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The World Economic Forum now ranks biodiversity loss as a top-five risk to the global economy, and the draft post-2020 Global Biodiversity Framework proposes an expansion of conservation areas to 30% of the earth’s surface by 2030 (hereafter the “30% target”), using protected areas (PAs) and other effective area-based conservation measures (OECMs). Two immediate concerns are how much a 30% target might cost and whether it will cause economic losses to the agriculture, forestry and fisheries sectors. Conservation areas also generate economic benefits (e.g. revenue from nature tourism and ecosystem services), making PAs/Nature an economic sector in their own right. If some economic sectors benefit but others experience a loss, high-level policy makers need to know the net impact on the wider economy, as well as on individual sectors. The current report, based on the work of over 100 economists/scientists, analyses the global economic implications of a 30% PA target for agriculture, forestry, fisheries, and the PA/nature sector itself. (OECMs were only defined by the CBD in 2018, too recently to economically model, but we include a qualitative treatment of them.) We carried out two analyses: a global financial one (concrete revenues and costs only); and a tropics- focused economic one (including non-monetary ecosystem service values), for multiple scenarios of how a 30% PA target might be implemented. Our financial analysis showed that expanding PAs to 30% would generate higher overall output (revenues) than non-expansion (an extra $64 billion-$454 billion per year by 2050). (Figure 1-2). In the economic analysis, only a partial assessment was possible, focusing on forests and mangroves. For those biomes alone, the 30% target had an avoided-loss value of $170-$534 billion per year by 2050, largely reflecting the benefit of avoiding the flooding, climate change, soil loss and coastal storm- surge damage that occur when natural vegetation is removed. The value for all biomes would be higher. Implementing the proposal would therefore make little initial difference to total (multi-sector) economic output, although a modest rise in gross output value is projected. The main immediate difference between expansion and non-expansion is therefore in broader economic/social values. Expansion outperforms non-expansion in mitigating the very large economic risks of climate change and biodiversity loss (Figure 5). The 30% target would also increase by 63%- 98% the area recognised as Indigenous Peoples’ and local communities’ land-based nature stewardship contribution (within appropriate rights and governance frameworks). Economic growth in the PA/nature sector (at 4-6%) was also many times faster than the 1% growth expected in competing sectors (Figure 3). Marine expansion restores growth to fisheries (after a shock) but non-expansion leads to a mid-term contraction (Figure 4). The annual investment needed for an expanded (30%) PA system is $103 – $178 billion1. This figure includes $68 billion for the existing system, of which only $24.3 is currently spent. (Underfunded systems lose revenue, assets, carbon and biodiversity). Most of the investment need is in low- and middle-income countries (LMICs). These often have a competitive asset advantage in terms of natural areas, but they may need international support to capitalise on that opportunity. Otherwise, growing the PA sector could also entrench global economic inequalities. Benefits and costs also accrue to different stakeholders at smaller (e.g. local) scales, making welfare distribution a challenge that needs addressing.

Older individuals living on the streets of our urban cities are a unique sub-group of the homeless population. No studies have been published about these elderly “rough sleepers” who face daunting obstacles to health care while facing a litany of health risks on the streets that are magnified by the physical and mental limitations of advancing years. To improve our understanding of this itinerant group, the Street Team of the Boston Health Care for the Homeless Program prospectively followed 30 individuals aged 60 or older living on Boston’s streets for the four-year period from 2000 through 2003. This cohort included 8 (27%) women and 22 (73%) men ranging in age from 60 to 82 years. The average age was 67 years old. At the end of the four year study period, 9 (30%) had died and 6 (20%) were in nursing homes. Despite intense efforts, only 5 (17%) found housing. Seven (23%) were still on Boston’s streets after four years, and one was lost to follow-up. We conclude that elderly rough sleepers have high morbidity and mortality and pose significant challenges to programs seeking to provide housing and supportive health care services for this vulnerable sub-group of elderly homeless persons. New and creative housing options are needed, and the delicate issues of competency and guardianship must be addressed.