Bending the curve of terrestrial biodiversity needs an integrated strategy Summary paragraph Increased efforts are required to prevent further losses of terrestrial biodiversity and the ecosystem services it provides 1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity 3-yet, just feeding the growing human population will make this a challenge 4. We use an ensemble of land-use and biodiversity models to assess whether (and if so, how) humanity can reverse terrestrial biodiversity declines due to habitat conversion, a major threat to biodiversity 5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, may allow to feed the growing human population while reversing global terrestrial biodiversity trends from habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land, and generalize landscapelevel conservation planning, biodiversity trends from habitat conversion could become positive by mid-century on average across models (confidence interval: 2042-2061), but not for all models. Food prices could increase and, on average across models, almost half (confidence interval: 34-50%) of future biodiversity losses could not be avoided. However, additionally tackling the drivers of landuse change may avoid conflict with affordable food provision and reduces the food system's environmental impacts. Through further sustainable intensification and trade, reduced food waste, and healthier human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats, such as climate change, must be addressed to truly reverse biodiversity declines, our results show that bold conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy. Reversing biodiversity trends by 2050 Without further efforts to counteract habitat loss and degradation, we projected that global biodiversity will continue to decline (BASE scenario; Fig. 1). Rates of loss over time for all nine BDIs in 2010-2050 were close to or greater than those estimated for 1970-2010 (Extended data Extended Data Table 1). For various biodiversity aspects, on average across IAM and BDI combinations, peak losses over the 2010-2100 period were: 13% (range: 1-26%) for the extent of suitable habitat, 54% (range: 45-63%) for wildlife population density, 5% (range: 2-9%) for local compositional intactness , 4% (range: 1-12%) for global extinctions, and 4% (range: 2-8%) for regional extinctions (Extended Data Table 1). Percentage losses were greatest in biodiversity-rich regions (Sub-Saharan Africa, South Asia, South East Asia, the Caribbean and Latin America; Extended Data Fig. 2). The projected future trends for habitat loss and degradation and its driv...

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) -SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6 -to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

Abstract. Most scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS – carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0.5∘×0.5∘ spatial resolution. We also provide a combined “best bioenergy crop” yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 t DM ha−1 yr−1 (DM – dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are > 50 % higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0.5∘×0.5∘ global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019).

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%.

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.