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List of knowledge gaps on drivers identified from Chapter 3

Posted by patrick.meyfroidt on
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Last seen 12/02/2020
Joined 11/10/2016

This is a list of knowledge gaps identified on Drivers, taken from Chapter 3 (not exhaustive):

  • p. 186, l. 7249-7252: "The overall impact of these voluntary measures remains to be assessed but they offer a vital window of opportunity for reversing degradation trends and placing economies on a more sustainable footing - especially as large areas of marginal agricultural become increasingly abandoned with ongoing development (unresolved)."
  • p. 186, l. 7249-7252: "The overall impact of these voluntary measures remains to be assessed but they offer a vital window of opportunity for reversing degradation trends and placing economies on a more sustainable footing - especially as large areas of marginal agricultural become increasingly abandoned with ongoing development (unresolved)."
  • p. 192, l. 7420-7421: "Technological advances in livestock production systems have the potential to offset the increasing demand for animal products by increasing livestock production efficiency (Mario Herrero et al., 2013)."
  • p. 193, l. 7451-7453: "With further technological advances over the next several decades, reliance on natural grazing lands is expected to decline especially in regions such as Africa in which these advances will have the most impact on grazing practices (Alkemade et al., 2013)."
  • p. 197, l. 7547-7553: "Many studies have shown that modifying diets provides ample opportunities to meet societal demands without amplifying existing pressures on natural ecosystems (Bajželj, Richards, Allwood, & Smith, 2014; Cassidy, West, Gerber, & Foley, 2013; Herrero, Henderson, Havlík, & Thornton, 2016; Le Mouël et al., 2016; Mora et al., 2016), but very few studies have empirically investigated the possible effectiveness of policy options to modify dietary choices. Two studies on carbon taxes applied to meat consumption showed a possible sparing of 4 Mha with a tax of 60 € / tCO2eq (Wirsenius, Hedenus, & Mohlin, 2011) or a reduction of meat consumption by 5% for a tax of 80 $ / tCO2eq (Revell, 2015)."
  • p. 198-199, l. 7594-7600: "Changing dynamics of urban-rural interactions may modify households' resources (capital, labour force, information), possibly leading to the spread of institutional or technical innovations or to the development of niche crops that fulfil emerging culturally-driven demands from urban areas such as açai berries (Hecht, 2014) or argan oil (le Polain de Waroux & Chiche, 2013) or increasing land scarcity triggering diverse forms of tree-based land use intensification (Lambin & Meyfroidt, 2010; Meyfroidt & Lambin, 2011)"
  • p. 202, l. 7694-7698: "Debate on the merits of whether land for nature and for production should be segregated (land sparing) or integrated on the same land (land sharing, wildlife-friendly farming) continues but often fails to account for real world complexities (IPBES, 2017; Tscharntke et al., 2012). Conventional intensification often overlooks associated disruptions to natural systems resulting in pollinator loss or increases in pest species impacting on production (IPBES, 2016; Tscharntke et al., 2012)."
  • p. 203, l. 7747-7751: "Few studies have quantified the extent, drivers, or outcomes of land abandonment globally (Queiroz et al., 2014; Ramankutty & Foley 1999; Benayas et al., 2007) partly because of difficulties of measurement (Renwick et al., 2013). A key challenge is to disentangle multiple drivers, pathways and outcomes and, in particular, to separate cyclical, reversible and permanent processes of abandonment (Munroe et al., 2013)."
  • p. 213, l. 8148-8149: "Many extractive industries are located near areas of high or intermediate biodiversity, though the reason for this is unclear (Durán et al., 2013)."
  • p. 217, l. 8242-8247: "Changes in population densities of large metropolitan areas may also drive changes in infrastructure and industrial development. In a sampling of 120 large cities, population densities declined by 2% per year between 1990 and 2000 and these declines were associated with low-density urban/sub-urban expansion of those areas (i.e., urban sprawl) (Angel, Parent, & Civco, 2010). It is not clear whether these declines arise from administrative policies or as a consequence of consumer preferences combined with higher incomes, cheaper travel, and the ability to work remotely (Ewing, 2008)."
  • p. 219, l. 8318-8320: "A major difficulty in assessing changes in fire regimes are the challenges associated with characterizing ‘natural’ background fire regimes that have changed across millennia (Bowman et al., 2011)."
  • p. 233, l. 8794-8798: "Although information is currently lacking from several eco-regions in eastern and southern Asia, Mediterranean ecoregions in California and southern Europe, and several subtropical and tropical regions of Latin America and Africa, it is likely that most ecosystems are likely to be affected by future anthropogenically-driven changes in nitrogen and phosphorus availability (Bobbink et al., 2010)."
  • p. 235, l. 8846-8850: "Although underlying mechanisms are complex, such interactive effects are believed to be responsible for the bark beetle outbreaks in North America in recent decades, where millions of hectares of conifer forests have been killed from Mexico to Alaska (Figure 3.11) (Bentz et al., 2010; Raffa et al., 2008), and for observed range expansions of the coffee berry borer in East Africa (Jaramillo et al., 2011), amongst others."
  • p. 235, l. 8881-8885: "Although our understanding of climate change impacts on invasive species is far from complete (Hellmann et al., 2008; Smith et al., 2012), it is likely that climate-induced changes will further exacerbate the problems of invasive species in many areas (Bradley, 2010; Kriticos, Sutherst, Brown, Adkins, & Maywald, 2003; Ward & Masters, 2007; Ziska, Blumenthal, Runion, Hunt, & Diaz-Soltero, 2011)."
  • p. 241, l. 9027-9029: "Cultural factors, whilst often far less recognized and understood can have a powerful and long-lasting effect on how individuals and whole human communities and nations relate to both environmental opportunities and challenges."
  • p. 254, l. 9399-9401: "Part of the challenge also lies in the fact that estimates of uncertainty are rarely provided for maps of global land use and land cover (Keenan et al., 2015), and improvements are needed in how to estimate and represent uncertainties in spatial data."
  • p. 255, l. 9407-9411: "The development of commonly agreed indicators and approaches to mapping land degradation at different spatial scales, together with a concerted effort by a research community engaged in trans-disciplinary research that also engages non-scientific stakeholders to develop such datasets, would constitute a major advance in our understanding of priority areas for action, as well as the underlying drivers of observed patterns."
  • p. 255, l. 9412-9416: "Data on specific management practices such as levels of rotational grazing in pastures, levels of fertilizer and pesticide application in croplands, and harvesting intensities of timber and non-timber resources are much sparser and inconsistent."
  • p. 255, l. 9426-9432: "Research on the effectiveness of different strategies to land restoration and rehabilitation, including the underlying economic and policy levers necessary to implement such strategies, is still very much in its infancy. Systematic appraisals and meta-analyses focused on the cost-effectiveness of different restoration strategies are urgent research priorities, as are the development of commonly accepted conceptual and analytical frameworks for measuring success – where success includes interventions across the entire mitigation hierarchy, from avoided loss to the mitigation of impacts to the recovery and rehabilitation of degraded land."
  • p. 256, l. 9477-9481: "An integrated understanding of the role of indirect drivers then requires mixed method approaches that blend statistical analyses with scenario modelling, place-based empirical studies and qualitative research (e.g., Meyfroidt et al., 2013) and the inclusion of more targeted data on social, political and governance variables in land-use modelling work that have traditionally been dominated by natural scientists (e.g., McNeill et al., 2014)."

Patrick Meyfroidt

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