- Email: [email protected]
Predicting the future and saving species
14
Update
TRENDS in Ecology and Evolution
provides data about the populations structure and mating dynamics (which is surprising, given the importance of sex-ratio studies and the advent of genetic markers enabling a detailed characterization of breeding structures). According to Orzak, fig wasps are one of the few taxa in which LMC should occur, because females oviposit inside a fig, where their offspring then eclose and mate. Interspecific variation in foundress number per fig provides an ideal system with which to test LMC. In line with theory, comparative studies showed not only that sex ratios are highly female biased, but also that the bias is higher in species with lower numbers of foundresses per fig. These data are arguably the stronger test of LMC and are frequently presented in textbooks as tests of sex-ratio theory and examples of adaptation. Incidentally, a new genetic study showed that, even for fig wasps, reality might be more complex than it actually seems (D. Molbo et al., unpublished). Contrary to the common belief that
Vol.18 No.1 January 2003
figs are pollinated by a single species, two or three cryptic species of wasps were found in most species of figs. Moreover, not all foundresses in a fig reproduce, thus leading to an even higher level of LMC than was estimated previously from counts of dead foundresses. In summary, this excellent book provides an up-to-date and critical review of the models and data relating to sex ratios. The book is very well structured and demonstrates that a multi-authored book can be cohesive. The authors demonstrate convincingly that sex ratio is an excellent model trait for examining general questions in evolutionary biology. And, as clearly pointed out by Orzack, and West and Herre, although we have learned much from sexratio studies, there is much more left to do than simply dotting i’s and crossing t’s. References 1 Hamilton, W.D. (1967) Extraordinary sex ratios. Science 156, 477 – 488
Predicting the future and saving species Population Viability Analysis edited by S.R. Beissinger and D.R. McCullough. University of Chicago Press, 2002. £24.50 pbk (496 pages) ISBN 0 22604178 6. Quantitative Conservation Biology by W.F. Morris and D.F. Doak. Sinauer Associates, 2002. £24.99 pbk (480 pages) ISBN 0 87893546 0
Tim Coulson Department of Zoology, Downing Street, University of Cambridge, Cambridge CB2 3EJ, UK
Population viability analysis (PVA) is the first methodology that most conservation biologists would use when assessing or identifying conservation strategies for a population. It involves constructing a mathematical model of the population dynamics, which is then used to assess the probability of a population either going extinct or declining below a threshold size within a specified number of years. The performance of different conservation strategies can then be assessed by imposing them on the model and comparing results. For a population of an endangered species, the best strategy is usually considered the one that gives the lowest probability of extinction or declining below the threshold. PVA has become a widely used tool in conservation biology, but has recently attracted some controversy. Its advocates pedal PVA as a tool that accurately produces probabilistic population trajectories under a wide range of circumstances [1]. Critics argue that, given the quality of data available for most Corresponding author: Tim Coulson ([email protected]).
populations of endangered species, constructing a model that can produce accurate and useful population trajectories might often not be possible [2]. Quantitative Conservation Biology provides a clear guide about how to do a PVA, beginning with a consideration of PVAs that are based on count data (the number of individuals seen in each census). It moves through more complex demographically structured models to spatially explicit models, and covers problems in parameter estimation and the incorporation of observation error. The book is so clearly written that it provides an excellent introduction to population modelling that will prove useful to biologists of all levels who wish to learn more about the subject. The book contains over 40 MATLAB programs that can be used as the basis for any PVA. This is a nice touch. Many PVAs are currently performed using off-the-shelf packages, such as VORTEX [3], which, although powerful, have the drawback that they enable PVAs to be run by anyone, regardless of their understanding of the population model assumptions or structure. By encouraging the reader to construct their own PVA from scratch based on the source MATLAB code, Morris and Doak will hopefully promote a solid understanding among applied conservation biologists about how PVAs work, and how they can be performed.
http://tree.trends.com 0169-5347/02/$ - see front matter q 2002 Elsevier Science Ltd. All rights reserved. PII: S0169-5347(02)00003-4
Update
TRENDS in Ecology and Evolution
Throughout the book is the message that population models should be kept simple and should be based on available data. This should be obvious, but still needs stating. There has been a tendency in the PVA literature to incorporate all factors that might cause extinction, for example random demographic fluctuations, loss of genetic diversity, the accumulation of deleterious mutations or as a result of catastrophes. Some practitioners like all these factors to be considered in PVAs, but if you are basing your model on a handful of estimates of population size, it is difficult to have any idea what form functions describing these processes should take. And perhaps herein lies my biggest criticism of this book. After 440 pages of learning how to do a PVA, one reaches the final chapter on when not to do one. The chapter is balanced and discusses criticism of the methods, but I would have preferred the caveats and cautioning to have been prominent earlier on and the discussions extended. As with any modelling exercise, predictions are dependent on the models used to generate them. If there are insufficient data to construct a model that can at least capture the essential pattern of the population dynamics, the model might be useless as a tool for estimating probabilistic trajectories. If you don’t know what the dynamics look like, or don’t have the data to construct a reasonable model, don’t try. The costs of getting it wrong are too high. Not only could recommendations supported by an inaccurate PVA decrease the viability of the population they are intended to help, but also conservation biology could get bad press that might jeopardize the application of PVAs in circumstances where sufficient data are available to construct a useful model. Proponents of PVA have challenged critics who caution against uncritical use of PVA with the charge that PVAs are the best tool available for assessing extinction risk, and then ask what should be used instead? PVAs are currently the best tool available, but that does not mean that they always produce useful probabilistic population trajectories. If a model that captures the pattern of the population dynamics cannot be constructed, or if this pattern is unknown, there is little benefit to guessing under the guise of science. Common sense might provide a better guide. For example, if truckloads of harvested animals were being removed from a population, a sensible objective would be to decrease or remove this threat. Running parallel to an initiative to meet this objective should be data collection that would enable a PVA to be constructed when a better understanding of the population dynamics is achieved. As more data are collected, PVAs can be updated and an adaptive approach used. Maehr et al. and Ludwig and Walters in Population Viability Analysis discuss adaptive conservation strategies and the re-running of PVAs once more data are available. This is a book that deals with the history, philosophy, use and future directions of PVA, and is the best book currently available to learn about these aspects of the field, with an underlying message that is balanced and avoids being partisan. Population Viability Analysis is split into four parts, the first provides an overview of PVAs, describing their history, how they are http://tree.trends.com
Vol.18 No.1 January 2003
15
constructed and the various levels of complexity that can be incorporated. The second deals with the construction and parameterization of the models, including analysis of mark – recapture data, Bayesean statistics and incorporation of sources of error. The third section considers the marriage of theory and practice, and the final section considers the future of PVA, although no confidence intervals are provided around its predicted future trajectory. One chapter that I found particularly thought provoking was that by Shaffer and colleagues about PVA and conservation policy. They review the application of PVAs in the ‘policy and management arena’ and highlight three issues that have not been adequately addressed: first, that the utility of PVAs is hampered by lack of good data; second, that policy makers have not accepted scientific findings about what the minimum viable population size should be; and third, that policy makers have not accepted that population viability can only be assessed within a specified timeframe. From their review of the literature, the authors describe five initiatives that are required to address the three lessons. You will have to read the chapter to find out what these initiatives are, but they would benefit population ecology in general. Belovski and colleagues describe the use of replicate populations of brine shrimp Artenia franciscana populations in the laboratory to assess extinction risk, providing one of the most robust tests of PVAs of which I am aware. The message is mixed: simple models tend to perform better than more complex ones, but many frequently used PVA models perform badly at predicting extinction risk. More studies of this ilk are required across a range of organisms before these results can be generalised. Population viability is a relatively new field that currently has champions and sceptics. It is as yet too early to assess critically how useful estimating probabilities of extinction really is in practice. It is also unclear whether the development of the field over the past couple of decades has led to any improvement in our predicting future probabilistic population trajectories. My guess is that it hasn’t. So which book will have the best viability? I could check citation rates over the next few months and use these to construct a count-based PVA. I could extract information from the publishers about the performance of similar books in the field. Given the current information available to me, I think that I will refrain from attempting to make any predictions. But common sense tells me that ecologists would find much of interest in both books, even if they have mixed feelings about the utility of PVAs. References 1 Brook, B.W. et al. (2000) Predictive accuracy of population viability analysis in conservation biology. Nature 404, 385 – 387 2 Coulson, T. et al. (2001) The use and abuse of population viability analysis. Trends Ecol. Evol. 16, 219– 221 3 Lacy, R.C. (1993) VORTEX: a computer simulation model for population viability analysis. Wildlife Res. 20, 45 – 65
Update
TRENDS in Ecology and Evolution
provides data about the populations structure and mating dynamics (which is surprising, given the importance of sex-ratio studies and the advent of genetic markers enabling a detailed characterization of breeding structures). According to Orzak, fig wasps are one of the few taxa in which LMC should occur, because females oviposit inside a fig, where their offspring then eclose and mate. Interspecific variation in foundress number per fig provides an ideal system with which to test LMC. In line with theory, comparative studies showed not only that sex ratios are highly female biased, but also that the bias is higher in species with lower numbers of foundresses per fig. These data are arguably the stronger test of LMC and are frequently presented in textbooks as tests of sex-ratio theory and examples of adaptation. Incidentally, a new genetic study showed that, even for fig wasps, reality might be more complex than it actually seems (D. Molbo et al., unpublished). Contrary to the common belief that
Vol.18 No.1 January 2003
figs are pollinated by a single species, two or three cryptic species of wasps were found in most species of figs. Moreover, not all foundresses in a fig reproduce, thus leading to an even higher level of LMC than was estimated previously from counts of dead foundresses. In summary, this excellent book provides an up-to-date and critical review of the models and data relating to sex ratios. The book is very well structured and demonstrates that a multi-authored book can be cohesive. The authors demonstrate convincingly that sex ratio is an excellent model trait for examining general questions in evolutionary biology. And, as clearly pointed out by Orzack, and West and Herre, although we have learned much from sexratio studies, there is much more left to do than simply dotting i’s and crossing t’s. References 1 Hamilton, W.D. (1967) Extraordinary sex ratios. Science 156, 477 – 488
Predicting the future and saving species Population Viability Analysis edited by S.R. Beissinger and D.R. McCullough. University of Chicago Press, 2002. £24.50 pbk (496 pages) ISBN 0 22604178 6. Quantitative Conservation Biology by W.F. Morris and D.F. Doak. Sinauer Associates, 2002. £24.99 pbk (480 pages) ISBN 0 87893546 0
Tim Coulson Department of Zoology, Downing Street, University of Cambridge, Cambridge CB2 3EJ, UK
Population viability analysis (PVA) is the first methodology that most conservation biologists would use when assessing or identifying conservation strategies for a population. It involves constructing a mathematical model of the population dynamics, which is then used to assess the probability of a population either going extinct or declining below a threshold size within a specified number of years. The performance of different conservation strategies can then be assessed by imposing them on the model and comparing results. For a population of an endangered species, the best strategy is usually considered the one that gives the lowest probability of extinction or declining below the threshold. PVA has become a widely used tool in conservation biology, but has recently attracted some controversy. Its advocates pedal PVA as a tool that accurately produces probabilistic population trajectories under a wide range of circumstances [1]. Critics argue that, given the quality of data available for most Corresponding author: Tim Coulson ([email protected]).
populations of endangered species, constructing a model that can produce accurate and useful population trajectories might often not be possible [2]. Quantitative Conservation Biology provides a clear guide about how to do a PVA, beginning with a consideration of PVAs that are based on count data (the number of individuals seen in each census). It moves through more complex demographically structured models to spatially explicit models, and covers problems in parameter estimation and the incorporation of observation error. The book is so clearly written that it provides an excellent introduction to population modelling that will prove useful to biologists of all levels who wish to learn more about the subject. The book contains over 40 MATLAB programs that can be used as the basis for any PVA. This is a nice touch. Many PVAs are currently performed using off-the-shelf packages, such as VORTEX [3], which, although powerful, have the drawback that they enable PVAs to be run by anyone, regardless of their understanding of the population model assumptions or structure. By encouraging the reader to construct their own PVA from scratch based on the source MATLAB code, Morris and Doak will hopefully promote a solid understanding among applied conservation biologists about how PVAs work, and how they can be performed.
http://tree.trends.com 0169-5347/02/$ - see front matter q 2002 Elsevier Science Ltd. All rights reserved. PII: S0169-5347(02)00003-4
Update
TRENDS in Ecology and Evolution
Throughout the book is the message that population models should be kept simple and should be based on available data. This should be obvious, but still needs stating. There has been a tendency in the PVA literature to incorporate all factors that might cause extinction, for example random demographic fluctuations, loss of genetic diversity, the accumulation of deleterious mutations or as a result of catastrophes. Some practitioners like all these factors to be considered in PVAs, but if you are basing your model on a handful of estimates of population size, it is difficult to have any idea what form functions describing these processes should take. And perhaps herein lies my biggest criticism of this book. After 440 pages of learning how to do a PVA, one reaches the final chapter on when not to do one. The chapter is balanced and discusses criticism of the methods, but I would have preferred the caveats and cautioning to have been prominent earlier on and the discussions extended. As with any modelling exercise, predictions are dependent on the models used to generate them. If there are insufficient data to construct a model that can at least capture the essential pattern of the population dynamics, the model might be useless as a tool for estimating probabilistic trajectories. If you don’t know what the dynamics look like, or don’t have the data to construct a reasonable model, don’t try. The costs of getting it wrong are too high. Not only could recommendations supported by an inaccurate PVA decrease the viability of the population they are intended to help, but also conservation biology could get bad press that might jeopardize the application of PVAs in circumstances where sufficient data are available to construct a useful model. Proponents of PVA have challenged critics who caution against uncritical use of PVA with the charge that PVAs are the best tool available for assessing extinction risk, and then ask what should be used instead? PVAs are currently the best tool available, but that does not mean that they always produce useful probabilistic population trajectories. If a model that captures the pattern of the population dynamics cannot be constructed, or if this pattern is unknown, there is little benefit to guessing under the guise of science. Common sense might provide a better guide. For example, if truckloads of harvested animals were being removed from a population, a sensible objective would be to decrease or remove this threat. Running parallel to an initiative to meet this objective should be data collection that would enable a PVA to be constructed when a better understanding of the population dynamics is achieved. As more data are collected, PVAs can be updated and an adaptive approach used. Maehr et al. and Ludwig and Walters in Population Viability Analysis discuss adaptive conservation strategies and the re-running of PVAs once more data are available. This is a book that deals with the history, philosophy, use and future directions of PVA, and is the best book currently available to learn about these aspects of the field, with an underlying message that is balanced and avoids being partisan. Population Viability Analysis is split into four parts, the first provides an overview of PVAs, describing their history, how they are http://tree.trends.com
Vol.18 No.1 January 2003
15
constructed and the various levels of complexity that can be incorporated. The second deals with the construction and parameterization of the models, including analysis of mark – recapture data, Bayesean statistics and incorporation of sources of error. The third section considers the marriage of theory and practice, and the final section considers the future of PVA, although no confidence intervals are provided around its predicted future trajectory. One chapter that I found particularly thought provoking was that by Shaffer and colleagues about PVA and conservation policy. They review the application of PVAs in the ‘policy and management arena’ and highlight three issues that have not been adequately addressed: first, that the utility of PVAs is hampered by lack of good data; second, that policy makers have not accepted scientific findings about what the minimum viable population size should be; and third, that policy makers have not accepted that population viability can only be assessed within a specified timeframe. From their review of the literature, the authors describe five initiatives that are required to address the three lessons. You will have to read the chapter to find out what these initiatives are, but they would benefit population ecology in general. Belovski and colleagues describe the use of replicate populations of brine shrimp Artenia franciscana populations in the laboratory to assess extinction risk, providing one of the most robust tests of PVAs of which I am aware. The message is mixed: simple models tend to perform better than more complex ones, but many frequently used PVA models perform badly at predicting extinction risk. More studies of this ilk are required across a range of organisms before these results can be generalised. Population viability is a relatively new field that currently has champions and sceptics. It is as yet too early to assess critically how useful estimating probabilities of extinction really is in practice. It is also unclear whether the development of the field over the past couple of decades has led to any improvement in our predicting future probabilistic population trajectories. My guess is that it hasn’t. So which book will have the best viability? I could check citation rates over the next few months and use these to construct a count-based PVA. I could extract information from the publishers about the performance of similar books in the field. Given the current information available to me, I think that I will refrain from attempting to make any predictions. But common sense tells me that ecologists would find much of interest in both books, even if they have mixed feelings about the utility of PVAs. References 1 Brook, B.W. et al. (2000) Predictive accuracy of population viability analysis in conservation biology. Nature 404, 385 – 387 2 Coulson, T. et al. (2001) The use and abuse of population viability analysis. Trends Ecol. Evol. 16, 219– 221 3 Lacy, R.C. (1993) VORTEX: a computer simulation model for population viability analysis. Wildlife Res. 20, 45 – 65