The proteome of cholesteryl-ester-enriched versus triacylglycerol-enriched lipid droplets

Within cells, lipids are stored in the form of lipid droplets (LDs), consisting of a neutral lipid core, surrounded by a phospholipid monolayer and an outer layer of protein. LDs typically accumulate either triacylglycerol (TAG) and diacylglycerol or cholesteryl ester (CE), depending on the type of tissue. Recently, there has been an increased interest in the proteins that surround LDs. LD proteins have been found to be quite diverse, from structural proteins to metabolic enzymes, proteins involved in vesicular transport, and proteins that may play a role in LD formation. Previous proteomics analyses have focused on TAG-enriched LDs, whereas CE-enriched LDs have been largely ignored. Our study has compared the LD proteins from CE-enriched LDs to TAG-enriched LDs in steroidogenic cells. In primary rat granulosa cells loaded with either HDL to produce CE-enriched LDs or fatty acids to produce TAG-enriched LDs, 61 proteins were found to be elevated in CE-enriched LDs and 40 proteins elevated in TAG-enriched LDs with 278 proteins in similar amounts. Protein expression was further validated by selected reaction monitoring (SRM) mass spectrometry (MS). SRM verified expression of 25 of 27 peptides that were previously detected by tandem mass tagging MS. Several proteins were confirmed to be elevated in CE-enriched LDs by SRM including the intermediate filament vimentin. This study is the first to compare the proteins found on CE-enriched LDs with TAG-enriched LDs and constitutes the first step in creating a better understanding of the proteins found on CE-enriched LDs in steroidogenic cells

Scotland’s biodiversity progress to 2020 Aichi Targets:Conserving genetic diversity- development of a national approach for addressing Aichi Biodiversity Target 13 that includes wild species

Aichi Target 13 (T13) focuses on the conservation of genetic diversity. •Major challenges in implementing T13 are that the type of genetic diversity to conserve is not clearly defined, and that key issues in genetic conservation vary across different sectors (e.g., forestry vs agriculture vs other species of socio-economic importance). •In Scotland and the UK more widely, baseline mechanisms are well established for assessing and reporting on genetic diversity in species of agricultural importance (e.g., rare livestock breeds, crop wild relatives), and a methodology has been established for ornamental plants. •A new UK Strategy for Forest Genetics Resources was launched in 2019, creating a framework for linking forest trees into T13 reporting. •However, there is no clear strategy to deal with ‘other species of socio-economic importance’ in Scotland, the UK or indeed elsewhere, and addressing this gap is the major focus of this report. •There is a lack of guidance for identifying focal species of socio-economic importance, and no clear mechanism for addressing T13 for these species once they have been identified. •To address this, we have identified a set of criteria for defining terrestrial and freshwater species of socio-economic importance in Scotland, and selected an initial list of 26 species. •The criteria applied were: -National conservation priority wild species. -Species of national cultural importance. -Species providing key ecosystem services. -Species of importance for wild harvesting (food and medicine). -Economically important game species. •We then developed a simple, readily applicable scorecard method for assessing risks to the conservation of genetic diversity in these species. •The scorecard approach is not dependent on prior genetic knowledge, and instead uses structured expert opinion assessments of whether: -Demographic declines are likely to lead to loss of genetic diversity (genetic erosion). -Hybridisation is likely to lead to undesirable replacement of genetic diversity. -Restrictions to regeneration/turnover are likely to impede evolutionary change. •For plant species where seed-banking is a viable mechanism for holding genetic resources ex situ,we also report on the representativeness of these ex situ collections. •Overall, this scorecard provides a mechanism for incorporating ‘other species of socio-economic importance’ into T13 actions and reporting. •Furthermore, its application is not restricted to Aichi T13 as the approach is designed as a generic scorecard for genetic diversity. It is thus relevant to post-2020 CBD targets focusing on genetic diversity. •Future priorities include: -Extension to other species of socio-economic, commercial and cultural importance (with the inclusion of marine species being a particularly high priority). -Harmonising genetic conservation strategies between sectors (drawing on commonalities), whilst minimising disruption of existing well-established methodologies within sectors. -Greater incorporation of genomic data into monitoring genetic diversity (particularly in the agricultural and forestry sectors where data availability is potentially high)

Land cover change and carbon emissions over 100 years in an African biodiversity hotspot

Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the pre-satellite era. Here we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo-referenced and digitised historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a five-fold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4-1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha(-1) yr(-1) . This is at least three-fold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8-5.7) Mg C ha(-1) , compared to a committed loss of 11.9 (7.2-16.6) Mg C ha(-1) within areas lacking such protection. Furthermore, for nine protected areas where LULCC data is available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics. This article is protected by copyright. All rights reserved

Inequitable gains and losses from conservation in a global biodiversity hotspot

A billion rural people live near tropical forests. Urban populations need them for water, energy and timber. Global society benefits from climate regulation and knowledge embodied in tropical biodiversity. Ecosystem service valuations can incentivise conservation, but determining costs and benefits across multiple stakeholders and interacting services is complex and rarely attempted. We report on a 10-year study, unprecedented in detail and scope, to determine the monetary value implications of conserving forests and woodlands in Tanzania’s Eastern Arc Mountains. Across plausible ranges of carbon price, agricultural yield and discount rate, conservation delivers net global benefits (+US$8.2B present value, 20-year central estimate). Crucially, however, net outcomes diverge widely across stakeholder groups. International stakeholders gain most from conservation (+US$10.1B), while local-rural communities bear substantial net costs (-US$1.9B), with greater inequities for more biologically important forests. Other Tanzanian stakeholders experience conflicting incentives: tourism, drinking water and climate regulation encourage conservation (+US$72M); logging, fuelwood and management costs encourage depletion (-US$148M). Substantial global investment in disaggregating and mitigating local costs (e.g., through boosting smallholder yields) is essential to equitably balance conservation and development objectives

Corporate Cash Holdings in the Shipping Industry

We examine the corporate cash holdings of listed shipping companies and show that shipping firms hold more cash than similar firms in other asset-heavy industries. Higher cash holdings in the shipping industry are not attributable to firm- or country-level characteristics, but rather to the higher marginal value of cash. Shipping firms value an additional dollar of cash higher than matched manufacturing firms, regardless of their financial constraints status, but depending on their cultural background and the cyclicality of their expansion opportunities. Less procyclical shipping firms have a higher marginal value of cash, and this valuation effect is most pronounced in bad times of the business cycle when external capital supply tends to becomescarce.Overall, it appears that shipping companies are more conservative than their peers in managing their cash positions

Adenosine Triphosphate Stimulates Aquifex aeolicus MutL Endonuclease Activity

BACKGROUND:Human PMS2 (hPMS2) homologues act to nick 5' and 3' to misincorporated nucleotides during mismatch repair in organisms that lack MutH. Mn(++) was previously found to stimulate the endonuclease activity of these homologues. ATP was required for the nicking activity of hPMS2 and yPMS1, but was reported to inhibit bacterial MutL proteins from Thermus thermophilus and Aquifex aeolicus that displayed homology to hPMS2. Mutational analysis has identified the DQHA(X)(2)E(X)(4)E motif present in the C-terminus of PMS2 homologues as important for endonuclease activity. METHODOLOGIES/PRINCIPAL FINDINGS:We examined the effect ATP had on the Mn(++) induced nicking of supercoiled pBR322 by full-length and mutant A. aeolicus MutL (Aae MutL) proteins. Assays were single time point, enzyme titration experiments or reaction time courses. The maximum velocity for MutL nicking was determined to be 1.6+/-0.08x10(-5) s(-1) and 4.2+/-0.3x10(-5) s(-1) in the absence and presence of ATP, respectively. AMPPNP stimulated the nicking activity to a similar extent as ATP. A truncated Aae MutL protein composed of only the C-terminal 123 amino acid residues was found to nick supercoiled DNA. Furthermore, mutations in the conserved C-terminal DQHA(X)(2)E(X)(4)E and CPHGRP motifs were shown to abolish Aae MutL endonuclease activity. CONCLUSIONS:ATP stimulated the Mn(++) induced endonuclease activity of Aae MutL. Experiments utilizing AMPPNP implied that the stimulation did not require ATP hydrolysis. A mutation in the DQHA(X)(2)E(X)(4)E motif of Aae MutL further supported the role of this region in endonclease activity. For the first time, to our knowledge, we demonstrate that changing the histidine residue in the conserved CPHGRP motif abolishes endonucleolytic activity of a hPMS2 homologue. Finally, the C-terminal 123 amino acid residues of Aae MutL were sufficient to display Mn(++) induced nicking activity

Effects of climate and atmospheric nitrogen deposition on early to mid-term stage litter decomposition across biomes

Litter decomposition is a key process for carbon and nutrient cycling in terrestrial ecosystems and is mainly controlled by environmental conditions, substrate quantity and quality as well as microbial community abundance and composition. In particular, the effects of climate and atmospheric nitrogen (N) deposition on litter decomposition and its temporal dynamics are of significant importance, since their effects might change over the course of the decomposition process. Within the TeaComposition initiative, we incubated Green and Rooibos teas at 524 sites across nine biomes. We assessed how macroclimate and atmospheric inorganic N deposition under current and predicted scenarios (RCP 2.6, RCP 8.5) might affect litter mass loss measured after 3 and 12 months. Our study shows that the early to mid-term mass loss at the global scale was affected predominantly by litter quality (explaining 73% and 62% of the total variance after 3 and 12 months, respectively) followed by climate and N deposition. The effects of climate were not litter-specific and became increasingly significant as decomposition progressed, with MAP explaining 2% and MAT 4% of the variation after 12 months of incubation. The effect of N deposition was litter-specific, and significant only for 12-month decomposition of Rooibos tea at the global scale. However, in the temperate biome where atmospheric N deposition rates are relatively high, the 12-month mass loss of Green and Rooibos teas decreased significantly with increasing N deposition, explaining 9.5% and 1.1% of the variance, respectively. The expected changes in macroclimate and N deposition at the global scale by the end of this century are estimated to increase the 12-month mass loss of easily decomposable litter by 1.1-3.5% and of the more stable substrates by 3.8-10.6%, relative to current mass loss. In contrast, expected changes in atmospheric N deposition will decrease the mid-term mass loss of high-quality litter by 1.4-2.2% and that of low-quality litter by 0.9-1.5% in the temperate biome. Our results suggest that projected increases in N deposition may have the capacity to dampen the climate-driven increases in litter decomposition depending on the biome and decomposition stage of substrate

Effects of Climate and Atmospheric Nitrogen Deposition on Early to Mid-Term Stage Litter Decomposition Across Biomes

open263siWe acknowledge support by the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Research Foundation (FZT 118), Scientific Grant Agency VEGA(GrantNo.2/0101/18), as well as by the European Research Council under the European Union’s Horizon 2020 Research and Innovation Program (Grant Agreement No. 677232)Litter decomposition is a key process for carbon and nutrient cycling in terrestrial ecosystems and is mainly controlled by environmental conditions, substrate quantity and quality as well as microbial community abundance and composition. In particular, the effects of climate and atmospheric nitrogen (N) deposition on litter decomposition and its temporal dynamics are of significant importance, since their effects might change over the course of the decomposition process. Within the TeaComposition initiative, we incubated Green and Rooibos teas at 524 sites across nine biomes. We assessed how macroclimate and atmospheric inorganic N deposition under current and predicted scenarios (RCP 2.6, RCP 8.5) might affect litter mass loss measured after 3 and 12 months. Our study shows that the early to mid-term mass loss at the global scale was affected predominantly by litter quality (explaining 73% and 62% of the total variance after 3 and 12 months, respectively) followed by climate and N deposition. The effects of climate were not litter-specific and became increasingly significant as decomposition progressed, with MAP explaining 2% and MAT 4% of the variation after 12 months of incubation. The effect of N deposition was litter-specific, and significant only for 12-month decomposition of Rooibos tea at the global scale. However, in the temperate biome where atmospheric N deposition rates are relatively high, the 12-month mass loss of Green and Rooibos teas decreased significantly with increasing N deposition, explaining 9.5% and 1.1% of the variance, respectively. The expected changes in macroclimate and N deposition at the global scale by the end of this century are estimated to increase the 12-month mass loss of easily decomposable litter by 1.1-3.5% and of the more stable substrates by 3.8-10.6%, relative to current mass loss. In contrast, expected changes in atmospheric N deposition will decrease the mid-term mass loss of high-quality litter by 1.4-2.2% and that of low-quality litter by 0.9-1.5% in the temperate biome. Our results suggest that projected increases in N deposition may have the capacity to dampen the climate-driven increases in litter decomposition depending on the biome and decomposition stage of substrate.openKwon T.; Shibata H.; Kepfer-Rojas S.; Schmidt I.K.; Larsen K.S.; Beier C.; Berg B.; Verheyen K.; Lamarque J.-F.; Hagedorn F.; Eisenhauer N.; Djukic I.; Caliman A.; Paquette A.; Gutierrez-Giron A.; Petraglia A.; Augustaitis A.; Saillard A.; Ruiz-Fernandez A.C.; Sousa A.I.; Lillebo A.I.; Da Rocha Gripp A.; Lamprecht A.; Bohner A.; Francez A.-J.; Malyshev A.; Andric A.; Stanisci A.; Zolles A.; Avila A.; Virkkala A.-M.; Probst A.; Ouin A.; Khuroo A.A.; Verstraeten A.; Stefanski A.; Gaxiola A.; Muys B.; Gozalo B.; Ahrends B.; Yang B.; Erschbamer B.; Rodriguez Ortiz C.E.; Christiansen C.T.; Meredieu C.; Mony C.; Nock C.; Wang C.-P.; Baum C.; Rixen C.; Delire C.; Piscart C.; Andrews C.; Rebmann C.; Branquinho C.; Jan D.; Wundram D.; Vujanovic D.; Adair E.C.; Ordonez-Regil E.; Crawford E.R.; Tropina E.F.; Hornung E.; Groner E.; Lucot E.; Gacia E.; Levesque E.; Benedito E.; Davydov E.A.; Bolzan F.P.; Maestre F.T.; Maunoury-Danger F.; Kitz F.; Hofhansl F.; Hofhansl G.; De Almeida Lobo F.; Souza F.L.; Zehetner F.; Koffi F.K.; Wohlfahrt G.; Certini G.; Pinha G.D.; Gonzlez G.; Canut G.; Pauli H.; Bahamonde H.A.; Feldhaar H.; Jger H.; Serrano H.C.; Verheyden H.; Bruelheide H.; Meesenburg H.; Jungkunst H.; Jactel H.; Kurokawa H.; Yesilonis I.; Melece I.; Van Halder I.; Quiros I.G.; Fekete I.; Ostonen I.; Borovsk J.; Roales J.; Shoqeir J.H.; Jean-Christophe Lata J.; Probst J.-L.; Vijayanathan J.; Dolezal J.; Sanchez-Cabeza J.-A.; Merlet J.; Loehr J.; Von Oppen J.; Loffler J.; Benito Alonso J.L.; Cardoso-Mohedano J.-G.; Penuelas J.; Morina J.C.; Quinde J.D.; Jimnez J.J.; Alatalo J.M.; Seeber J.; Kemppinen J.; Stadler J.; Kriiska K.; Van Den Meersche K.; Fukuzawa K.; Szlavecz K.; Juhos K.; Gerhtov K.; Lajtha K.; Jennings K.; Jennings J.; Ecology P.; Hoshizaki K.; Green K.; Steinbauer K.; Pazianoto L.; Dienstbach L.; Yahdjian L.; Williams L.J.; Brigham L.; Hanna L.; Hanna H.; Rustad L.; Morillas L.; Silva Carneiro L.; Di Martino L.; Villar L.; Fernandes Tavares L.A.; Morley M.; Winkler M.; Lebouvier M.; Tomaselli M.; Schaub M.; Glushkova M.; Torres M.G.A.; De Graaff M.-A.; Pons M.-N.; Bauters M.; Mazn M.; Frenzel M.; Wagner M.; Didion M.; Hamid M.; Lopes M.; Apple M.; Weih M.; Mojses M.; Gualmini M.; Vadeboncoeur M.; Bierbaumer M.; Danger M.; Scherer-Lorenzen M.; Ruek M.; Isabellon M.; Di Musciano M.; Carbognani M.; Zhiyanski M.; Puca M.; Barna M.; Ataka M.; Luoto M.; H. Alsafaran M.; Barsoum N.; Tokuchi N.; Korboulewsky N.; Lecomte N.; Filippova N.; Hlzel N.; Ferlian O.; Romero O.; Pinto-Jr O.; Peri P.; Dan Turtureanu P.; Haase P.; Macreadie P.; Reich P.B.; Petk P.; Choler P.; Marmonier P.; Ponette Q.; Dettogni Guariento R.; Canessa R.; Kiese R.; Hewitt R.; Weigel R.; Kanka R.; Cazzolla Gatti R.; Martins R.L.; Ogaya R.; Georges R.; Gaviln R.G.; Wittlinger S.; Puijalon S.; Suzuki S.; Martin S.; Anja S.; Gogo S.; Schueler S.; Drollinger S.; Mereu S.; Wipf S.; Trevathan-Tackett S.; Stoll S.; Lfgren S.; Trogisch S.; Seitz S.; Glatzel S.; Venn S.; Dousset S.; Mori T.; Sato T.; Hishi T.; Nakaji T.; Jean-Paul T.; Camboulive T.; Spiegelberger T.; Scholten T.; Mozdzer T.J.; Kleinebecker T.; Runk T.; Ramaswiela T.; Hiura T.; Enoki T.; Ursu T.-M.; Di Cella U.M.; Hamer U.; Klaus V.; Di Cecco V.; Rego V.; Fontana V.; Piscov V.; Bretagnolle V.; Maire V.; Farjalla V.; Pascal V.; Zhou W.; Luo W.; Parker W.; Parker P.; Kominam Y.; Kotrocz Z.; Utsumi Y.Kwon T.; Shibata H.; Kepfer-Rojas S.; Schmidt I.K.; Larsen K.S.; Beier C.; Berg B.; Verheyen K.; Lamarque J.-F.; Hagedorn F.; Eisenhauer N.; Djukic I.; Caliman A.; Paquette A.; Gutierrez-Giron A.; Petraglia A.; Augustaitis A.; Saillard A.; Ruiz-Fernandez A.C.; Sousa A.I.; Lillebo A.I.; Da Rocha Gripp A.; Lamprecht A.; Bohner A.; Francez A.-J.; Malyshev A.; Andric A.; Stanisci A.; Zolles A.; Avila A.; Virkkala A.-M.; Probst A.; Ouin A.; Khuroo A.A.; Verstraeten A.; Stefanski A.; Gaxiola A.; Muys B.; Gozalo B.; Ahrends B.; Yang B.; Erschbamer B.; Rodriguez Ortiz C.E.; Christiansen C.T.; Meredieu C.; Mony C.; Nock C.; Wang C.-P.; Baum C.; Rixen C.; Delire C.; Piscart C.; Andrews C.; Rebmann C.; Branquinho C.; Jan D.; Wundram D.; Vujanovic D.; Adair E.C.; Ordonez-Regil E.; Crawford E.R.; Tropina E.F.; Hornung E.; Groner E.; Lucot E.; Gacia E.; Levesque E.; Benedito E.; Davydov E.A.; Bolzan F.P.; Maestre F.T.; Maunoury-Danger F.; Kitz F.; Hofhansl F.; Hofhansl G.; De Almeida Lobo F.; Souza F.L.; Zehetner F.; Koffi F.K.; Wohlfahrt G.; Certini G.; Pinha G.D.; Gonzlez G.; Canut G.; Pauli H.; Bahamonde H.A.; Feldhaar H.; Jger H.; Serrano H.C.; Verheyden H.; Bruelheide H.; Meesenburg H.; Jungkunst H.; Jactel H.; Kurokawa H.; Yesilonis I.; Melece I.; Van Halder I.; Quiros I.G.; Fekete I.; Ostonen I.; Borovsk J.; Roales J.; Shoqeir J.H.; Jean-Christophe Lata J.; Probst J.-L.; Vijayanathan J.; Dolezal J.; Sanchez-Cabeza J.-A.; Merlet J.; Loehr J.; Von Oppen J.; Loffler J.; Benito Alonso J.L.; Cardoso-Mohedano J.-G.; Penuelas J.; Morina J.C.; Quinde J.D.; Jimnez J.J.; Alatalo J.M.; Seeber J.; Kemppinen J.; Stadler J.; Kriiska K.; Van Den Meersche K.; Fukuzawa K.; Szlavecz K.; Juhos K.; Gerhtov K.; Lajtha K.; Jennings K.; Jennings J.; Ecology P.; Hoshizaki K.; Green K.; Steinbauer K.; Pazianoto L.; Dienstbach L.; Yahdjian L.; Williams L.J.; Brigham L.; Hanna L.; Hanna H.; Rustad L.; Morillas L.; Silva Carneiro L.; Di Martino L.; Villar L.; Fernandes Tavares L.A.; Morley M.; Winkler M.; Lebouvier M.; Tomaselli M.; Schaub M.; Glushkova M.; Torres M.G.A.; De Graaff M.-A.; Pons M.-N.; Bauters M.; Mazn M.; Frenzel M.; Wagner M.; Didion M.; Hamid M.; Lopes M.; Apple M.; Weih M.; Mojses M.; Gualmini M.; Vadeboncoeur M.; Bierbaumer M.; Danger M.; Scherer-Lorenzen M.; Ruek M.; Isabellon M.; Di Musciano M.; Carbognani M.; Zhiyanski M.; Puca M.; Barna M.; Ataka M.; Luoto M.; H. Alsafaran M.; Barsoum N.; Tokuchi N.; Korboulewsky N.; Lecomte N.; Filippova N.; Hlzel N.; Ferlian O.; Romero O.; Pinto-Jr O.; Peri P.; Dan Turtureanu P.; Haase P.; Macreadie P.; Reich P.B.; Petk P.; Choler P.; Marmonier P.; Ponette Q.; Dettogni Guariento R.; Canessa R.; Kiese R.; Hewitt R.; Weigel R.; Kanka R.; Cazzolla Gatti R.; Martins R.L.; Ogaya R.; Georges R.; Gaviln R.G.; Wittlinger S.; Puijalon S.; Suzuki S.; Martin S.; Anja S.; Gogo S.; Schueler S.; Drollinger S.; Mereu S.; Wipf S.; Trevathan-Tackett S.; Stoll S.; Lfgren S.; Trogisch S.; Seitz S.; Glatzel S.; Venn S.; Dousset S.; Mori T.; Sato T.; Hishi T.; Nakaji T.; Jean-Paul T.; Camboulive T.; Spiegelberger T.; Scholten T.; Mozdzer T.J.; Kleinebecker T.; Runk T.; Ramaswiela T.; Hiura T.; Enoki T.; Ursu T.-M.; Di Cella U.M.; Hamer U.; Klaus V.; Di Cecco V.; Rego V.; Fontana V.; Piscov V.; Bretagnolle V.; Maire V.; Farjalla V.; Pascal V.; Zhou W.; Luo W.; Parker W.; Parker P.; Kominam Y.; Kotrocz Z.; Utsumi Y

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Summary • Tropical forest degradation is widely recognised as a driver of biodiversity loss and a major source of carbon emissions. However, in contrast to deforestation, the more gradual changes from degradation are challenging to detect, quantify, and monitor. Here we present a field protocol for rapid, area-standardised quantifications of forest condition, which can also be done by non-specialists. Using the example of threatened high-biodiversity forests in Tanzania, we analyse and predict degradation based on this method. We also compare the field data to optical and radar remote sensing datasets, thereby conducting a large-scale, independent test of the ability of these products to map degradation in East Africa from space. • Our field data consist of 551 ‘degradation’ transects collected between 1996 and 2010, covering >600 ha across 86 forests in the Eastern Arc Mountains and coastal forests. • Degradation was widespread, with over one third of the study forests – mostly protected areas – having more than 10% of their trees cut. Commonly-used optical remote-sensing maps of complete tree cover loss only detected severe impacts (≥25% of trees cut), i.e. a focus on remotely sensed deforestation would have significantly underestimated carbon emissions and declines in forest quality. Radar-based maps detected even low impacts (<5% of trees cut) in ~90% of cases. The field data additionally allowed to differentiate different types and drivers of harvesting, with spatial patterns suggesting that logging and charcoal production were mainly driven by demand from major cities. • Rapid degradation surveys and radar remote sensing can provide an early warning and guide appropriate conservation and policy responses. This is particularly important in areas where forest degradation is more widespread than deforestation, such as in east and southern Africa