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4. Long-term thermal sensitivity of Earth's tropical forests

Author

Sullivan, M.J.P., Lewis, S.L., Affum-Baffoe, K., Castilho, C., Costa, F., Sanchez, A.C., Ewango, C.E.N., Hubau, W., Marimon, B., Monteagudo-Mendoza, A., Qie, L., Sonké, B., Martinez, R.V., Baker, T.R., Brienen, R.J.W., Feldpausch, T.R., Galbraith, D., Gloor, M., Malhi, Y., Aiba, S.-I., Alexiades, M.N., Almeida, E.C., de Oliveira, E.A., Dávila, E.Á., Loayza, P.A., Andrade, A., Vieira, S.A., Aragão, L.E.O.C., Araujo-Murakami, A., Arets, E.J.M.M., Arroyo, L., Ashton, P., Aymard C, G., Baccaro, F.B., Banin, L.F., Baraloto, C., Camargo, P.B., Barlow, J., Barroso, J., Bastin, J.-F., Batterman, S.A., Beeckman, H., Begne, S.K., Bennett, A.C., Berenguer, E., Berry, N., Blanc, L., Boeckx, P., Bogaert, J., Bonal, D., Bongers, F., Bradford, M., Brearley, F.Q., Brncic, T., Brown, F., Burban, B., Camargo, J.L., Castro, W., Céron, C., Ribeiro, S.C., Moscoso, V.C., Chave, J., Chezeaux, E., Clark, C.J., de Souza, F.C., Collins, M., Comiskey, J.A., Valverde, F.C., Medina, M.C., da Costa, L., Dančák, M., Dargie, G.C., Davies, S., Cardozo, N.D., de Haulleville, T., de Medeiros, M.B., Del Aguila Pasquel, J., Derroire, G., Di Fiore, A., Doucet, J.-L., Dourdain, A., Droissant, V., Duque, L.F., Ekoungoulou, R., Elias, F., Erwin, T., Esquivel-Muelbert, A., Fauset, S., Ferreira, J., Llampazo, G.F., Foli, E., Ford, A., Gilpin, M., Hall, J.S., Hamer, K.C., Hamilton, A.C., Harris, D.J., Hart, T.B., Hédl, R., Herault, B., Herrera, R., Higuchi, N., Hladik, A., Coronado, E.H., Huamantupa-Chuquimaco, I., Huasco, W.H., Jeffery, K.J., Jimenez-Rojas, E., Kalamandeen, M., Djuikouo, M.N.K., Kearsley, E., Umetsu, R.K., Kho, L.K., Killeen, T., Kitayama, K., Klitgaard, B., Koch, A., Labrière, N., Laurance, W., Laurance, S., Leal, M.E., Levesley, A., Lima, A.J.N., Lisingo, J., Lopes, A.P., Lopez-Gonzalez, G., Lovejoy, T., Lovett, J.C., Lowe, R., Magnusson, W.E., Malumbres-Olarte, J., Manzatto, ÂG., Marimon B.H., Jr, Marshall, A.R., Marthews, T., de Almeida Reis, S.M., Maycock, C., Melgaço, K., Mendoza, C., Metali, F., Mihindou, V., Milliken, W., Mitchard, E.T.A., Morandi, P.S., Mossman, H.L., Nagy, L., Nascimento, H., Neill, D., Nilus, R., Vargas, P.N., Palacios, W., Camacho, N.P., Peacock, J., Pendry, C., Peñuela Mora, M.C., Pickavance, G.C., Pipoly, J., Pitman, N., Playfair, M., Poorter, L., Poulsen, J.R., Poulsen, A.D., Preziosi, R., Prieto, A., Primack, R.B., Ramírez-Angulo, H., Reitsma, J., Réjou-Méchain, M., Correa, Z.R., de Sousa, T.R., Bayona, L.R., Roopsind, A., Rudas, A., Rutishauser, E., Abu Salim, K., Salomão, R.P., Schietti, J., Sheil, D., Silva, R.C., Espejo, J.S., Valeria, C.S., Silveira, M., Simo-Droissart, M., Simon, M.F., Singh, J., Soto Shareva, Y.C., Stahl, C., Stropp, J., Sukri, R., Sunderland, T., Svátek, M., Swaine, M.D., Swamy, V., Taedoumg, H., Talbot, J., Taplin, J., Taylor, D., Ter Steege, H., Terborgh, J., Thomas, R., Thomas, S.C., Torres-Lezama, A., Umunay, P., Gamarra, L.V., van der Heijden, G., van der Hout, P., van der Meer, P., van Nieuwstadt, M., Verbeeck, H., Vernimmen, R., Vicentini, A., Vieira, I.C.G., Torre, E.V., Vleminckx, J., Vos, V., Wang, O., White, L.J.T., Willcock, S., Woods, J.T., Wortel, V., Young, K., Zagt, R., Zemagho, L., Zuidema, P.A., Zwerts, J.A., Phillips, O.L., Sullivan, M.J.P., Lewis, S.L., Affum-Baffoe, K., Castilho, C., Costa, F., Sanchez, A.C., Ewango, C.E.N., Hubau, W., Marimon, B., Monteagudo-Mendoza, A., Qie, L., Sonké, B., Martinez, R.V., Baker, T.R., Brienen, R.J.W., Feldpausch, T.R., Galbraith, D., Gloor, M., Malhi, Y., Aiba, S.-I., Alexiades, M.N., Almeida, E.C., de Oliveira, E.A., Dávila, E.Á., Loayza, P.A., Andrade, A., Vieira, S.A., Aragão, L.E.O.C., Araujo-Murakami, A., Arets, E.J.M.M., Arroyo, L., Ashton, P., Aymard C, G., Baccaro, F.B., Banin, L.F., Baraloto, C., Camargo, P.B., Barlow, J., Barroso, J., Bastin, J.-F., Batterman, S.A., Beeckman, H., Begne, S.K., Bennett, A.C., Berenguer, E., Berry, N., Blanc, L., Boeckx, P., Bogaert, J., Bonal, D., Bongers, F., Bradford, M., Brearley, F.Q., Brncic, T., Brown, F., Burban, B., Camargo, J.L., Castro, W., Céron, C., Ribeiro, S.C., Moscoso, V.C., Chave, J., Chezeaux, E., Clark, C.J., de Souza, F.C., Collins, M., Comiskey, J.A., Valverde, F.C., Medina, M.C., da Costa, L., Dančák, M., Dargie, G.C., Davies, S., Cardozo, N.D., de Haulleville, T., de Medeiros, M.B., Del Aguila Pasquel, J., Derroire, G., Di Fiore, A., Doucet, J.-L., Dourdain, A., Droissant, V., Duque, L.F., Ekoungoulou, R., Elias, F., Erwin, T., Esquivel-Muelbert, A., Fauset, S., Ferreira, J., Llampazo, G.F., Foli, E., Ford, A., Gilpin, M., Hall, J.S., Hamer, K.C., Hamilton, A.C., Harris, D.J., Hart, T.B., Hédl, R., Herault, B., Herrera, R., Higuchi, N., Hladik, A., Coronado, E.H., Huamantupa-Chuquimaco, I., Huasco, W.H., Jeffery, K.J., Jimenez-Rojas, E., Kalamandeen, M., Djuikouo, M.N.K., Kearsley, E., Umetsu, R.K., Kho, L.K., Killeen, T., Kitayama, K., Klitgaard, B., Koch, A., Labrière, N., Laurance, W., Laurance, S., Leal, M.E., Levesley, A., Lima, A.J.N., Lisingo, J., Lopes, A.P., Lopez-Gonzalez, G., Lovejoy, T., Lovett, J.C., Lowe, R., Magnusson, W.E., Malumbres-Olarte, J., Manzatto, ÂG., Marimon B.H., Jr, Marshall, A.R., Marthews, T., de Almeida Reis, S.M., Maycock, C., Melgaço, K., Mendoza, C., Metali, F., Mihindou, V., Milliken, W., Mitchard, E.T.A., Morandi, P.S., Mossman, H.L., Nagy, L., Nascimento, H., Neill, D., Nilus, R., Vargas, P.N., Palacios, W., Camacho, N.P., Peacock, J., Pendry, C., Peñuela Mora, M.C., Pickavance, G.C., Pipoly, J., Pitman, N., Playfair, M., Poorter, L., Poulsen, J.R., Poulsen, A.D., Preziosi, R., Prieto, A., Primack, R.B., Ramírez-Angulo, H., Reitsma, J., Réjou-Méchain, M., Correa, Z.R., de Sousa, T.R., Bayona, L.R., Roopsind, A., Rudas, A., Rutishauser, E., Abu Salim, K., Salomão, R.P., Schietti, J., Sheil, D., Silva, R.C., Espejo, J.S., Valeria, C.S., Silveira, M., Simo-Droissart, M., Simon, M.F., Singh, J., Soto Shareva, Y.C., Stahl, C., Stropp, J., Sukri, R., Sunderland, T., Svátek, M., Swaine, M.D., Swamy, V., Taedoumg, H., Talbot, J., Taplin, J., Taylor, D., Ter Steege, H., Terborgh, J., Thomas, R., Thomas, S.C., Torres-Lezama, A., Umunay, P., Gamarra, L.V., van der Heijden, G., van der Hout, P., van der Meer, P., van Nieuwstadt, M., Verbeeck, H., Vernimmen, R., Vicentini, A., Vieira, I.C.G., Torre, E.V., Vleminckx, J., Vos, V., Wang, O., White, L.J.T., Willcock, S., Woods, J.T., Wortel, V., Young, K., Zagt, R., Zemagho, L., Zuidema, P.A., Zwerts, J.A., and Phillips, O.L.

Abstract

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate.

Published
2020

6. Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Author

Wijedasa, LS, Jauhiainen, J, Kononen, M, Lampela, M, Vasander, H, Leblanc, MC, Evers, S, Smith, TEL, Yule, CM, Varkkey, H, Lupascu, M, Parish, F, Singleton, I, Clements, GR, Aziz, SA, Harrison, ME, Cheyne, S, Anshari, GZ, Meijaard, E, Goldstein, JE, Waldron, S, Hergoualc'h, K, Dommain, R, Frolking, S, Evans, CD, Posa, MRC, Glaser, PH, Suryadiputra, N, Lubis, R, Santika, T, Padfield, R, Kurnianto, S, Hadisiswoyo, P, Lim, TW, Page, SE, Gauci, V, Van der Meer, PJ, Buckland, H, Garnier, F, Samuel, MK, Choo, LNLK, O'Reilly, P, Warren, M, Suksuwan, S, Sumarga, E, Jain, A, Laurance, WF, Couwenberg, J, Joosten, H, Vernimmen, R, Hooijer, A, Malins, C, Cochrane, MA, Perumal, B, Siegert, F, Peh, KSH, Corneau, LP, Verchot, L, Harvey, CF, Cobb, A, Jaafar, Z, Wosten, H, Manuri, S, Muller, M, Giesen, W, Phelps, J, Yong, DL, Silvius, M, Wedeux, BMM, Hoyt, A, Osaki, M, Hirano, T, Takahashi, H, Kohyama, TS, Haraguchi, A, Nugroho, NP, Coomes, DA, Quoi, LP, Dohong, A, Gunawan, H, Gaveau, DLA, Langner, A, Lim, FKS, Edwards, DP, Giam, X, Van der Werf, G, Carmenta, R, Verwer, CC, Gibson, L, Grandois, L, Graham, LLB, Regalino, J, Wich, SA, Rieley, J, Kettridge, N, Brown, C, Pirard, R, Moore, S, Capilla, BR, Ballhorn, U, Ho, HC, Hoscilo, A, Lohberger, S, Evans, TA, Yulianti, N, Blackham, G, Onrizal, Husson, S, Murdiyarso, D, Pangala, S, Cole, LES, Tacconi, L, Segah, H, Tonoto, P, Lee, JSH, Schmilewski, G, Wulffraat, S, Putra, EI, Cattau, ME, Clymo, RS, Morrison, R, Mujahid, A, Miettinen, J, Liew, SC, Valpola, S, Wilson, D, D'Arcy, L, Gerding, M, Sundari, S, Thornton, SA, Kalisz, B, Chapman, SJ, Su, ASM, Basuki, I, Itoh, M, Traeholt, C, Sloan, S, Sayok, AK, Andersen, R, Wijedasa, LS, Jauhiainen, J, Kononen, M, Lampela, M, Vasander, H, Leblanc, MC, Evers, S, Smith, TEL, Yule, CM, Varkkey, H, Lupascu, M, Parish, F, Singleton, I, Clements, GR, Aziz, SA, Harrison, ME, Cheyne, S, Anshari, GZ, Meijaard, E, Goldstein, JE, Waldron, S, Hergoualc'h, K, Dommain, R, Frolking, S, Evans, CD, Posa, MRC, Glaser, PH, Suryadiputra, N, Lubis, R, Santika, T, Padfield, R, Kurnianto, S, Hadisiswoyo, P, Lim, TW, Page, SE, Gauci, V, Van der Meer, PJ, Buckland, H, Garnier, F, Samuel, MK, Choo, LNLK, O'Reilly, P, Warren, M, Suksuwan, S, Sumarga, E, Jain, A, Laurance, WF, Couwenberg, J, Joosten, H, Vernimmen, R, Hooijer, A, Malins, C, Cochrane, MA, Perumal, B, Siegert, F, Peh, KSH, Corneau, LP, Verchot, L, Harvey, CF, Cobb, A, Jaafar, Z, Wosten, H, Manuri, S, Muller, M, Giesen, W, Phelps, J, Yong, DL, Silvius, M, Wedeux, BMM, Hoyt, A, Osaki, M, Hirano, T, Takahashi, H, Kohyama, TS, Haraguchi, A, Nugroho, NP, Coomes, DA, Quoi, LP, Dohong, A, Gunawan, H, Gaveau, DLA, Langner, A, Lim, FKS, Edwards, DP, Giam, X, Van der Werf, G, Carmenta, R, Verwer, CC, Gibson, L, Grandois, L, Graham, LLB, Regalino, J, Wich, SA, Rieley, J, Kettridge, N, Brown, C, Pirard, R, Moore, S, Capilla, BR, Ballhorn, U, Ho, HC, Hoscilo, A, Lohberger, S, Evans, TA, Yulianti, N, Blackham, G, Onrizal, Husson, S, Murdiyarso, D, Pangala, S, Cole, LES, Tacconi, L, Segah, H, Tonoto, P, Lee, JSH, Schmilewski, G, Wulffraat, S, Putra, EI, Cattau, ME, Clymo, RS, Morrison, R, Mujahid, A, Miettinen, J, Liew, SC, Valpola, S, Wilson, D, D'Arcy, L, Gerding, M, Sundari, S, Thornton, SA, Kalisz, B, Chapman, SJ, Su, ASM, Basuki, I, Itoh, M, Traeholt, C, Sloan, S, Sayok, AK, and Andersen, R

Abstract

Letter

Published
2017

8. NHI Toetsing, Ontwikkeling en toepassing van methode voor toetsing van NHI 2.1 inclusief vergelijking met NHI 2.0

Author

Hoogewoud, J., Veldhuizen, A.A., Prinsen, G., Kuijper, M.J.M., Huinink, J., Lourens, A., and Vernimmen, R.

Subjects
oppervlaktewater, groundwater, grondwater, surface water, hydrology, Wageningen Environmental Research, CWC - Integrated Water Resources Management, CWK - Integraal Waterbeheer, information systems, hydrologie, informatiesystemen
Abstract

Dit rapport beschrijft de achtergrond van de methode om NHI2.1 te toetsen aan de criteria die opgesteld zijn door Rijkswaterstaat Waterdienst geldend voor 2010 en bevat de resultaten van die toetsing en de vergelijking met resultaten van NHI2.0. Volgens de criteria is de berekende aan en afvoer van oppervlakte water verbeterd. Op enkele belangrijke meetpunten van de oppervlaktewaterverdeling zijn signifinante verbeteringen te zien.

Published
2011

9. Drought Forecasting System of the Netherlands

Author

Hydrologie, Landscape functioning, Geocomputation and Hydrology, Weerts, A. H., Berendrecht, W. L., Veldhuizen, A., Goorden, N., Vernimmen, R., Lourens, A., Prinsen, G., Mulder, M., Kroon, T., Stam, J., Hydrologie, Landscape functioning, Geocomputation and Hydrology, Weerts, A. H., Berendrecht, W. L., Veldhuizen, A., Goorden, N., Vernimmen, R., Lourens, A., Prinsen, G., Mulder, M., Kroon, T., and Stam, J.

Published
2009

13. Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia.

Author

Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., van Dijk, A. I. J. M., and Thompson, S.

Subjects
RAINFALL, DROUGHTS, EARTH stations, EMPIRICAL research, ERROR analysis in mathematics
Abstract

The accuracy of three satellite rainfall products (TMPA 3B42RT, CMORPH and PERSIANN) was investigated through comparison with grid cell average ground station rainfall data in Indonesia, with a focus on their ability to detect patterns of low rainfall that may lead to drought conditions. Each of the three products underestimated rainfall in dry season months. The CMORPH and PERSIANN data differed most from ground station data and were also very different from the TMPA 3B42RT data. It proved possible to improve TMPA 3B42RT estimates by applying a single empirical bias correction equation that was uniform in space and time. For the six regions investigated, this reduced the root mean square error for estimates of dry season rainfall totals by a mean 9% (from 44 to 40 mm) and for annual totals by 14% (from 77 to 66 mm). The resulting errors represent 10% and 3% of mean dry season and annual rainfall, respectively. The accuracy of these bias corrected TMPA 3B42RT data is considered adequate for use in real-time drought monitoring in Indonesia. Compared to drought monitoring with only ground stations, this use of satellite-based rainfall estimates offers important advantages in terms of accuracy, spatial coverage, timeliness and cost efficiency. [ABSTRACT FROM AUTHOR]

Published
2012
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14. Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia.

Author

Vernimmen, R. R. E., Hooijer, A., Mamenun, and Aldrian, E.

Abstract

The accuracy of satellite rainfall data from different sources, TRMM 3B42RT, CMORPH and PERSIANN, was investigated through comparison with reliable ground station rainfall data in Indonesia, with a focus on their ability to detect patterns of low rainfall that may lead to drought conditions. It was found that all sources underestimated rainfall in dry season months. The CMORPH and PERSIANN data differed most from ground station data and are also very different from the TRMM data. However, it proved possible to improve TRMM data to yield sufficiently accurate estimates, both for dry periods (R² 0.65-0.92) and annually (R² 0.84-0.96), applying a single parameterized bias correction equation that is constant in space and time. It is proposed that these bias cor- rected TRMM data be used in real-time drought monitoring, in Indonesia and probably in other countries where similar conditions exist. This will yield major advantages, in terms of accuracy, spatial coverage, timely availability and cost efficiency, over drought monitoring with only ground stations. [ABSTRACT FROM AUTHOR]

Published
2011
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15. Graves' ophthalmopathy: What is the evidence for extraocular muscle specific autoantibodies

Author

Gaag, R., Vernimmen, R., Fiebelkorn, N., Dierendonck, M., and Kijlstra, A.

Abstract

Graves' ophthalmopathy is thought to be an autoimmune disease. Whether this disease is organ specific or one of the manifestations of the closely linked Graves' thyroid disease is still a matter of speculation. Many papers describe autoimmunity to orbital antigens, in particular to extraocular muscles, in patients with Graves' ophthalmopathy. In this paper we have tried to give an overview of the evidence for circulating antibodies against extraocular muscle antigens and to discuss their significance in relation to the immunopathogenesis of the disease.

Published
1990
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18. DeltaDTM: A global coastal digital terrain model.

Author

Pronk M, Hooijer A, Eilander D, Haag A, de Jong T, Vousdoukas M, Vernimmen R, Ledoux H, and Eleveld M

Abstract

Coastal elevation data are essential for a wide variety of applications, such as coastal management, flood modelling, and adaptation planning. Low-lying coastal areas (found below 10 m +Mean Sea Level (MSL)) are at risk of future extreme water levels, subsidence and changing extreme weather patterns. However, current freely available elevation datasets are not sufficiently accurate to model these risks. We present DeltaDTM, a global coastal Digital Terrain Model (DTM) available in the public domain, with a horizontal spatial resolution of 1 arcsecond (∼30 m) and a vertical mean absolute error (MAE) of 0.45 m overall. DeltaDTM corrects CopernicusDEM with spaceborne lidar from the ICESat-2 and GEDI missions. Specifically, we correct the elevation bias in CopernicusDEM, apply filters to remove non-terrain cells, and fill the gaps using interpolation. Notably, our classification approach produces more accurate results than regression methods recently used by others to correct DEMs, that achieve an overall MAE of 0.72 m at best. We conclude that DeltaDTM will be a valuable resource for coastal flood impact modelling and other applications., (© 2024. The Author(s).)

Published
2024
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19. Long-term thermal sensitivity of Earth's tropical forests.

Author

Sullivan MJP, Lewis SL, Affum-Baffoe K, Castilho C, Costa F, Sanchez AC, Ewango CEN, Hubau W, Marimon B, Monteagudo-Mendoza A, Qie L, Sonké B, Martinez RV, Baker TR, Brienen RJW, Feldpausch TR, Galbraith D, Gloor M, Malhi Y, Aiba SI, Alexiades MN, Almeida EC, de Oliveira EA, Dávila EÁ, Loayza PA, Andrade A, Vieira SA, Aragão LEOC, Araujo-Murakami A, Arets EJMM, Arroyo L, Ashton P, Aymard C G, Baccaro FB, Banin LF, Baraloto C, Camargo PB, Barlow J, Barroso J, Bastin JF, Batterman SA, Beeckman H, Begne SK, Bennett AC, Berenguer E, Berry N, Blanc L, Boeckx P, Bogaert J, Bonal D, Bongers F, Bradford M, Brearley FQ, Brncic T, Brown F, Burban B, Camargo JL, Castro W, Céron C, Ribeiro SC, Moscoso VC, Chave J, Chezeaux E, Clark CJ, de Souza FC, Collins M, Comiskey JA, Valverde FC, Medina MC, da Costa L, Dančák M, Dargie GC, Davies S, Cardozo ND, de Haulleville T, de Medeiros MB, Del Aguila Pasquel J, Derroire G, Di Fiore A, Doucet JL, Dourdain A, Droissart V, Duque LF, Ekoungoulou R, Elias F, Erwin T, Esquivel-Muelbert A, Fauset S, Ferreira J, Llampazo GF, Foli E, Ford A, Gilpin M, Hall JS, Hamer KC, Hamilton AC, Harris DJ, Hart TB, Hédl R, Herault B, Herrera R, Higuchi N, Hladik A, Coronado EH, Huamantupa-Chuquimaco I, Huasco WH, Jeffery KJ, Jimenez-Rojas E, Kalamandeen M, Djuikouo MNK, Kearsley E, Umetsu RK, Kho LK, Killeen T, Kitayama K, Klitgaard B, Koch A, Labrière N, Laurance W, Laurance S, Leal ME, Levesley A, Lima AJN, Lisingo J, Lopes AP, Lopez-Gonzalez G, Lovejoy T, Lovett JC, Lowe R, Magnusson WE, Malumbres-Olarte J, Manzatto ÂG, Marimon BH Jr, Marshall AR, Marthews T, de Almeida Reis SM, Maycock C, Melgaço K, Mendoza C, Metali F, Mihindou V, Milliken W, Mitchard ETA, Morandi PS, Mossman HL, Nagy L, Nascimento H, Neill D, Nilus R, Vargas PN, Palacios W, Camacho NP, Peacock J, Pendry C, Peñuela Mora MC, Pickavance GC, Pipoly J, Pitman N, Playfair M, Poorter L, Poulsen JR, Poulsen AD, Preziosi R, Prieto A, Primack RB, Ramírez-Angulo H, Reitsma J, Réjou-Méchain M, Correa ZR, de Sousa TR, Bayona LR, Roopsind A, Rudas A, Rutishauser E, Abu Salim K, Salomão RP, Schietti J, Sheil D, Silva RC, Espejo JS, Valeria CS, Silveira M, Simo-Droissart M, Simon MF, Singh J, Soto Shareva YC, Stahl C, Stropp J, Sukri R, Sunderland T, Svátek M, Swaine MD, Swamy V, Taedoumg H, Talbot J, Taplin J, Taylor D, Ter Steege H, Terborgh J, Thomas R, Thomas SC, Torres-Lezama A, Umunay P, Gamarra LV, van der Heijden G, van der Hout P, van der Meer P, van Nieuwstadt M, Verbeeck H, Vernimmen R, Vicentini A, Vieira ICG, Torre EV, Vleminckx J, Vos V, Wang O, White LJT, Willcock S, Woods JT, Wortel V, Young K, Zagt R, Zemagho L, Zuidema PA, Zwerts JA, and Phillips OL

Subjects
Acclimatization, Biomass, Carbon metabolism, Earth, Planet, Wood, Carbon Cycle, Climate Change, Forests, Hot Temperature, Trees metabolism, Tropical Climate
Abstract

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Published
2020
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20. Mapping deep peat carbon stock from a LiDAR based DTM and field measurements, with application to eastern Sumatra.

Author

Vernimmen R, Hooijer A, Akmalia R, Fitranatanegara N, Mulyadi D, Yuherdha A, Andreas H, and Page S

Abstract

Background: Reduction of carbon emissions from peatlands is recognized as an important factor in global climate change mitigation. Within the SE Asia region, areas of deeper peat present the greatest carbon stocks, and therefore the greatest potential for future carbon emissions from degradation and fire. They also support most of the remaining lowland swamp forest and its associated biodiversity. Accurate maps of deep peat are central to providing correct estimates of peat carbon stocks and to facilitating appropriate management interventions. We present a rapid and cost-effective approach to peat thickness mapping in raised peat bogs that applies a model of peat bottom elevation based on field measurements subtracted from a surface elevation model created from airborne LiDAR data., Results: In two raised peat bog test areas in Indonesia, we find that field peat thickness measurements correlate well with surface elevation derived from airborne LiDAR based DTMs (R 2 0.83-0.88), confirming that the peat bottom is often relatively flat. On this basis, we created a map of extent and depth of deep peat (> 3 m) from a new DTM that covers two-thirds of Sumatran peatlands, applying a flat peat bottom of 0.61 m +MSL determined from the average of 2446 field measurements. A deep peat area coverage of 2.6 Mha or 60.1% of the total peat area in eastern Sumatra is mapped, suggesting that deep peat in this region is more common than shallow peat and its extent was underestimated in earlier maps. The associated deep peat carbon stock range is 9.0-11.5 Pg C in eastern Sumatra alone., Conclusion: We discuss how the deep peat map may be used to identify priority areas for peat and forest conservation and thereby help prevent major potential future carbon emissions and support the safeguarding of the remaining forest and biodiversity. We propose rapid application of this method to other coastal raised bog peatland areas in SE Asia in support of improved peatland zoning and management. We demonstrate that the upcoming global ICESat-2 and GEDI satellite LiDAR coverage will likely result in a global DTM that, within a few years, will be sufficiently accurate for this application.

Published
2020
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21. Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences.

Author

Wijedasa LS, Jauhiainen J, Könönen M, Lampela M, Vasander H, Leblanc MC, Evers S, Smith TE, Yule CM, Varkkey H, Lupascu M, Parish F, Singleton I, Clements GR, Aziz SA, Harrison ME, Cheyne S, Anshari GZ, Meijaard E, Goldstein JE, Waldron S, Hergoualc'h K, Dommain R, Frolking S, Evans CD, Posa MR, Glaser PH, Suryadiputra N, Lubis R, Santika T, Padfield R, Kurnianto S, Hadisiswoyo P, Lim TW, Page SE, Gauci V, Van Der Meer PJ, Buckland H, Garnier F, Samuel MK, Choo LN, O'Reilly P, Warren M, Suksuwan S, Sumarga E, Jain A, Laurance WF, Couwenberg J, Joosten H, Vernimmen R, Hooijer A, Malins C, Cochrane MA, Perumal B, Siegert F, Peh KS, Comeau LP, Verchot L, Harvey CF, Cobb A, Jaafar Z, Wösten H, Manuri S, Müller M, Giesen W, Phelps J, Yong DL, Silvius M, Wedeux BM, Hoyt A, Osaki M, Hirano T, Takahashi H, Kohyama TS, Haraguchi A, Nugroho NP, Coomes DA, Quoi LP, Dohong A, Gunawan H, Gaveau DL, Langner A, Lim FK, Edwards DP, Giam X, Van Der Werf G, Carmenta R, Verwer CC, Gibson L, Gandois L, Graham LL, Regalino J, Wich SA, Rieley J, Kettridge N, Brown C, Pirard R, Moore S, Capilla BR, Ballhorn U, Ho HC, Hoscilo A, Lohberger S, Evans TA, Yulianti N, Blackham G, Onrizal, Husson S, Murdiyarso D, Pangala S, Cole LE, Tacconi L, Segah H, Tonoto P, Lee JS, Schmilewski G, Wulffraat S, Putra EI, Cattau ME, Clymo RS, Morrison R, Mujahid A, Miettinen J, Liew SC, Valpola S, Wilson D, D'Arcy L, Gerding M, Sundari S, Thornton SA, Kalisz B, Chapman SJ, Su AS, Basuki I, Itoh M, Traeholt C, Sloan S, Sayok AK, and Andersen R

Published
2017
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22. Variable carbon losses from recurrent fires in drained tropical peatlands.

Author

Konecny K, Ballhorn U, Navratil P, Jubanski J, Page SE, Tansey K, Hooijer A, Vernimmen R, and Siegert F

Subjects
Indonesia, Tropical Climate, Carbon, Fires, Models, Theoretical, Soil
Abstract

Tropical peatland fires play a significant role in the context of global warming through emissions of substantial amounts of greenhouse gases. However, the state of knowledge on carbon loss from these fires is still poorly developed with few studies reporting the associated mass of peat consumed. Furthermore, spatial and temporal variations in burn depth have not been previously quantified. This study presents the first spatially explicit investigation of fire-driven tropical peat loss and its variability. An extensive airborne Light Detection and Ranging data set was used to develop a prefire peat surface modelling methodology, enabling the spatially differentiated quantification of burned area depth over the entire burned area. We observe a strong interdependence between burned area depth, fire frequency and distance to drainage canals. For the first time, we show that relative burned area depth decreases over the first four fire events and is constant thereafter. Based on our results, we revise existing peat and carbon loss estimates for recurrent fires in drained tropical peatlands. We suggest values for the dry mass of peat fuel consumed that are 206 t ha(-1) for initial fires, reducing to 115 t ha(-1) for second, 69 t ha(-1) for third and 23 t ha(-1) for successive fires, which are 58-7% of the current IPCC Tier 1 default value for all fires. In our study area, this results in carbon losses of 114, 64, 38 and 13 t C ha(-1) for first to fourth fires, respectively. Furthermore, we show that with increasing proximity to drainage canals both burned area depth and the probability of recurrent fires increase and present equations explaining burned area depth as a function of distance to drainage canal. This improved knowledge enables a more accurate approach to emissions accounting and will support IPCC Tier 2 reporting of fire emissions., (© 2015 John Wiley & Sons Ltd.)

Published
2016
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23. Mitomycin C primary trabeculectomy in primary glaucoma of white patients.

Author

Nuijts RM, Vernimmen RC, and Webers CA

Subjects
Cataract etiology, Cataract physiopathology, Disease Progression, Glaucoma ethnology, Humans, Intraocular Pressure, Postoperative Complications, Postoperative Period, Prospective Studies, Retinal Diseases etiology, Visual Acuity, Antimetabolites therapeutic use, Glaucoma drug therapy, Glaucoma surgery, Intraoperative Care, Mitomycin therapeutic use, Trabeculectomy, White People
Abstract

Purpose: To evaluate the clinical outcome of eyes which underwent primary trabeculectomy with adjunctive mitomycin C (MMC) for primary glaucoma., Patients and Methods: A prospective analysis of 25 eyes in 23 patients who underwent primary trabeculectomy with MMC for primary glaucoma was performed. Clinical outcome measures including postoperative intraocular pressure, change in logarithm of the minimum angle of resolution (LogMAR) visual acuity, and incidence of complications were measured up to 1 year postoperatively., Results: Mean intraocular pressure decreased from 26.0 +/- 4.4 mmHg preoperatively to 12.5 +/- 3.9 mmHg (p < 0.0001) 1 year postoperatively. The mean LogMAR visual acuity changed from 0.23 +/- 0.19 preoperatively to 0.23 +/- 0.20 1 year postoperatively (p = 1.0). One eye developed a temporary hypotonous maculopathy and 4 eyes progressed in cataract formation., Conclusion: Primary trabeculectomy with MMC in eyes with primary glaucoma showed excellent pressure reduction. There were no cases of persistent hypotonous maculopathy or bleb endophthalmitis.

Published
1997

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