314 (2019).
CAS  Article  Google Scholar 

16.
UN Department of Economics and Social Affairs. World population prospects-population division—United Nations. Int. J. Logist. Manag. 9, 1–13 (2019).
Google Scholar 

17.
Bourn, D. et al. The rise and fall of the Aldabran giant tortoise population. . Proc. R. Soc. Lond. Ser. B Biol. Sci. 266, 1091–1100 (1999).
CAS  Article  Google Scholar 

18.
Mortimer, J. A., von Brandis, R. G., Liljevik, A., Chapman, R. & Collie, J. Fall and rise of nesting green turtles (Chelonia mydas) at Aldabra Atoll, seychelles: positive response to four decades of protection (1968–2008). Chelonian Conserv. Biol. 10, 165–176 (2011).
Article  Google Scholar 

19.
Šúr, M., Bunbury, N. & Van De Crommenacker, J. Frigatebirds on Aldabra Atoll: population census, recommended monitoring protocol and sustainable tourism guidelines. Bird Conserv. Int. 23, 214–220 (2013).
Article  Google Scholar 

20.
Van De Crommenacker, J. et al. Long-term monitoring of landbirds on Aldabra Atoll indicates increasing population trends. Bird Conserv. Int. 26, 337–349 (2016).
Article  Google Scholar 

21.
Friedlander, A. et al. Biodiversity and ecosystem health of the Aldabra Group, Southern Seychelles – Scientific report to the government of Seychelles (2015).

22.
Harper, G. A. & Bunbury, N. Invasive rats on tropical islands: their population biology and impacts on native species. Glob. Ecol. Conserv. 3, 607–627 (2015).
Article  Google Scholar 

23.
Prior, K. M., Adams, D. C., Klepzig, K. D. & Hulcr, J. When does invasive species removal lead to ecological recovery? Implications for management success. Biol. Invasions 20, 267–283 (2018).
Article  Google Scholar 

24.
Brooks, T. M. et al. Habitat loss and extinction in the hotspots of biodiversity. Conserv. Biol. 16, 909–923 (2002).
Article  Google Scholar 

25.
Courchamp, F., Hoffmann, B. D., Russell, J. C., Leclerc, C. & Bellard, C. Climate change, sea-level rise, and conservation: keeping island biodiversity afloat. Trends Ecol. Evol. 29, 127–130 (2014).
Article  Google Scholar 

26.
Cherian, A. Linkages between biodiversity conservation and global climate change in small island developing States (SIDS). Nat. Resour. Forum 31, 128–131 (2007).
Article  Google Scholar 

27.
Lavers, J. L. & Bond, A. L. Exceptional and rapid accumulation of anthropogenic debris on one of the world’s most remote and pristine islands. Proc. Natl. Acad. Sci. USA. 114, 6052–6055 (2017).
CAS  Article  Google Scholar 

28.
Lavers, J. L., Dicks, L., Dicks, M. R. & Finger, A. Significant plastic accumulation on the Cocos (Keeling) Islands Australia. Sci. Rep. 9, 7102 (2019).
ADS  CAS  Article  Google Scholar 

29.
Duhec, A. V., Jeanne, R. F., Maximenko, N. & Hafner, J. Composition and potential origin of marine debris stranded in the Western Indian Ocean on remote Alphonse Island Seychelles. Mar. Pollut. Bull. 96, 76–86 (2015).
CAS  Article  Google Scholar 

30.
Dunlop, S. W., Dunlop, B. J. & Brown, M. Plastic pollution in paradise: daily accumulation rates of marine litter on Cousine Island. Seychelles. Mar. Pollut. Bull. https://doi.org/10.1016/j.marpolbul.2019.110803 (2019).
Article  PubMed  Google Scholar 

31.
Beaumont, N. J. et al. Global ecological, social and economic impacts of marine plastic. Mar. Pollut. Bull. 142, 189–195 (2019).
CAS  Article  Google Scholar 

32.
Eunomia. Plastics in the Marine Environment. Eunomia Research & Consulting Ltd. (2016) Study to Support the Development of Measures to Combat a Range of Marine Litter Sources, Report for DG Environment of the European Commission 1, (2016).

33.
Lebreton, L. et al. Evidence that the Great Pacific Garbage Patch is rapidly accumulating plastic. Sci. Rep. 8, 4666 (2018).
ADS  CAS  Article  Google Scholar 

34.
Monteiro, R. C. P., Ivar do Sul, J. A. & Costa, M. F. Plastic pollution in islands of the Atlantic Ocean. Environ. Pollut. 238, 103–110 (2018).
CAS  Article  Google Scholar 

35.
Edyvane, K. S. & Penny, S. S. Trends in derelict fishing nets and fishing activity in northern Australia: implications for trans-boundary fisheries management in the shared Arafura and Timor Seas. Fish. Res. 188, 23–37 (2017).
Article  Google Scholar 

36.
Eriksen, M. et al. Plastic pollution in the World’s Oceans: more than 5 Trillion Plastic Pieces Weighing over 250,000 Tons Afloat at Sea. PLoS ONE 9, e111913 (2014).
ADS  Article  Google Scholar 

37.
Seychelles Fishing Authority. SFA Fisheries Statistical Report Year 2016. (2016).

38.
Maufroy, A., Chassot, E., Joo, R. & Kaplan, D. M. Large-scale examination of spatio-temporal patterns of drifting fish aggregating devices (dFADs) from tropical tuna fisheries of the Indian and Atlantic Oceans. PLoS ONE 10, e0128023 (2015).
Article  Google Scholar 

39.
Balderson, S. D. & Martin, L. E. C. Environmental impacts and causation of ‘ beached ’ Drifting Fish Aggregating Devices around Seychelles Islands: a preliminary report on data collected by Island Conservation Society. In 11th Work. Party Ecosyst. Bycatch, 7–11 Sept. 2015, Olhão, Port. 1–15 (2015).

40.
Bouwman, H., Evans, S. W., Cole, N., Choong Kwet Yive, N. S. & Kylin, H. The flip-or-flop boutique: marine debris on the shores of St Brandon’s rock, an isolated tropical atoll in the Indian Ocean. Mar. Environ. Res. 114, 58–64 (2016).
CAS  Article  Google Scholar 

41.
Knowles, C. The flip-flop trail and fragile globalization. Theory Cult. Soc. 32, 231–244 (2015).
Article  Google Scholar 

42.
Ryan, P. G., Dilley, B. J., Ronconi, R. A. & Connan, M. Rapid increase in Asian bottles in the South Atlantic Ocean indicates major debris inputs from ships. Proc. Natl. Acad. Sci. USA 116, 20892–20897 (2019).
ADS  CAS  Article  Google Scholar 

43.
Lebreton, L. C. M. et al. River plastic emissions to the world’s oceans. Nat. Commun. 8, 15611 (2017).
ADS  CAS  Article  Google Scholar 

44.
Talma, E. & Martin, M. The Status of Waste Management in Seychelles. (2013).

45.
Adelene Lai, J. H. & Pius Krütli, & M. S. Solid Waste Management in the Seychelles. USYS TdLab Transdisciplinary Case Study (2016).

46.
Quanz, C., Fleischer-Dogley, F. & Frühauf, M. Compatibility of nature conservation and tourism on the seychelles islands; potentials, projects and problems. Hercynia 42, 1–20 (2009).
Google Scholar 

47.
Hoornweg, D., Bhada-Tata, P. & Kennedy, C. Waste production must peak this century. Nature 615–617 (2013).

48.
Lamb, J. B. et al. Plastic waste associated with disease on coral reefs. Science 359, 460–462 (2018).
ADS  CAS  Article  Google Scholar 

49.
Stoddart, D. R. & Mole, L. U. Climate of Aldabra Atoll. Atoll Res. Bull. 202, 1–21 (1977).
Article  Google Scholar 

50.
Lopez, J., Moreno, G., Sancristobal, I. & Murua, J. Evolution and current state of the technology of echo-sounder buoys used by Spanish tropical tuna purse seiners in the Atlantic Indian and Pacific Oceans. Fish. Res. 155, 127–137 (2014).
Article  Google Scholar 

51.
Fonteneau, A., Chassot, E. & Bodin, N. Global spatio-temporal patterns in tropical tuna purse seine fisheries on drifting fish aggregating devices (DFADs): taking a historical perspective to inform current challenges. Aquat. Living Resour 26, 37–48 (2013).
Article  Google Scholar  More

Trabaque tufa record
Trabaque Canyon (40.36° N; 2.26° W; 840 m above sea level) is located in the central Iberian Peninsula (Fig. 1). At this site, tufa deposits precipitate as freshwater carbonates downstream of overflow karst springs. During the last interglacial period, tufa precipitated continuously at the studied site while water level of the aquifer was high enough for upstream springs to discharge13. Outcrops of the studied tufa deposit are preserved in the margins of Trabaque River over a distance of 500 m downstream of overflow karstic springs. The studied tufa deposit is 12 m thick, with a gentle ramp morphology, and a simple stratigraphy of sub-horizontal tufa beds that covered the full section of the narrow canyon. The accumulation of tufa created a small lake upstream the ramp, which prevented erosive events while the deposit was active, because most of the river bedload was accumulated in the basin of the lake. This configuration favoured the lack of erosive episodes in the tufa and the deposition of a continuous record. The tufa deposit was partially eroded by subsequent fluvial incision once the tufa accretion ceased and detrital sediments filled the lake basin and started to flow over the ramp during floods. The tufa deposit is mostly composed of well-cemented intra-clastic and peloidal carbonate particles13. The deposit comprises tufa beds 0.02–1 m thick that typically extend tens of metres downstream. At the base of the section, the tufa lies over loose fluvial sediments of sandy silt, whereas at the top of the section there is an erosive scar, and recent gravitational deposits overlay the tufa preserved in the slopes of the canyon.
Figure 1

Pictures of Trabaque Canyon and the studied deposit. (a) Trabaque Canyon. The river flows according to yellow arrows. The red ellipse shows the location of the main section where the deposit was sampled. The inlet map shows the location of Trabaque Canyon within the Iberian Peninsula. (b) View of most of the studied Trabaque tufa section. The base and top of the section are missing from this panorama. The centre of the valley bottom is to the left of the image and the slope of the canyon to the right. The river flowed from the position of the observer towards the tufa deposit. The picture shows gravitational pulses GP-2 and GP-3 that interdigitate with the tufa deposit, and their disappearance from the bottom of the valley after GP-3. (c) Detail of GP-3 gravitational deposit. (d) Detail of the alternation between well-cemented and loose tufa beds at the top of the section.

Full size image

The base of the deposit section is characterized by nearly 4 m of tufa sediments in the centre of the valley, laterally interdigitating with gravitational deposits towards the slopes (Fig. 1). These gravitational deposits partially invaded the bottom of the valley during three distinct pulses. These gravitational deposits occurred during periods of enhanced slope processes due to the decrease in vegetation cover on the canyon slopes during prolonged dry periods. The evidence of local erosion recorded by the gravitational deposits is consistent with other proxies that record local and regional erosion and that are displayed in Fig. 2. Thus, independent evidence of erosion is also recognized from the increase of insoluble residue (IR) particles in the tufa, recorded by the percentage of silt IR. IR particles were transported to the tufa by the river or by the action of wind. The increase of these particles in the tufa is interpreted as enhanced erosion, not only from the catchment but also from outside the basin. Higher concentrations of Si and Al are also interpreted as proxies of soil erosion from areas with silicate substrates inside or outside the catchment. The increase of micro-charcoal particles in the tufa is also interpreted as a sign of enhanced soil erosion. Charcoals were incorporated to the tufa during floods or transported by the wind after the occurrence of fires, as well as from the erosion of soils that accumulated charcoals from previous fire events. In any case, the increase of micro-charcoals in the tufa record suggests soil erosion due to the lost of vegetation cover. Major events of local and regional erosion occurred synchronously (Fig. 2), supporting that the common decreases in vegetation cover that resulted in erosion events were related to periods of reduced precipitation.
Figure 2

Record of the Trabaque tufa deposit. (a) Simplified lithological log of the Trabaque record. Patterns represent gravitational deposits (black) with distinct three pulses, well-cemented tufa sediments (light grey), and alternation of well-cemented and loose tufa sediments (dark grey). (b,c) Tufa δ18O and δ13C records. Isotope values at each date (dots) are the average of 3 sub-samples and blue/red line is a 3-point running mean. The grey shade shows the 1σ variability of the three sub-samples along the record. (d) Concentration of Si and Al. (e) Silt-sized insoluble residue in tufa as percentage of the total sample. (f) Counts of micro-charcoal particles  More

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. More

General situation of the research area
The research area was conducted at Liufangzi village, Gongzhuling city, Jilin Province (N43°34′10″, E124°52′55″), as shown in Fig. 8. The area has a continental monsoon climate in the humid area of the middle temperate zone, with an average annual precipitation of 594.8 mm, which is mainly concentrated in June and August. The average annual temperature is 5.6 °C, and the daily average temperature drops to 0 °C in November of each year, with a freezing period of up to five months. Corn is one of the main commodity crops in the area, with a sowing date in early May and a harvest date in early October.
Figure 8

Location of study area (Liufangzi Village, Gongzhuling City, Jilin Province).

Full size image

The soil of the site is a silty loam black soil, which had been planted with monoculture corn with no tillage for 5 years. On October 5, 2018 (after the autumn harvest), a flat field was selected to set up the experiment. Soil samples were collected using the zigzag sampling method, and selective physical and chemical properties of soil were determined, including pH (5.48), organic matter (26.4 g kg−1), clay (29.12%), and soil bulk density (1.21 g cm−3 in 5–10 cm and 1.53 g cm−3 in 20–25 cm).
Reagents and instruments
Reagents
The main raw material of the added impervious agent was corn starch and acrylic compound, which was entrusted to Jilin Yida Chemical Co., Ltd. The added urea was an analytical reagent, and the reagents used for analysis included H2SO4, H3PO4, NaOH, NH4OH, NH4Cl, K2S2O8, Na2B4O7, KNO3, KNO2, K2Cr2O7, FeSO4, sulfonamide, and naphthalene ethylenediamine hydrochloride; these were all analytical reagents provided by Beijing Chemical Plant.
Instruments laboratory-built soil leaching column; continuous flow injection analyser (SKALAR SA++, Netherlands).
Test plot setup and agronomic practices
The experimental plots were maintained in the field consisting of (1) CK (no-tillage control treatment, with corn straw removed and soil left under no-till management); (2) ploughing treatment (corn straw was removed and then mouldboard ploughed to a 30 cm depth); (3) straw returning treatment (corn straw (25.32% moist) was incorporated into the soil on October 5, 2018 (after autumn harvest), with an application amount of 1.25 kg m−2. Briefly, corn straw was chopped into small pieces (0.5 cm length), evenly placed on the soil surface, and then incorporated into the soil with ploughing (the depth of 30 cm)); and (4) impervious agent addition treatment (the impervious agent mentioned previously evenly laid on the soil surface at the amount of 15 g m−2 and then incorporated into the 0–30 cm soil by mouldboard ploughing). The abovementioned field operations were conducted after corn harvest in the fall of 2018 with a testing area of 10 m × 50 m for each plot and three replicates for each treatment. In the following spring (2019), grain corn was planted in all treatment plots with a planting density of 65,000 plants ha−1. All plots were managed in the same way with a one-time fertilization application of 200–90-90 kg (N-P-K) ha−1 and 2,4-d spray as weed control.
For all the above treatments (including the control treatment), undisturbed soils (0–30 cm layer) were collected with an undisturbed soil column (refer to Fig. 9) for the leaching experiment on September 25, 2019 (before autumn harvest, after 350 days of straw returning to the field); soil samples of 0–15 cm were collected for determination of soil organic matter and adsorption experiment of nitrogen in the soil; and soil samples of 5–10 cm and 20–25 cm layers were collected for determination of soil bulk density. In addition, for the straw returning treatment, one sampling was added on May 25, 2019 (one month after sowing, 230 days after straw returning), for the determination of soil organic matter content and soil bulk density, nitrogen adsorption and leaching experiment in soil.
Figure 9

Schematic diagram of simulated leaching device of undisturbed soil column. (a) Soil extraction; (b) leaching; (c) physical map of leaching in undisturbed soil column. 1: Handle; 2.3.4: guide port; 5.6: screw port; 7: punching plate. I main body of leaching column; II soil cutter; III leaching solution collector.

Full size image

The soil samples used for soil organic matter determination and nitrogen absorption testing were air dried, sieved through a 2-mm sieve and visible plant debris and stones were removed, and then stored.
Experiment of nitrogen adsorption in soil
Ten parts of the soil samples (air-dried,  More

1.
Erős, T., O’Hanley, J. R. & Czeglédi, I. A unified model for optimizing riverscape conservation. J. Appl. Ecol. 55, 1871–1883 (2018).
Google Scholar 
2.
Ruggeri, P., Pasternak, E. & Okamura, B. To remain or leave: Dispersal variation and its genetic consequences in benthic freshwater invertebrates. Ecol. Evol. 9, 12069–12088 (2019).
PubMed  PubMed Central  Google Scholar 

3.
Baguette, M., Blanchet, S., Legrand, D., Stevens, V. M. & Turlure, C. Individual dispersal, landscape connectivity and ecological networks. Biol. Rev. 88, 310–326 (2013).
PubMed  Google Scholar 

4.
Geist, J. Seven steps towards improving freshwater conservation. Aquat. Conserv. Mar. Freshw. Ecosyst. 25, 447–453 (2015).
Google Scholar 

5.
Kujala, H., Lahoz-Monfort, J. J., Elith, J. & Moilanen, A. Not all data are equal: Influence of data type and amount in spatial conservation prioritisation. Methods Ecol. Evol. 9, 2249–2261 (2018).
Google Scholar 

6.
Johnson, J. B., Peat, S. M. & Adams, B. J. Where’s the ecology in molecular ecology?. Oikos 118, 1601–1609 (2009).
Google Scholar 

7.
Janse, J. H. et al. GLOBIO-aquatic, a global model of human impact on the biodiversity of inland aquatic ecosystems. Environ. Sci. Policy 48, 99–114 (2015).
Google Scholar 

8.
Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).
ADS  PubMed  CAS  Google Scholar 

9.
Moore, D., Cranston, G., Reed, A. & Galli, A. Projecting future human demand on the Earth’s regenerative capacity. Ecol. Indic. 16, 3–10 (2012).
Google Scholar 

10.
Yawson, D. O., Adu, M. O. & Armah, F. A. Impacts of climate change and mitigation policies on malt barley supplies and associated virtual water flows in the UK. Sci. Rep. 10, 1–12 (2020).
Google Scholar 

11.
Naidoo, R. et al. Global mapping of ecosystem services and conservation priorities. Proc. Natl. Acad. Sci. USA 105, 9495–9500 (2008).
ADS  PubMed  CAS  Google Scholar 

12.
Hermoso, V., Villero, D., Clavero, M. & Brotons, L. Spatial prioritisation of EU’s LIFE-Nature programme to strengthen the conservation impact of Natura 2000. J. Appl. Ecol. 55, 1575–1582 (2018).
Google Scholar 

13.
Hermoso, V., Morán-Ordóñez, A., Canessa, S. & Brotons, L. Realising the potential of Natura 2000 to achieve EU conservation goals as 2020 approaches. Sci. Rep. 9, 1–10 (2019).
CAS  Google Scholar 

14.
Lobera, G., Pardo, I., García, L. & García, C. Disentangling spatio-temporal drivers influencing benthic communities in temporary streams. Aquat. Sci. 81, 1–17 (2019).
CAS  Google Scholar 

15.
Richman, N. I. et al. Multiple drivers of decline in the global status of freshwater crayfish (Decapoda: Astacidea). Philos. Trans. R. Soc. B Biol. Sci. 370, 20140060 (2015).

16.
Manenti, R. et al. Causes and consequences of crayfish extinction: Stream connectivity, habitat changes, alien species and ecosystem services. Freshw. Biol. 64, 284–293 (2019).
Google Scholar 

17.
Kozák, P., Füreder, L., Kouba, A., Reynolds, J. & Souty-Grosset, C. Current conservation strategies for European crayfish. Knowl. Manag. Aquat. Ecosyst. 01, https://doi.org/10.1051/kmae/2011018 (2011).

18.
Pârvulescu, L. Introducing a new Austropotamobius crayfish species (Crustacea, Decapoda, Astacidae): A miocene endemism of the Apuseni Mountains, Romania. Zool. Anz. 279, 94–102 (2019).
Google Scholar 

19.
Kouba, A., Petrusek, A. & Kozák, P. Continental-wide distribution of crayfish species in Europe: Update and maps. Knowl. Manag. Aquat. Ecosyst. 413, 05–31 (2014).
Google Scholar 

20.
Pârvulescu, L. et al. A journey on plate tectonics sheds light on European crayfish phylogeography. Ecol. Evol. 9, 1957–1971 (2019).
PubMed  PubMed Central  Google Scholar 

21.
Pârvulescu, L. & Zaharia, C. Current limitations of the stone crayfish distribution in Romania: Implications for its conservation status. Limnologica 43, 143–150 (2013).
Google Scholar 

22.
Klobučar, G. I. V. et al. Role of the Dinaric Karst (western Balkans) in shaping the phylogeographic structure of the threatened crayfish Austropotamobius torrentium. Freshw. Biol. 58, 1089–1105 (2013).
Google Scholar 

23.
Qian, S. S., Cuffney, T. F., Alameddine, I., McMahon, G. & Reckhow, K. H. On the application of multilevel modeling in environmental and ecological studies. Ecology 91, 355–361 (2010).
PubMed  Google Scholar 

24.
Manning, P. et al. Redefining ecosystem multifunctionality. Nat. Ecol. Evol. 2, 427–436 (2018).
PubMed  Google Scholar 

25.
Koizumi, I., Usio, N., Kawai, T., Azuma, N. & Masuda, R. Loss of genetic diversity means loss of geological information: The endangered Japanese crayfish exhibits remarkable historical footprints. PLoS ONE 7, e33986 (2012).
ADS  PubMed  PubMed Central  CAS  Google Scholar 

26.
McNyset, K. M. Use of ecological niche modelling to predict distributions of freshwater fish species in Kansas. Ecol. Freshw. Fish 14, 243–255 (2005).
Google Scholar 

27.
Henrys, P. A. & Jarvis, S. G. Integration of ground survey and remote sensing derived data: Producing robust indicators of habitat extent and condition. Ecol. Evol. 9, 8104–8112 (2019).
PubMed  PubMed Central  Google Scholar 

28.
Pârvulescu, L., Zaharia, C., Satmari, A. & Drăguţ, L. Is the distribution pattern of the stone crayfish in the Carpathians related to karstic refugia from Pleistocene glaciations?. Freshw. Sci. 32, 1410–1419 (2013).
Google Scholar 

29.
Longshaw, M. & Stebbing, P. Biology and Ecology of Crayfish. (CRC Press, 2015).

30.
Chucholl, C. The bad and the super-bad: Prioritising the threat of six invasive alien to three imperilled native crayfishes. Biol. Invasions 18, 1967–1988 (2016).
Google Scholar 

31.
Chucholl, C. & Schrimpf, A. The decline of endangered stone crayfish (Austropotamobius torrentium) in southern Germany is related to the spread of invasive alien species and land-use change. Aquat. Conserv. Mar. Freshw. Ecosyst. 26, 44–56 (2016).
Google Scholar 

32.
Pârvulescu, L. et al. Flash-flood potential: A proxy for crayfish habitat stability. Ecohydrology 9, 1507–1516 (2016).
Google Scholar 

33.
Farr, T. G. et al. The shuttle radar topography mission. Rev. Geophys. 45, RG2004 (2007).

34.
Şandric, I. et al. Integrating catchment land cover data to remotely assess freshwater quality: A step forward in heterogeneity analysis of river networks. Aquat. Sci. 81, 26 (2019).
Google Scholar 

35.
Burkhard, B., Kroll, F., Nedkov, S. & Müller, F. Mapping ecosystem service supply, demand and budgets. Ecol. Indic. 21, 17–29 (2012).
Google Scholar 

36.
Zeller, K. A., McGarigal, K. & Whiteley, A. R. Estimating landscape resistance to movement: A review. Landsc. Ecol. 27, 777–797 (2012).
Google Scholar 

37.
Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).
Google Scholar 

38.
R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2017).

39.
Freeman, E. A. & Moisen, G. G. A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa. Ecol. Modell. 217, 48–58 (2008).
Google Scholar 

40.
Iorgu, E. I., Popa, O. P., Petrescu, A.-M. & Popa, L. O. Cross-amplification of microsatellite loci in the endangered stone-crayfish Austropotamobius torrentium (Crustacea: Decapoda). Knowl. Manag. Aquat. Ecosyst. 08, https://doi.org/10.1051/kmae/2011021 (2011).

41.
Peakall, R. & Smouse, P. E. genalex 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295 (2006).

42.
Goudet, J. FSTAT (Version 1.2): A computer program to calculate F-statistics. J. Hered. 86, 485–486 (1995).

43.
Rousset, F. genepop’007: A complete re-implementation of the genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).
PubMed  Google Scholar 

44.
Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. & Shipley, P. micro-checker: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535–538 (2004).
Google Scholar 

45.
Dempster, A. P., Laird, N. M. & Rubin, D. B. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 39, 1–22 (1977).
MathSciNet  MATH  Google Scholar 

46.
Chapuis, M. P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631 (2007).
PubMed  CAS  Google Scholar 

47.
Weir, B. S. & Cockerham, C. C. Estimating F‐statistics for the analysis of population structure. Evolution (N. Y). 38, 1358–1370 (1984).

48.
Hammer, D. A. T., Ryan, P. D., Hammer, Ø. & Harper, D. A. T. Past: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica vol. 4 https://palaeo-electronica.orghttp//palaeo-electronica.org/2001_1/past/issue1_01.htm. (2001).

49.
Nei, M., Tajima, F. & Tateno, Y. Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol. 19, 153–170 (1983).
ADS  PubMed  CAS  Google Scholar 

50.
Langella, O. Populations, 1.2. 30. https://bioinformatics.org/~tryphon/populations (1999).

51.
Pritchard, J. K., Stephens, M., Rosenberg, N. A. & Donnelly, P. Association mapping in structured populations. Am. J. Hum. Genet. 67, 170–181 (2000).
PubMed  PubMed Central  CAS  Google Scholar 

52.
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).
PubMed  CAS  Google Scholar 

53.
Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. Clumpak: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 15, 1179–1191 (2015).
PubMed  PubMed Central  CAS  Google Scholar 

54.
Vähä, J. P. & Primmer, C. R. Efficiency of model-based Bayesian methods for detecting hybrid individuals under different hybridization scenarios and with different numbers of loci. Mol. Ecol. 15, 63–72 (2005).
Google Scholar 

55.
Bergl, R. A. & Viglant, L. Genetic analysis reveals population structure and recent migration within the highly fragmented range of the Cross River gorilla (Gorilla gorilla diehli). Mol. Ecol. 16, 501–516 (2006).
Google Scholar 

56.
Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11, 1–15 (2010).
Google Scholar 

57.
Paetkau, D., Calvert, W., Stirling, I. & Strobeck, C. Microsatellite analysis of population structure in Canadian polar bears. Mol. Ecol. 4, 347–354 (1995).
PubMed  CAS  Google Scholar 

58.
Duchesne, P. & Turgeon, J. FLOCK Provides Reliable Solutions to the ‘“Number of Populations”’ Problem. https://doi.org/10.1093/jhered/ess038.

59.
Janes, J. K. et al. The K = 2 conundrum. Mol. Ecol. 26, 3594–3602 (2017).
PubMed  Google Scholar 

60.
Funk, S. M. et al. Major inconsistencies of inferred population genetic structure estimated in a large set of domestic horse breeds using microsatellites. Ecol. Evol. 10, 4261–4279 (2020).
PubMed  PubMed Central  Google Scholar 

61.
Berger, C., Štambuk, A., Maguire, I., Weiss, S. & Füreder, L. Integrating genetics and morphometrics in species conservation—A case study on the stone crayfish, Austropotamobius torrentium. Limnologica 69, 28–38 (2018).
Google Scholar 

62.
Iojă, C. I. et al. The efficacy of Romania’s protected areas network in conserving biodiversity. Biol. Conserv. 143, 2468–2476 (2010).
Google Scholar 

63.
Rabăgia, T. & Maţenco, L. Tertiary tectonic and sedimentological evolution of the South Carpathians foredeep: Tectonic vs eustatic control. Mar. Pet. Geol. 16, 719–740 (1999).

64.
Rãdoane, M., Rãdoane, N. & Dumitriu, D. Geomorphological evolution of longitudinal river profiles in the Carpathians. Geomorphology 50, 293–306 (2003).
ADS  Google Scholar 

65.
Helms, B., Loughman, Z. J., Brown, B. L. & Stoeckel, J. Recent advances in crayfish biology, ecology, and conservation. Freshw. Sci. 32, 1273–1275 (2013).
Google Scholar 

66.
Svobodová, J. et al. The relationship between water quality and indigenous and alien crayfish distribution in the Czech Republic: Patterns and conservation implications. Aquat. Conserv. Mar. Freshw. Ecosyst. 22, 776–786 (2012).
Google Scholar 

67.
Pöckl, M. & Streissl, F. Austropotamobius torrentium as an indicator for habitat quality in running waters? Bull. Français la Pêche la Piscic. 743–758, https://doi.org/10.1051/kmae:2005030 (2005).

68.
Magyar, I. et al. Progradation of the paleo-Danube shelf margin across the Pannonian Basin during the Late Miocene and Early Pliocene. Glob. Planet. Change 103, 168–173 (2013).
ADS  Google Scholar 

69.
Zhang, Y., Luan, P., Ren, G., Hu, G. & Yin, J. Estimating the inbreeding level and genetic relatedness in an isolated population of critically endangered Sichuan taimen (Hucho Bleekeri) using genome-wide SNP markers. Ecol. Evol. 10, 1390–1400 (2020).
PubMed  PubMed Central  Google Scholar 

70.
Hoarau, G. et al. Low effective population size and evidence for inbreeding in an overexploited flatfish, plaice (Pleuronectes platessa L.). Proc. Biol. Sci. 272, 497–503 (2005).

71.
Jourdan, J. et al. Reintroduction of freshwater macroinvertebrates: Challenges and opportunities. Biol. Rev. https://doi.org/10.1111/brv.12458 (2018).
Article  PubMed  Google Scholar 

72.
Oidtmann, B., Heitz, E., Rogers, D. & Hoffmann, R. Transmission of crayfish plague. Dis. Aquat. Organ. 52, 159–167 (2002).
PubMed  Google Scholar 

73.
Rusch, J. C. et al. Simultaneous detection of native and invasive crayfish and Aphanomyces astaci from environmental DNA samples in a wide range of habitats in Central Europe. NeoBiota (2020).

74.
Hall, Q. A., Curtis, J. M., Williams, J. & Stunz, G. W. The importance of newly-opened tidal inlets as spawning corridors for adult Red Drum (Sciaenops ocellatus). Fish. Res. 212, 48–55 (2019).
Google Scholar 

75.
Stewart, F. E. C., Darlington, S., Volpe, J. P., McAdie, M. & Fisher, J. T. Corridors best facilitate functional connectivity across a protected area network. Sci. Rep. 9, 10852 (2019).
ADS  PubMed  PubMed Central  Google Scholar 

76.
Strauss, A., White, A. & Boots, M. Invading with biological weapons: The importance of disease-mediated invasions. Funct. Ecol. 26, 1249–1261 (2012).
Google Scholar 

77.
Clavero, M. & García-Berthou, E. Invasive species are a leading cause of animal extinctions. Trends Ecol. Evol. 20, 110 (2005).
PubMed  Google Scholar 

78.
Nunes, A. L., Tricarico, E., Panov, V. E., Cardoso, A. C. & Katsanevakis, S. Pathways and gateways of freshwater invasions in Europe. Aquat. Invasions 10, 359–370 (2015).
Google Scholar 

79.
Zeng, Y. & Yeo, D. C. J. Assessing the aggregated risk of invasive crayfish and climate change to freshwater crabs: A Southeast Asian case study. Biol. Conserv. 223, 58–67 (2018).
Google Scholar 

80.
Alonso, F., Temino, C. & Diéguez-Uribeondo, J. Status of the white-clawed crayfish, Austropotamobius pallipes (Lereboullet, 1858), in Spain: Distribution and legislation. 31–53 (2000).

81.
Van Dyck, H. & Baguette, M. Dispersal behaviour in fragmented landscapes: Routine or special movements?. Basic Appl. Ecol. 6, 535–545 (2005).
Google Scholar 

82.
Rodrigues, A. S. L., Pilgrim, J. D., Lamoreux, J. F., Hoffmann, M. & Brooks, T. M. The value of the IUCN Red List for conservation. Trends Ecol. Evol. 21, 71–76 (2006).
PubMed  Google Scholar 

83.
Füreder, L., Gherardi, F. & Souty-Grosset, C. Austropotamobius torrentium. The IUCN Red List of Threatened Species 2010 e.T2431A9439449 https://doi.org/10.2305/IUCN.UK.2010-3.RLTS.T2431A9439449.en (2010). More

NEWS
10 September 2020

Fires are releasing record levels of carbon dioxide, partly because they are burning ancient peatlands that have been a carbon sink.

Alexandra Witze

Search for this author in:

Northern fires (like the one shown here in the Novosibirsk Region of south Siberia) released record-setting amounts of carbon dioxide this year.Credit: Kirill Kukhmar/TASS/Getty

Wildfires blazed along the Arctic Circle this summer, incinerating tundra, blanketing Siberian cities in smoke and capping the second extraordinary fire season in a row. By the time the fire season waned at the end of last month, the blazes had emitted a record 244 megatonnes of carbon dioxide — that’s 35% more than last year, which also set records. One culprit, scientists say, could be peatlands that are burning as the top of the world melts.
Peatlands are carbon-rich soils that accumulate as waterlogged plants slowly decay, sometimes over thousands of years. They are the most carbon-dense ecosystems on Earth; a typical northern peatland packs in roughly ten times as much carbon as a boreal forest. When peat burns, it releases its ancient carbon to the atmosphere, adding to the heat-trapping gases that cause climate change.

Nearly half the world’s peatland-stored carbon lies between 60 and 70 degrees north, along the Arctic Circle. The problem with this is that historically frozen carbon-rich soils are expected to thaw as the planet warms, making them even more vulnerable to wildfires and more likely to release large amounts of carbon. It’s a feedback loop: as peatlands release more carbon, global warming increases, which thaws more peat and causes more wildfires. A study published last month1 shows that northern peatlands could eventually shift from being a net sink for carbon to a net source of carbon, further accelerating climate change.
The unprecedented Arctic wildfires of 2019 and 2020 show that transformational shifts are already under way, says Thomas Smith, an environmental geographer at the London School of Economics and Political Science. “Alarming is the right term.”
Zombie fires
The fire season in the Arctic kicked off unusually early this year: as early as May, there were fires blazing north of the tree line in Siberia, which normally wouldn’t happen until around July. One reason is that temperatures in winter and spring were warmer than usual, priming the landscape to burn. It’s also possible that peat fires had been smouldering beneath the ice and snow all winter and then emerged, zombie-like, in the spring as the snow melted. Scientists have shown that this kind of low-temperature, flameless combustion can burn in peat and other organic matter, such as coal, for months or even years.
Because of the early start, individual Arctic wildfires have been burning for longer than usual, and “they’re starting much farther north than they used to — in landscapes that we thought were fire-resistant rather than fire-prone”, says Jessica McCarty, a geographer at Miami University in Oxford, Ohio.

Sources: Copernicus Atmosphere Monitoring Service/European Centre for Medium-Range Weather Forecasts; Hugelius, G. et al. Proc. Natl. Acad. Sci. USA 117, 20438–20446 (2020)

Researchers are now assessing just how bad this Arctic fire season was. The Russian Wildfires Remote Monitoring System catalogued 18,591 separate fires in Russia’s two easternmost districts, with a total of nearly 14 million hectares burnt, says Evgeny Shvetsov, a fire specialist at the Sukachev Institute of Forest, which is part of the Russian Academy of Sciences in Krasnoyarsk. Most of the burning happened in permafrost zones, where the ground is normally frozen year-round.
To estimate the record carbon dioxide emissions, scientists with the European Commission’s Copernicus Atmosphere Monitoring Service used satellites to study the wildfires’ locations and intensity, and then calculated how much fuel each had probably burnt. Yet even that is likely to be an underestimate, says Mark Parrington, an atmospheric scientist at the European Centre for Medium-Range Weather Forecasts in Reading, UK, who was involved in the analysis. Fires that burn in peatland can be too low-intensity for satellite sensors to capture.
The problem with peat
How much this year’s Arctic fires will affect global climate over the long term depends on what they burnt. That’s because peatlands, unlike boreal forest, do not regrow quickly after a fire, so the carbon released is permanently lost to the atmosphere.
Smith has calculated that about half of the Arctic wildfires in May and June were on peatlands — and that in many cases, the fires went on for days, suggesting that they were fuelled by thick layers of peat or other soil rich in organic matter.

And the August study1 found that there are nearly four million square kilometres of peatlands in northern latitudes. More of that than previously thought is frozen and shallow — and therefore vulnerable to thawing and drying out, says Gustaf Hugelius, a permafrost scientist at Stockholm University who led the investigation. He and his colleagues also found that although peatlands have been helping to cool the climate for thousands of years, by storing carbon as they accumulate, they will probably become a net source of carbon being released into the atmosphere — which could happen by the end of the century.
Fire risk in Siberia is predicted to increase as the climate warms2, but by many measures, the shift has already arrived, says Amber Soja, an environmental scientist who studies Arctic fires at the US National Institute of Aerospace in Hampton, Virginia. “What you would expect is already happening,” she says. “And in some cases faster than we would have expected.”

doi: 10.1038/d41586-020-02568-y

References

1.
Hugelius, G. et al. Proc. Natl Acad. Sci. USA 117, 20438–20446 (2020).

2.
Sherstyukov, B. G. & Sherstyukov, A. B. Russian Meteorol. Hydrol. 39, 292–301 (2014).

Download references

Latest on:

Atmospheric science

Climate change

Environmental sciences

An essential round-up of science news, opinion and analysis, delivered to your inbox every weekday.

Related Articles More

Total P and available P
Fertilizer application significantly (P  0.05). The highest increase in available P concentration in NPK + S treatment observed in the 60–100 cm soil depth, with the increase of 111% and 115% in 60–80 cm and 80–100 cm soil depths, respectively, over CK treatment.
Figure 2

Effect of long-term application of chemical fertilizer, organic manure, and straw on total phosphorus (P) and available P concentrations. * indicates significant difference at P  3.6%) was associated with OM treatment, especially at the 0–20 and 20–40 cm soil depths (Fig. 3). The PAC values under NPK, NPK + S and OM treatments increased by 7.6%, 4.5% and 11.5% in the 0–20 cm soil depth and 4.2%, 1.3%, and 5.8% in 20–40 cm soil depth, respectively as compared to the CK treatment. However, PAC value for soil depth below 40 cm showed the trend, NPK  More

NEWS AND VIEWS
09 September 2020

How can the decline in global biodiversity be reversed, given the need to supply food? Computer modelling provides a way to assess the effectiveness of combining various conservation and food-system interventions to tackle this issue.

Brett A. Bryan &

Brett A. Bryan is at the Centre for Integrative Ecology, Deakin University, Melbourne, Victoria 3125, Australia.
Contact

Search for this author in:

Carla L. Archibald

Carla L. Archibald is at the Centre for Integrative Ecology, Deakin University, Melbourne, Victoria 3125, Australia.

Search for this author in:

Nature is in trouble, and its plight will probably become even more precarious unless we do something about it1. Writing in Nature, Leclère et al.2 quantify what might be needed to reverse this deeply worrying path while also feeding people’s increasingly voracious appetites. The authors’ answer is to team ambitious conservation measures with food-system transformation in the hope of reversing the trend of global terrestrial biodiversity loss.

By nature, we mean the diversity of life that has evolved over billions of years to exist in dynamic balance with Earth’s biophysical environment and the ecosystems present. Nature contributes to human well-being in many ways, and the services it provides, such as carbon sequestration by plants or pollination by insects, could impose a vast cost if lost3. Although the slow and long-term decline of Earth’s biodiversity4 is often overshadowed by climate change, and more recently by the COVID-19 pandemic, the loss of biodiversity is no less of a risk than those posed by the other challenges. Many would argue that the effect of biodiversity losses could surpass the combined impacts of climate change and COVID-19.
More and more, the realization is growing that, as a planet, we are what we eat. Human demand for food is accelerating with the ever-increasing global population (projected to approach 10 billion by 2050), and each successive generation is wealthier and consumes more resource-intensive diets than did the previous one5. Trying to balance this rapidly rising demand against the limited amount of land available for crops and pasture sets agriculture and nature (Fig. 1) on a collision course6. As Leclère and colleagues show, a bold and integrated strategy is required immediately to turn this around.

Figure 1 | A bean field bordering a rainforest reserve near Sorriso, Brazil.Credit: Florian Plaucheur/AFP/Getty

Taking a long view out to the year 2100, Leclère et al. present a global modelling study assessing the ability of ambitious conservation and food-system intervention scenarios to reverse the decline, or, as they call it, “bending the curve”, of biodiversity losses resulting from changes in agricultural land use and management. Projections of future land use and biodiversity are uncertain, and when these models are combined, this uncertainty is compounded. One of the great innovations of Leclère and colleagues’ work is in embracing this uncertainty by combining an ensemble of four global land-use models and eight global biodiversity models and measuring the performance of future land-use scenarios in terms of higher-level model-independent metrics such as the amount of biodiversity loss avoided.
Importantly, the study also included a baseline (termed BASE) scenario — the world expected without interventions — and Leclère et al. used this to gauge the effectiveness of the intervention scenarios. Although it is not a focus of the paper, it’s worth pausing to ponder the sobering picture painted by this business-as-usual future largely bereft of birdsong and insect chirp.
Choosing to act now can make a difference to nature’s plight. Most (61%) of the model combinations run by the authors indicated that implementing ambitious conservation actions led to a positive uptick in the biodiversity curve by 2050. Such conservation actions included: extending the global conservation network by establishing protected nature reserves; restoring degraded land; and basing future land-use decisions on comprehensive landscape-level conservation planning. This comprehensive conservation strategy avoids more than half (an average of 58%) of the biodiversity losses expected if nothing is done, but also leads to a hike in food prices.

When conservation actions were teamed with a range of equally ambitious food-system interventions, the prognosis for global biodiversity in the model was improved further. Including both supply- and demand-side measures, these approaches included boosting agricultural yields, having an increasingly globalized food trade, reducing food waste by half, and the global adoption of healthy diets by halving meat consumption. These combined measures of conservation and food-systems actions avoided more than two-thirds of future biodiversity losses, with the integrated action portfolio (combining all actions) avoiding an average of 90% of future biodiversity losses. Almost all models predicted a biodiversity about-face by mid-century. These food-system measures also avoided adverse outcomes for food affordability.
Leclère and colleagues’ work complements the current global climate-change scenario framework (tools for future planning by governments and others, including scenarios called shared socio-economic pathways, which integrate future socio-economic projections with greenhouse-gas emissions), and represents the most comprehensive incorporation of biodiversity into this scenario framing7 so far. However, a major limitation of the present study is that it does not consider the potential impact of climate change on biodiversity. This raises an internal inconsistency because, on the one hand, the baseline scenario considers land-use, social and economic changes under approximately 4 °C of global heating by 21008, yet, on the other hand, it does not consider the profound effect of warming on plant and animal populations and the ecosystems they comprise9. Also absent from the models were other threats to biodiversity, including harvesting, hunting and invasive species10. Although Leclère and colleagues recognized these limitations and assigned them a high priority for future research, unfortunately for us all, omitting these key threats probably means that the authors’ estimates of biodiversity’s plight and the effectiveness of integrated global conservation and food-system action are overly optimistic. To truly bend the curve, Leclère and colleagues’ integrated portfolio will need to be substantially expanded to address the full range of threats to biodiversity.
Although the models say that a better future is possible, is the combination of the multiple ambitious conservation and food-system interventions considered by Leclère et al. a realistic possibility? Achieving each one of the conservation and food-system actions would require a monumental coordinated effort from all nations. And even if the global community were to get its act together in prioritizing conservation and food-system transformation, would such efforts come in time and be enough to save our planet’s natural legacy? We certainly hope so.

doi: 10.1038/d41586-020-02502-2

References

1.
Díaz, S. et al. Science 366, eaax3100 (2019).

2.
Leclère, D. et al. Nature https://doi.org/10.1038/s41586-020-2705-y (2020).

3.
Costanza, R. et al. Glob. Environ. Change Hum. Policy Dimens. 26, 152–158 (2014).

4.
Butchart, S. H. M. et al. Science 328, 1164–1168 (2010).

5.
Springmann, M. et al. Nature 562, 519–525 (2018).

6.
Montesino Pouzols, F. et al. Nature 516, 383–386 (2014).

7.
Kok, M. T. J. et al. Biol. Conserv. 221, 137–150 (2018).

8.
Leclère, D. et al. Towards Pathways Bending the Curve of Terrestrial Biodiversity Trends Within the 21st Century https://doi.org/10.22022/ESM/04-2018.15241 (Int. Inst. Appl. Syst. Analysis, 2018).

9.
Warren, R., Price, J., Graham, E., Forstenhaeusler, N. & VanDerWal, J. Science 360, 791–795 (2018).

10.
Driscoll, D. A. et al. Nature Ecol. Evol. 2, 775–781 (2018).

Download references

Latest on:

Agriculture

An essential round-up of science news, opinion and analysis, delivered to your inbox every weekday.

Related Articles More