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56. ForestGEO: understanding forest diversity and dynamics through a global observatory network

Author

Davies, Stuart J., Abiem, Iveren, Abu Salim, Kamariah, Aguilar, Salomón, Allen, David, Alonso, Alfonso, Anderson-Teixeira, Kristina, Andrade, Ana, Arellano, Gabriel, Ashton, Peter S., Baker, Patrick J., Baker, Matthew E., Baltzer, Jennifer L., Basset, Yves, Bissiengou, Pulchérie, Bohlman, Stephanie, Bourg, Norman A., Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Burslem, David F.R.P., Cao, Min, Cárdenas, Dairon, Chang, Li-Wan, Chang-Yang, Chia-Hao, Chao, Kuo-Jung, Chao, Wei-Chun, Chapman, Hazel, Chen, Yu-Yun, Chisholm, Ryan A., Chu, Chengjin, Chuyong, George, Clay, Keith, Comita, Liza S., Condit, Richard, Cordell, Susan, Dattaraja, Handanakere S., de Oliveira, Alexandre Adalardo, den Ouden, Jan, Detto, Matteo, Dick, Christopher, Du, Xiaojun, Duque, Álvaro, Ediriweera, Sisira, Ellis, Erle C., Engone Obiang, Nestor Laurier, Esufali, Shameema, Ewango, Corneille E.N., Fernando, Edwino S., Filip, Jonah, Fischer, Gunter A., Foster, Robin, Giambelluca, Thomas, Giardina, Christian, Gilbert, Gregory S., Gonzalez-Akre, Erika, Gunatilleke, I.A.U.N., Gunatilleke, C.V.S., Hao, Zhanqing, Hau, Billy C.H., He, Fangliang, Ni, Hongwei, Howe, Robert W., Hubbell, Stephen P., Huth, Andreas, Inman-Narahari, Faith, Itoh, Akira, Janík, David, Jansen, Patrick A., Jiang, Mingxi, Johnson, Daniel J., Jones, F. Andrew, Kanzaki, Mamoru, Kenfack, David, Kiratiprayoon, Somboon, Král, Kamil, Krizel, Lauren, Lao, Suzanne, Larson, Andrew J., Li, Yide, Li, Xiankun, Litton, Creighton M., Liu, Yu, Liu, Shirong, Lum, Shawn K.Y., Luskin, Matthew S., Lutz, James A., Luu, Hong Truong, Ma, Keping, Makana, Jean-Remy, Malhi, Yadvinder, Martin, Adam, McCarthy, Caly, McMahon, Sean M., McShea, William J., Memiaghe, Hervé, Mi, Xiangcheng, Mitre, David, Mohamad, Mohizah, Monks, Logan, Muller-Landau, Helene C., Musili, Paul M., Myers, Jonathan A., Nathalang, Anuttara, Ngo, Kang Min, Norden, Natalia, Novotny, Vojtech, O'Brien, Michael J., Orwig, David, Ostertag, Rebecca, Papathanassiou, Konstantinos, Parker, Geoffrey G., Pérez, Rolando, Perfecto, Ivette, Phillips, Richard P., Pongpattananurak, Nantachai, Pretzsch, Hans, Ren, Haibo, Reynolds, Glen, Rodriguez, Lillian J., Russo, Sabrina E., Sack, Lawren, Sang, Weiguo, Shue, Jessica, Singh, Anudeep, Song, Guo-Zhang M., Sukumar, Raman, Sun, I-Fang, Suresh, Hebbalalu S., Swenson, Nathan G., Tan, Sylvester, Thomas, Sean C., Thomas, Duncan, Thompson, Jill, Turner, Benjamin L., Uowolo, Amanda, Uriarte, María, Valencia, Renato, Vandermeer, John, Vicentini, Alberto, Visser, Marco, Vrska, Tomas, Wang, Xugao, Wang, Xihua, Weiblen, George D., Whitfeld, Timothy J.S., Wolf, Amy, Wright, S. Joseph, Xu, Han, Yao, Tze Leong, Yap, Sandra L., Ye, Wanhui, Yu, Mingjian, Zhang, Minhua, Zhu, Daoguang, Zhu, Li, Zimmerman, Jess K., Zuleta, Daniel, Davies, Stuart J., Abiem, Iveren, Abu Salim, Kamariah, Aguilar, Salomón, Allen, David, Alonso, Alfonso, Anderson-Teixeira, Kristina, Andrade, Ana, Arellano, Gabriel, Ashton, Peter S., Baker, Patrick J., Baker, Matthew E., Baltzer, Jennifer L., Basset, Yves, Bissiengou, Pulchérie, Bohlman, Stephanie, Bourg, Norman A., Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Burslem, David F.R.P., Cao, Min, Cárdenas, Dairon, Chang, Li-Wan, Chang-Yang, Chia-Hao, Chao, Kuo-Jung, Chao, Wei-Chun, Chapman, Hazel, Chen, Yu-Yun, Chisholm, Ryan A., Chu, Chengjin, Chuyong, George, Clay, Keith, Comita, Liza S., Condit, Richard, Cordell, Susan, Dattaraja, Handanakere S., de Oliveira, Alexandre Adalardo, den Ouden, Jan, Detto, Matteo, Dick, Christopher, Du, Xiaojun, Duque, Álvaro, Ediriweera, Sisira, Ellis, Erle C., Engone Obiang, Nestor Laurier, Esufali, Shameema, Ewango, Corneille E.N., Fernando, Edwino S., Filip, Jonah, Fischer, Gunter A., Foster, Robin, Giambelluca, Thomas, Giardina, Christian, Gilbert, Gregory S., Gonzalez-Akre, Erika, Gunatilleke, I.A.U.N., Gunatilleke, C.V.S., Hao, Zhanqing, Hau, Billy C.H., He, Fangliang, Ni, Hongwei, Howe, Robert W., Hubbell, Stephen P., Huth, Andreas, Inman-Narahari, Faith, Itoh, Akira, Janík, David, Jansen, Patrick A., Jiang, Mingxi, Johnson, Daniel J., Jones, F. Andrew, Kanzaki, Mamoru, Kenfack, David, Kiratiprayoon, Somboon, Král, Kamil, Krizel, Lauren, Lao, Suzanne, Larson, Andrew J., Li, Yide, Li, Xiankun, Litton, Creighton M., Liu, Yu, Liu, Shirong, Lum, Shawn K.Y., Luskin, Matthew S., Lutz, James A., Luu, Hong Truong, Ma, Keping, Makana, Jean-Remy, Malhi, Yadvinder, Martin, Adam, McCarthy, Caly, McMahon, Sean M., McShea, William J., Memiaghe, Hervé, Mi, Xiangcheng, Mitre, David, Mohamad, Mohizah, Monks, Logan, Muller-Landau, Helene C., Musili, Paul M., Myers, Jonathan A., Nathalang, Anuttara, Ngo, Kang Min, Norden, Natalia, Novotny, Vojtech, O'Brien, Michael J., Orwig, David, Ostertag, Rebecca, Papathanassiou, Konstantinos, Parker, Geoffrey G., Pérez, Rolando, Perfecto, Ivette, Phillips, Richard P., Pongpattananurak, Nantachai, Pretzsch, Hans, Ren, Haibo, Reynolds, Glen, Rodriguez, Lillian J., Russo, Sabrina E., Sack, Lawren, Sang, Weiguo, Shue, Jessica, Singh, Anudeep, Song, Guo-Zhang M., Sukumar, Raman, Sun, I-Fang, Suresh, Hebbalalu S., Swenson, Nathan G., Tan, Sylvester, Thomas, Sean C., Thomas, Duncan, Thompson, Jill, Turner, Benjamin L., Uowolo, Amanda, Uriarte, María, Valencia, Renato, Vandermeer, John, Vicentini, Alberto, Visser, Marco, Vrska, Tomas, Wang, Xugao, Wang, Xihua, Weiblen, George D., Whitfeld, Timothy J.S., Wolf, Amy, Wright, S. Joseph, Xu, Han, Yao, Tze Leong, Yap, Sandra L., Ye, Wanhui, Yu, Mingjian, Zhang, Minhua, Zhu, Daoguang, Zhu, Li, Zimmerman, Jess K., and Zuleta, Daniel

Abstract

ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the

Published
2021

62. Validation and extension of the Tea Bag Index to collect decomposition data from termite-rich ecosystems

Author

Teo, Aloysius, Kristensen, Nadiah P., Keuskamp, Joost A., Evans, Theodore A., Foo, Maosheng, Chisholm, Ryan A., Ecology and Biodiversity, Sub Ecology and Biodiversity, Ecology and Biodiversity, and Sub Ecology and Biodiversity

Subjects
0106 biological sciences, Termite-exclusion, Carbon mineralization, Soil Science, 04 agricultural and veterinary sciences, Citizen science, Tropical forest, 010603 evolutionary biology, 01 natural sciences, Full sample, Litter decomposition, nervous system diseases, nervous system, Statistics, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Recalcitrant fraction, Ecosystem, Ecology, Evolution, Behavior and Systematics, Litter bag
Abstract

The Tea Bag Index (TBI) is a standardised and cheap method to quantify microbial-driven decomposition by measuring the mass loss of tea within tea bags. Termites are known to damage the bags to access the content, rendering the method less suitable for termite-rich ecosystems. Extension of the TBI to accommodate and incorporate the influence of termites would broaden its applicability to include termite-rich ecosystems, such as tropical forests. We extended the original TBI by applying physical and chemical termite-exclusion methods. Tea mass loss and the proportion of tea bags detected by termites in the original TBI were also recorded to infer the role of termites in litter decomposition. TBI estimates derived from the original and extended TBI were compared, benchmarked against global estimates, and validated with time-series mass loss data. Using the original TBI, we found that termites damaged up to 80 % of tea bags and consumed the recalcitrant fraction of tea in several of them, leaving only 20 % of tea bags from which TBI estimates could be retrieved. The physical termite-exclusion treatment completely eliminated termite-infringement, thus preserving the full sample size for estimating TBI parameters. The chemical termite-exclusion treatment also successfully excluded termites, but potentially inhibited microbial decomposition and made TBI estimates unreliable. In the absence of termite-infringement, both the TBI estimates and time-series analysis revealed a low decomposition rate compared to other measurements in tropical and temperate regions. We propose an extended TBI, in which the physical termite-exclusion treatment is used to preserve the retrieval rate of TBI parameters and reliably measure microbial-driven decomposition, while the original TBI is used to incorporate the contribution of termites in driving litter mass loss. By characterising both termite- and microbial-driven decomposition, the extended TBI will provide a comprehensive understanding of decomposition and its drivers in termite-rich ecosystems, and permit global comparisons.

Published
2020

63. Null-Hypothesis Significance Testing and the Critical Weight Range for Australian Mammals

Author

Chisholm, Ryan and Taylor, Robert

Subjects
Australians, Environmental issues, Zoology and wildlife conservation
Abstract

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1523-1739.2007.00815.x Byline: RYAN CHISHOLM (*), ROBERT TAYLOR ([dagger]) Keywords: Australian mammals; critical weight range; extinction risk; mammal body size; null-hypothesis significance testing Abstract: Abstract: The critical weight range hypothesis for Australian terrestrial mammals states that species in the intermediate size range 35-5500 g are particularly susceptible to extinction. In a 2001 study Cardillo and Bromham found no statistically significant evidence for this hypothesis and suggested that research should instead focus on why small species are resistant to extinction. We used a similar data set of body sizes of Australian mammals grouped by conservation classification, but we used test statistics (mean deviation above and below the median body size) that are more statistically powerful than those of Cardillo and Bromham (quartiles, maxima, and minima of body size distributions). We found strong evidence in favor of the critical weight range hypothesis: the body size distribution of threatened species was more clustered toward the median body size from above and below. This pattern was statistically significant at the continental scale and in the arid zone, but not in the mesic zone. Confusing statistical significance with evidence of no effect, as Cardillo and Bromham did, can have negative implications for conservation biology because it can result in failure to act when action is warranted or provision of incorrect advice that affects policy and planning decisions. Abstract (Spanish): La Prueba de Significancia de la Hipotesis Nula y el Rango de Peso Critico para Mamiferos Australianos Resumen: La hipotesis del rango de peso critico (RPC) para mamiferos australianos terrestres plantea que las especies en el rango de tamano intermedio de 35-5500 g son particularmente susceptibles a la extincion. En un estudio en 2001, Cardillo y Bromham no encontraron evidencia significativa para esta hipotesis y sugirieron que, en su lugar, la investigacion se deberia enfocar al porque las especies pequenas son resistentes a la extincion. Utilizamos un conjunto de datos de tamanos corporales de mamiferos australianos agrupados por clasificacion de conservacion, pero utilizamos pruebas estadisticas (desviacion media por encima y por debajo de la mediana del tamano corporal) que son estadisticamente mas poderosas que utilizadas por Cardillo y Bromham (cuartilas, maximos y minimos de las distribuciones de tamanos corporales). Encontramos fuerte evidencia a favor de la hipotesis RPC: la distribucion del tamano corporal de especies amenazadas estuvo mayormente agrupada hacia la mediana del tamano corporal. Este patron fue estadisticamente significativo en la escala continental y en la zona arida, pero no en la zona mesica. La confusion de la significancia estadistica con la evidencia de no efecto, como hicieron Cardillo y Bromham, puede tener implicaciones negativas para la biologia de la conservacion porque puede resultar en la falta de accion cuando se requiera o en asesoria inadecuada que afecta las decisiones politicas y de planificacion. Author Affiliation: (*)Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, U.S.A., emailchisholm@princeton.edu ([dagger])Department of Environment and Conservation, Dubbo, New South Wales 2830, Australia Article History: Paper submitted February 17, 2007; revised manuscript accepted July 2, 2007.

Published
2007

65. Temporal population variability in local forest communities has mixed effects on tree species richness across a latitudinal gradient

Author

Fung, Tak, Chisholm, Ryan A., Anderson‐Teixeira, Kristina, Bourg, Norm, Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Chang‐Yang, Chia‐Hao, Chitra‐Tarak, Rutuja, Chuyong, George, Condit, Richard, Dattaraja, Handanakere S., Davies, Stuart J., Ewango, Corneille E.N., Fewless, Gary, Fletcher, Christine, Gunatilleke, C.V. Savitri, Gunatilleke, I.A.U. Nimal, Hao, Zhanqing, Hogan, J. Aaron, Howe, Robert, Hsieh, Chang‐Fu, Kenfack, David, Lin, YiChing, Ma, Keping, Makana, Jean‐Remy, McMahon, Sean, McShea, William J., Mi, Xiangcheng, Nathalang, Anuttara, Ong, Perry S., Parker, Geoffrey, Rau, E‐Ping, Shue, Jessica, Su, Sheng‐Hsin, Sukumar, Raman, Sun, I‐Fang, Suresh, Hebbalalu S., Tan, Sylvester, Thomas, Duncan, Thompson, Jill, Valencia, Renato, Vallejo, Martha I., Wang, Xugao, Wang, Yunquan, Wijekoon, Pushpa, Wolf, Amy, Yap, Sandra, Zimmerman, Jess, Fung, Tak, Chisholm, Ryan A., Anderson‐Teixeira, Kristina, Bourg, Norm, Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Chang‐Yang, Chia‐Hao, Chitra‐Tarak, Rutuja, Chuyong, George, Condit, Richard, Dattaraja, Handanakere S., Davies, Stuart J., Ewango, Corneille E.N., Fewless, Gary, Fletcher, Christine, Gunatilleke, C.V. Savitri, Gunatilleke, I.A.U. Nimal, Hao, Zhanqing, Hogan, J. Aaron, Howe, Robert, Hsieh, Chang‐Fu, Kenfack, David, Lin, YiChing, Ma, Keping, Makana, Jean‐Remy, McMahon, Sean, McShea, William J., Mi, Xiangcheng, Nathalang, Anuttara, Ong, Perry S., Parker, Geoffrey, Rau, E‐Ping, Shue, Jessica, Su, Sheng‐Hsin, Sukumar, Raman, Sun, I‐Fang, Suresh, Hebbalalu S., Tan, Sylvester, Thomas, Duncan, Thompson, Jill, Valencia, Renato, Vallejo, Martha I., Wang, Xugao, Wang, Yunquan, Wijekoon, Pushpa, Wolf, Amy, Yap, Sandra, and Zimmerman, Jess

Abstract

Among the local processes that determine species diversity in ecological communities, fluctuation‐dependent mechanisms that are mediated by temporal variability in the abundances of species populations have received significant attention. Higher temporal variability in the abundances of species populations can increase the strength of temporal niche partitioning but can also increase the risk of species extinctions, such that the net effect on species coexistence is not clear. We quantified this temporal population variability for tree species in 21 large forest plots and found much greater variability for higher latitude plots with fewer tree species. A fitted mechanistic model showed that among the forest plots, the net effect of temporal population variability on tree species coexistence was usually negative, but sometimes positive or negligible. Therefore, our results suggest that temporal variability in the abundances of species populations has no clear negative or positive contribution to the latitudinal gradient in tree species richness.

Published
2020

68. ForestGEO: Understanding forest diversity and dynamics through a global observatory network

Author

Davies, Stuart J., primary, Abiem, Iveren, additional, Abu Salim, Kamariah, additional, Aguilar, Salomón, additional, Allen, David, additional, Alonso, Alfonso, additional, Anderson-Teixeira, Kristina, additional, Andrade, Ana, additional, Arellano, Gabriel, additional, Ashton, Peter S., additional, Baker, Patrick J., additional, Baker, Matthew E., additional, Baltzer, Jennifer L., additional, Basset, Yves, additional, Bissiengou, Pulchérie, additional, Bohlman, Stephanie, additional, Bourg, Norman A., additional, Brockelman, Warren Y., additional, Bunyavejchewin, Sarayudh, additional, Burslem, David F.R.P., additional, Cao, Min, additional, Cárdenas, Dairon, additional, Chang, Li-Wan, additional, Chang-Yang, Chia-Hao, additional, Chao, Kuo-Jung, additional, Chao, Wei-Chun, additional, Chapman, Hazel, additional, Chen, Yu-Yun, additional, Chisholm, Ryan A., additional, Chu, Chengjin, additional, Chuyong, George, additional, Clay, Keith, additional, Comita, Liza S., additional, Condit, Richard, additional, Cordell, Susan, additional, Dattaraja, Handanakere S., additional, de Oliveira, Alexandre Adalardo, additional, den Ouden, Jan, additional, Detto, Matteo, additional, Dick, Christopher, additional, Du, Xiaojun, additional, Duque, Álvaro, additional, Ediriweera, Sisira, additional, Ellis, Erle C., additional, Obiang, Nestor Laurier Engone, additional, Esufali, Shameema, additional, Ewango, Corneille E.N., additional, Fernando, Edwino S., additional, Filip, Jonah, additional, Fischer, Gunter A., additional, Foster, Robin, additional, Giambelluca, Thomas, additional, Giardina, Christian, additional, Gilbert, Gregory S., additional, Gonzalez-Akre, Erika, additional, Gunatilleke, I.A.U.N., additional, Gunatilleke, C.V.S., additional, Hao, Zhanqing, additional, Hau, Billy C.H., additional, He, Fangliang, additional, Ni, Hongwei, additional, Howe, Robert W., additional, Hubbell, Stephen P., additional, Huth, Andreas, additional, Inman-Narahari, Faith, additional, Itoh, Akira, additional, Janík, David, additional, Jansen, Patrick A., additional, Jiang, Mingxi, additional, Johnson, Daniel J., additional, Jones, F. Andrew, additional, Kanzaki, Mamoru, additional, Kenfack, David, additional, Kiratiprayoon, Somboon, additional, Král, Kamil, additional, Krizel, Lauren, additional, Lao, Suzanne, additional, Larson, Andrew J., additional, Li, Yide, additional, Li, Xiankun, additional, Litton, Creighton M., additional, Liu, Yu, additional, Liu, Shirong, additional, Lum, Shawn K.Y., additional, Luskin, Matthew S., additional, Lutz, James A., additional, Luu, Hong Truong, additional, Ma, Keping, additional, Makana, Jean-Remy, additional, Malhi, Yadvinder, additional, Martin, Adam, additional, McCarthy, Caly, additional, McMahon, Sean M., additional, McShea, William J., additional, Memiaghe, Hervé, additional, Mi, Xiangcheng, additional, Mitre, David, additional, Mohamad, Mohizah, additional, Monks, Logan, additional, Muller-Landau, Helene C., additional, Musili, Paul M., additional, Myers, Jonathan A., additional, Nathalang, Anuttara, additional, Ngo, Kang Min, additional, Norden, Natalia, additional, Novotny, Vojtech, additional, O'Brien, Michael J., additional, Orwig, David, additional, Ostertag, Rebecca, additional, Papathanassiou, Konstantinos, additional, Parker, Geoffrey G., additional, Pérez, Rolando, additional, Perfecto, Ivette, additional, Phillips, Richard P., additional, Pongpattananurak, Nantachai, additional, Pretzsch, Hans, additional, Ren, Haibo, additional, Reynolds, Glen, additional, Rodriguez, Lillian J., additional, Russo, Sabrina E., additional, Sack, Lawren, additional, Sang, Weiguo, additional, Shue, Jessica, additional, Singh, Anudeep, additional, Song, Guo-Zhang M., additional, Sukumar, Raman, additional, Sun, I-Fang, additional, Suresh, Hebbalalu S., additional, Swenson, Nathan G., additional, Tan, Sylvester, additional, Thomas, Sean C., additional, Thomas, Duncan, additional, Thompson, Jill, additional, Turner, Benjamin L., additional, Uowolo, Amanda, additional, Uriarte, María, additional, Valencia, Renato, additional, Vandermeer, John, additional, Vicentini, Alberto, additional, Visser, Marco, additional, Vrska, Tomas, additional, Wang, Xugao, additional, Wang, Xihua, additional, Weiblen, George D., additional, Whitfeld, Timothy J.S., additional, Wolf, Amy, additional, Wright, S. Joseph, additional, Xu, Han, additional, Yao, Tze Leong, additional, Yap, Sandra L., additional, Ye, Wanhui, additional, Yu, Mingjian, additional, Zhang, Minhua, additional, Zhu, Daoguang, additional, Zhu, Li, additional, Zimmerman, Jess K., additional, and Zuleta, Daniel, additional

Published
2021
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70. List of Contributors

Author

Akçakaya, H. Resit, primary, Alberti, Marina, additional, Baxter, Charles K., additional, Beck, Jeffrey L., additional, Beissinger, Steven R., additional, Bekessy, Sarah, additional, Brook, Barry W., additional, Ceder, Kevin, additional, Chisholm, Ryan, additional, Comnick, Jeffrey M., additional, Cushman, Samuel A., additional, Dettmers, Randy, additional, Dickson, Brett G., additional, Dijak, William D., additional, Donovan, Michael L., additional, Early, Richard J., additional, Estey, Michael E., additional, Fitzgerald, Jane, additional, Flather, Curtis H., additional, Gitzen, Robert A., additional, Gobster, Paul H., additional, Gordon, Ascelin, additional, Granfors, Diane A., additional, Gustafson, Eric J., additional, Haight, Robert G., additional, Haufler, Jonathan B., additional, He, Hong S., additional, Hepinstall, Jeffrey A., additional, Herter, Dale R., additional, Hicks, Lorin L., additional, Johnson, Rex R., additional, Jones, Tim, additional, Kernohan, Brian J., additional, Larsen, David R., additional, Larson, Michael A., additional, Linden, Daniel W., additional, Marzluff, John M., additional, McCarter, James B., additional, McKelvey, Kevin S., additional, McKenzie, Donald, additional, Millspaugh, Joshua J., additional, Nelson, Christopher S., additional, Nicholson, Emily, additional, Niemuth, Neal D., additional, Noon, Barry R., additional, Oliver, Chadwick D., additional, Pearce, Jennie, additional, Possingham, Hugh P., additional, Probst, John R., additional, Raymond, Crystal L., additional, Reynolds, Ronald E., additional, Rittenhouse, Chadwick D., additional, Roloff, Gary J., additional, Rowland, Mary M., additional, Rustay, Christopher, additional, Ruth, Janet M., additional, Shifley, Stephen R., additional, Shriner, Susan A., additional, Stabins, Henning C., additional, Strong, Marshall L., additional, Suring, Lowell H., additional, Thogmartin, Wayne E., additional, Thompson, Frank R., additional, Venier, Lisa, additional, Vogel, William O., additional, Wangler, Brian, additional, Will, Tom C., additional, Wilson, Kenneth R., additional, Wintle, Brendan, additional, and Wisdom, Michael J., additional

Published
2009
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85. Effects of temporal environmental stochasticity on species richness: a mechanistic unification spanning weak to strong temporal correlations.

Author

Fung, Tak, O'Dwyer, James P., and Chisholm, Ryan A.

Subjects
SPECIES diversity, COEXISTENCE of species, ENDANGERED species, COMPETITION (Biology)
Abstract

A long‐standing puzzle in ecology is coexistence of many species despite relatively few limiting resources. Studies using competitive community models have found that temporal environmental stochasticity (TES) can provide a solution by providing a rare‐species advantage, for example by creating temporal niches. However, this appears to contradict studies using population models, which have found that TES‐induced temporal fluctuations in species abundances increase the chance of species becoming rare and hence increase their extinction risk. Here, we clarified how TES affects species richness by analysing a competitive community model using a novel mean‐field approach. We found that when temporal correlation in TES was weak, the dominant effect of TES was to create temporal niches by decreasing the strength of interspecific competition via a temporal averaging effect, thereby increasing species richness relative to the neutral case without TES. In contrast, when temporal correlation was strong, the dominant effect of TES was to increase the strength of selection and hence interspecific competition, thereby decreasing species richness. Compared with these indirect community effects of TES, the direct effects of TES on species richness via temporal fluctuations in abundances of species populations were relatively minor. [ABSTRACT FROM AUTHOR]

Published
2022
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86. Bird diversity on shelf islands does not benefit from recent land‐bridge connections.

Author

Sin, Yong Chee Keita, Kristensen, Nadiah P., Gwee, Chyi Yin, Chisholm, Ryan A., and Rheindt, Frank E.

Subjects
BIRD diversity, LAST Glacial Maximum, ABSOLUTE sea level change, ISLANDS, MULTIDIMENSIONAL scaling, SPECIES diversity
Abstract

Aim: Research in island biogeography has long focused mainly on present‐day island configurations. Recently, there has been an increasing focus on islands' past histories of land connection, shape and size. Moreover, continental islands (=shelf islands) have received less attention than oceanic islands, and species inventories from extremely small islands are lacking in many datasets. We examine the effects of sea‐level rise since the Last Glacial Maximum (LGM) on bird species diversity and composition of tropical shelf islands in Southeast Asia. Location: Sundaland. Taxon: Birds. Methods: We compiled avifaunal island inventories for 94 islands using an exhaustive literature review of historic surveys of larger islands combined with our own comprehensive island surveys from both small and large islands. Using generalised least‐squares models with spatial autocorrelation, we assessed the importance of traditional biogeographical parameters including area, maximum elevation, distance from mainland and geographical isolation, along with post‐LGM effects of change in island area and duration since isolation. We also compared the species composition on similar‐sized shelf islands from two categories—recently submerged and unsubmerged—using non‐metric multidimensional scaling. Results: Post‐LGM effects on species diversity are minimal and insular diversity is instead well explained by present‐day island characteristics, such as area, distance to mainland and proportion of land surrounding an island within a 10 km radius (Cox and Snell Pseudo‐R2 = 0.803). Avifaunal diversity is similar across recently submerged and unsubmerged small shelf islands. Main conclusion: Avifaunal diversity on tropical shelf islands equilibrates rapidly after isolation, indicating that both extinction and immigration rates are high. In particular, a high immigration rate of dispersive species maintains diversity, especially on small islands. Over‐water dispersal is generally restricted to short distances among Sundaic birds. Consequently, the diversity of an island can be maintained by the presence of large or stepping‐stone islands near it. [ABSTRACT FROM AUTHOR]

Published
2022
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87. Top 100 questions for biodiversity conservation in Southeast Asia

Author

Coleman, Joanna, Ascher, John S., Bickford, David P., Buchori, Damayanti, Cabanban, Annadel, Chisholm, Ryan A., Chong, Kwek Yan, Christie, Patrick, Clements, Gopalasamy R., dela Cruz, Thomas E. E., Dressler, Wolfram, Edwards, David P., Francis, Charles M., Friess, Dan A., Giam, Xingli, Gibson, Luke, Huang, Danwei, Hughes, Alice C., Jaafar, Zeehan, Koh, Lian Pin, Kudavidanage, Enoka P., Lee, Benjamin, Lee, Janice, Lee, Tien Ming, Leggett, Matt, Leimona, Beria, Linkie, Matthew, Luskin, Matthew, Lynam, Antony, Meijaard, Erik, Nijman, Vincent, Olsson, Annette, Page, Susan, Parolin, Pia, Peh, Kelvin S.-H., Posa, Mary Rose C., Prescott, Graham W., Rahman, Syed Ajijur, Ramchunder, Sorain J., Rao, Madhu, Reed, James, Richards, Daniel R., Slade, Eleanor, Steinmetz, Robert, Tan, Puay Yok, Todd, Peter A., Vo, Si Tuan, Webb, Edward L., Yee, A, Ziegler, Alan D., and Carrasco, L. Roman

Abstract

Southeast (SE) Asia holds high regional biodiversity and endemism levels but is also one of the world's most threatened regions. Local, regional and global threats could have severe consequences for the future survival of many species and the provision of ecosystem services.In the face of myriad pressing environmental problems, we carried out a research prioritisation exercise involving 64 experts whose research relates to conservation biology and sustainability in SE Asia. Experts proposed the most pressing research questions which, if answered, would advance the goals of biodiversity conservation and sustainable development in SE Asia. We received a total of 333 questions through three rounds of elicitation, ranked them (by votes) following a workshop and grouped them into themes.The top 100 questions depict SE Asia as a region where strong pressures on biodiversity interact in complex and poorly understood ways. They point to a lack of information about multiple facets of the environment, while exposing the many threats to biodiversity and human wellbeing. The themes that emerged indicate the need to evaluate specific drivers of biodiversity loss (wildlife harvesting, agricultural expansion, climate change, infrastructure development, pollution) and even to identify which species and habitats are most at risk. They also suggest the need to study the effectiveness of practice-based solutions (protected areas, ecological restoration), the human dimension (social interventions, organisational systems and processes and, the impacts of biodiversity loss and conservation interventions on people). Finally, they highlight gaps in fundamental knowledge of ecosystem function. These 100 questions should help prioritise and coordinate research, conservation, education and outreach activities and the distribution of scarce conservation resources in SE Asia.

Published
2019

88. Data from: Patterns of nitrogen-fixing tree abundance in forests across Asia and America

Author

Menge, Duncan N.L., Chisholm, Ryan A., Davies, Stuart J., Abu Salim, Kamariah, Allen, David, Alvarez, Mauricio, Bourg, Norm, Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Butt, Nathalie, den Ouden, Jan, Jansen, Patrick, Menge, Duncan N.L., Chisholm, Ryan A., Davies, Stuart J., Abu Salim, Kamariah, Allen, David, Alvarez, Mauricio, Bourg, Norm, Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Butt, Nathalie, den Ouden, Jan, and Jansen, Patrick

Abstract

Symbiotic nitrogen (N)‐fixing trees can provide large quantities of new N to ecosystems, but only if they are sufficiently abundant. The overall abundance and latitudinal abundance distributions of N‐fixing trees are well characterised in the Americas, but less well outside the Americas. Here, we characterised the abundance of N‐fixing trees in a network of forest plots spanning five continents, ~5,000 tree species and ~4 million trees. The majority of the plots (86%) were in America or Asia. In addition, we examined whether the observed pattern of abundance of N‐fixing trees was correlated with mean annual temperature and precipitation. Outside the tropics, N‐fixing trees were consistently rare in the forest plots we examined. Within the tropics, N‐fixing trees were abundant in American but not Asian forest plots (~7% versus ~1% of basal area and stems). This disparity was not explained by mean annual temperature or precipitation. Our finding of low N‐fixing tree abundance in the Asian tropics casts some doubt on recent high estimates of N fixation rates in this region, which do not account for disparities in N‐fixing tree abundance between the Asian and American tropics. Synthesis. Inputs of nitrogen to forests depend on symbiotic nitrogen fixation, which is constrained by the abundance of N‐fixing trees. By analysing a large dataset of ~4 million trees, we found that N‐fixing trees were consistently rare in the Asian tropics as well as across higher latitudes in Asia, America and Europe. The rarity of N‐fixing trees in the Asian tropics compared with the American tropics might stem from lower intrinsic N limitation in Asian tropical forests, although direct support for any mechanism is lacking. The paucity of N‐fixing trees throughout Asian forests suggests that N inputs to the Asian tropics might be lower than previously thought.

Published
2019

89. An a posteriori species clustering for quantifying the effects of species interactions on ecosystem functioning

Author

Jaillard, Benoit, Richon, Camille, Deleporte, Philippe, Loreau, Michel, Violle, Cyrille, Chisholm, Ryan, Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Institut National de la Recherche Agronomique (INRA)-Institut de Recherche pour le Développement (IRD)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Station d'écologie théorique et expérimentale (SETE), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Paul-Valéry - Montpellier 3 (UM3), ANR: Labex TULIP,TULIP,ANR-10-LABX-0041, European Project: 639706,H2020,ERC-2014-STG,CONSTRAINTS(2015), Rhizosphère et Symbiose (R&S), Institut National de la Recherche Agronomique (INRA), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Theoretical and Experimental Ecology Station, Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), TULIP Laboratory of Excellence, Grant/Award Number: ANR-10-LABX-41, French Foundation for Research on Biodiversity, European Research Council, Grant/Award Number: ERC-StG-2014-639706, ANR-11-IDEX-0002,UNITI,Université Fédérale de Toulouse(2011), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud])

Subjects
0106 biological sciences, 0301 basic medicine, F40 - Écologie végétale, Biodiversité et Ecologie, Biodiversity, fonctionnement des écosystèmes, Biology, 010603 evolutionary biology, 01 natural sciences, interaction entre espèces, Biodiversity and Ecology, modelling, 03 medical and health sciences, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Assembly motif, Clustering, Combinatorics, Community, Functional effect groups, Modelling, Theoretical ecology, Ecosystem, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Cluster analysis, ComputingMilieux_MISCELLANEOUS, Ecology, Evolution, Behavior and Systematics, modélisation, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, U10 - Informatique, mathématiques et statistiques, Ecology, Ecological Modeling, Species diversity, functional effect groups, assembly motif, 15. Life on land, modèle d'écologie théorique, Ecological network, theoretical ecology, 030104 developmental biology, combinatorics, Cedar creek, A priori and a posteriori, community, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Global biodiversity, clustering, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

International audience; Quantifying the effects of species interactions is key to understanding the relationships between biodiversity and ecosystem functioning but remains elusive due to combinatorics issues. Functional groups have been commonly used to capture the diversity of forms and functions and thus simplify the reality. However, the explicit incorporation of species interactions is still lacking in functional group-based approaches. Here, we propose a new approach based on an a posteriori clustering of species to quantify the effects of species interactions on ecosystem functioning.We first decompose the observed ecosystem function using null models, in which species diversity does not affect ecosystem function, to separate the effects of species interactions and species composition. This allows the identification of a posteriori functional groups that have contrasting diversity effects on ecosystem functioning. We then develop a formal combinatorial model of species interactions in which an ecosystem is described as a combination of co-occurring functional groups, which we call an assembly motif. Each assembly motif corresponds to a particular biotic environment. We demonstrate the relevance of our approach using datasets from a microbial experiment and the long-term Cedar Creek Biodiversity II experiment.We show that our a posteriori approach is more accurate, more efficient and more parsimonious than a priori approaches. The discrepancy between a priori and a posteriori approaches results from the way each clustering is set up: a priori approaches are based on ecosystem or species properties, such as ecosystem size (number of species or functional groups) or species' functional traits, whereas our a posteriori approach is based only on the observed interaction and composition effects on ecosystem functioning.Our findings demonstrate that an a posteriori approach is highly explanatory: it identifies who interacts with whom, and quantifies the effects of species interactions on ecosystem functioning. They also highlight that a combinatorial modelling of ecosystem functioning can predict the functioning of an ecosystem without any hypothesis about the biotic or environmental determinants or any information on species functional traits. It only requires the species composition of the ecosystem and the observed functioning of others that share the same assembly motif.

Published
2018
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90. Tropical Vegetation and Residential Property Value: A Hedonic Pricing Analysis in Singapore

Author

Belcher, Richard Neil and Chisholm, Ryan A.

Abstract

This posters was presented at the ACES ESP conference in Washington D.C. December 2018. It is a visualization of the research with the same name. AbstractEffective urban planning depends on knowing homebuyers' preferences for neighbourhood features that provide different amenities, such as managed parks and trees. As the expansion of tropical urban areas into biodiversity hotspots is predicted to more than double by 2030, knowing homebuyers utility from different vegetation types can contribute to global biodiversity conservation strategies. We used the hedonic pricing method to estimate the economic value of managed, spontaneous and high conservation value vegetation to Singapore public housing using a mixed effects model. On average vegetation had positive effects on property selling price, accounting for 3% of the average property's value, or a total of S$179 million for all public housing apartments sold over 13 months. These effects were almost entirely driven by managed vegetation, which had positive marginal effects on price for 98.1% of properties. The estimated marginal effects of high conservation value vegetation were mostly neutral, with some being negative (90.5%% properties), but positive for properties without much managed vegetation nearby. The estimated marginal effects of spontaneous vegetation were negative but mostly small.

Published
2018
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92. Temporal population variability in local forest communities has mixed effects on tree species richness across a latitudinal gradient

Author

Fung, Tak, primary, Chisholm, Ryan A., additional, Anderson‐Teixeira, Kristina, additional, Bourg, Norm, additional, Brockelman, Warren Y., additional, Bunyavejchewin, Sarayudh, additional, Chang‐Yang, Chia‐Hao, additional, Chitra‐Tarak, Rutuja, additional, Chuyong, George, additional, Condit, Richard, additional, Dattaraja, Handanakere S., additional, Davies, Stuart J., additional, Ewango, Corneille E. N., additional, Fewless, Gary, additional, Fletcher, Christine, additional, Gunatilleke, C. V. Savitri, additional, Gunatilleke, I. A. U. Nimal, additional, Hao, Zhanqing, additional, Hogan, J. Aaron, additional, Howe, Robert, additional, Hsieh, Chang‐Fu, additional, Kenfack, David, additional, Lin, YiChing, additional, Ma, Keping, additional, Makana, Jean‐Remy, additional, McMahon, Sean, additional, McShea, William J., additional, Mi, Xiangcheng, additional, Nathalang, Anuttara, additional, Ong, Perry S., additional, Parker, Geoffrey, additional, Rau, E‐Ping, additional, Shue, Jessica, additional, Su, Sheng‐Hsin, additional, Sukumar, Raman, additional, Sun, I‐Fang, additional, Suresh, Hebbalalu S., additional, Tan, Sylvester, additional, Thomas, Duncan, additional, Thompson, Jill, additional, Valencia, Renato, additional, Vallejo, Martha I., additional, Wang, Xugao, additional, Wang, Yunquan, additional, Wijekoon, Pushpa, additional, Wolf, Amy, additional, Yap, Sandra, additional, and Zimmerman, Jess, additional

Published
2019
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95. Patterns of nitrogen‐fixing tree abundance in forests across Asia and America

Author

Menge, Duncan N. L., primary, Chisholm, Ryan A., additional, Davies, Stuart J., additional, Abu Salim, Kamariah, additional, Allen, David, additional, Alvarez, Mauricio, additional, Bourg, Norm, additional, Brockelman, Warren Y., additional, Bunyavejchewin, Sarayudh, additional, Butt, Nathalie, additional, Cao, Min, additional, Chanthorn, Wirong, additional, Chao, Wei‐Chun, additional, Clay, Keith, additional, Condit, Richard, additional, Cordell, Susan, additional, Silva, João Batista, additional, Dattaraja, H. S., additional, Andrade, Ana Cristina Segalin, additional, Oliveira, Alexandre A., additional, den Ouden, Jan, additional, Drescher, Michael, additional, Fletcher, Christine, additional, Giardina, Christian P., additional, Savitri Gunatilleke, C. V., additional, Gunatilleke, I. A. U. Nimal, additional, Hau, Billy C. H., additional, He, Fangliang, additional, Howe, Robert, additional, Hsieh, Chang‐Fu, additional, Hubbell, Stephen P., additional, Inman‐Narahari, Faith M., additional, Jansen, Patrick A., additional, Johnson, Daniel J., additional, Kong, Lee Sing, additional, Král, Kamil, additional, Ku, Chen‐Chia, additional, Lai, Jiangshan, additional, Larson, Andrew J., additional, Li, Xiankun, additional, Li, Yide, additional, Lin, Luxiang, additional, Lin, YiChing, additional, Liu, Shirong, additional, Lum, Shawn K. Y., additional, Lutz, James A., additional, Ma, Keping, additional, Malhi, Yadvinder, additional, McMahon, Sean, additional, McShea, William, additional, Mi, Xiangcheng, additional, Morecroft, Michael, additional, Myers, Jonathan A., additional, Nathalang, Anuttara, additional, Novotny, Vojtech, additional, Ong, Perry, additional, Orwig, David A., additional, Ostertag, Rebecca, additional, Parker, Geoffrey, additional, Phillips, Richard P., additional, Abd. Rahman, Kassim, additional, Sack, Lawren, additional, Sang, Weiguo, additional, Shen, Guochun, additional, Shringi, Ankur, additional, Shue, Jessica, additional, Su, Sheng‐Hsin, additional, Sukumar, Raman, additional, Sun, I‐Fang, additional, Suresh, H. S., additional, Tan, Sylvester, additional, Thomas, Sean C., additional, Toko, Pagi S., additional, Valencia, Renato, additional, Vallejo, Martha I., additional, Vicentini, Alberto, additional, Vrška, Tomáš, additional, Wang, Bin, additional, Wang, Xihua, additional, Weiblen, George D., additional, Wolf, Amy, additional, Xu, Han, additional, Yap, Sandra, additional, Zhu, Li, additional, and Fung, Tak, additional

Published
2019
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99. Quantifying carbon in tree bark: The importance of bark morphology and tree size.

Author

Neumann, Mathias, Lawes, Michael J., and Chisholm, Ryan

Subjects
TREE size, BARK, WOOD density, CARBON, TREES, HARDWOODS
Abstract

Bark contributes approximately 20% to the total above‐ground biomass of trees, yet bark is not properly accounted for when estimating carbon sequestered by trees. Current allometric functions estimate tree volume from diameter measured over the bark, and derive bark density and carbon content from estimates for wood. As the bark density of hardwood species is 40%–50% lower than the wood density, but nearly equivalent in conifers, bark carbon is overestimated for most species. The latter is further exacerbated by variation in bark volume with bark surface morphology.Fissured bark volume is overestimated by diameter over bark measurements by up to 40%. The vacant space in fissures can be accounted for by a bark fissure index (BFI). We calculate bark carbon for Australian species from a non‐destructive and effective BFI using bark thickness measured in the field.Bark volume, and in turn bark carbon, scaled inversely with tree size (diameter) so that bark volume comprised 42% of small trees (10 cm diameter at breast height, DBH) but 23% of large trees (50 cm DBH). Our BFI method using a bark thickness gauge (BGM) yielded similar results than using the less time‐efficient contour gauge method (CM) to estimate BFI (bias BGM‐CM −1.3%, non‐significant at p = 0.72). Both BGM and CM had an error of <4% compared to digitized BFI from destructive sampled stem disks. An average of 15 bark gauge measurements per tree estimated bark thickness (and inconsequence BFI) for both fissured and unfissured bark with <20% error relative to the exact value.Using the bark gauge method, BFI can be rapidly measured from large numbers of trees needed for estimating bark carbon at the community level and modelling carbon uptake, storage and cycling in woody biomes. [ABSTRACT FROM AUTHOR]

Published
2021
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100. Carryover effects from natal habitat type upon competitive ability lead to trait divergence or source-sink dynamics

Author

van Baalen, Minus, van Baalen, M ( Minus ), Kristensen, Nadiah Pardede, Johansson, Jacob, Chisholm, Ryan A, Smith, Henrik G, Kokko, Hanna, van Baalen, Minus, van Baalen, M ( Minus ), Kristensen, Nadiah Pardede, Johansson, Jacob, Chisholm, Ryan A, Smith, Henrik G, and Kokko, Hanna

Abstract

Local adaptation to rare habitats is difficult due to gene flow, but can occur if the habitat has higher productivity. Differences in offspring phenotypes have attracted little attention in this context. We model a scenario where the rarer habitat improves offspring's later competitive ability – a carryover effect that operates on top of local adaptation to one or the other habitat type. Assuming localised dispersal, so the offspring tend to settle in similar habitat to the natal type, the superior competitive ability of offspring remaining in the rarer habitat hampers immigration from the majority habitat. This initiates a positive feedback between local adaptation and trait divergence, which can thereafter be reinforced by coevolution with dispersal traits that match ecotype to habitat type. Rarity strengthens selection on dispersal traits and promotes linkage disequilibrium between locally adapted traits and ecotype‐habitat matching dispersal. We propose that carryover effects may initiate isolation by ecology.

Published
2018

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