Measuring impacts on species with models and metrics of varying ecological and computational complexity
Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation dec...
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Published in | Conservation biology Vol. 34; no. 6; pp. 1512 - 1524 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Blackwell Publishing Ltd
01.12.2020
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Abstract | Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data‐rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments.
Medición de los Impactos sobre las Especies con Modelos y Medidas de Complejidad Ecológica y Computacional Variante
Resumen
Las estrategias para evaluar el impacto de los escenarios de perturbación de paisaje sobre la distribución de las especies van desde las medidas basadas en patrones de presencia o hábitat hasta los modelos integrales que incluyen explícitamente a los procesos ecológicos. La elección de medidas y modelos afecta la interpretación de los impactos y las decisiones de conservación. Exploramos los impactos de tres escenarios realistas de perturbación sobre cuatro especies con características ecológicas y taxonómicas diferentes. Usamos progresivamente modelos y medidas más complejas para evaluar el impacto relativo y la clasificación de los escenarios sobre las especies. Los modelos variaron desde aquellos de distribución de especies que dependen de las suposiciones implícitas acerca de los factores ambientales y la presencia de la especie hasta aquellos modelos poblacionales explícitos con una alta parametrización espacial que incluyen los procesos ecológicos y la estocasticidad. Las medidas tuvieron un desempeño uniforme en la clasificación de los diferentes escenarios de acuerdo a la gravedad, principalmente cuando la variación en el impacto fue causada por la cantidad de hábitat presente. Sin embargo, las medidas difirieron en la clasificación para los casos en los que las dinámicas de dispersión fueron significativas en la influencia de la persistencia metapoblacional. Los impactos de los escenarios sobre las especies con una habilidad reducida de dispersión estuvieron mejor caracterizados con el uso de modelos que capturaron explícitamente estos procesos. La capacidad metapoblacional proporcionó categorías de clasificación con la correlación más consistente a aquellas provenientes de los modelos ricos en datos y con una alta parametrización e incorporó información sobre la dispersión con un reducido costo adicional de cómputo y de datos. Nuestros resultados resaltan la importancia de la consideración explícita de la ecología de las especies, la configuración espacial del hábitat y la perturbación cuando se eligen los indicadores de la persistencia de una especie. Sugerimos que se usen estrategias híbridas que mezclen modelos simples y complejos para mejorar las evaluaciones realizadas a múltiples especies.
摘要
评估景观干扰情景对物种影响的方法包括基于物种出现格局或栖息地格局的指标和纳入生态过程的综合模型等。对指标和模型的选择会影响对物种所受影响的解读和保护决策。本研究探索了三种真实干扰情景对四种不同生态学特征和类群的物种的影响。我们使用了逐渐复杂化的模型和指标评估了干扰情景对物种的相对影响和影响等级。本研究涉及的模型包括依赖于环境因素和物种出现的隐式假设的物种分布模型, 以及明确包含生态过程和随机性的高度参数化的空间显式种群模型。当影响的变化是由栖息地数量驱动时, 各种指标对不同情景的影响严重程度排序的结果一致。然而, 当扩散动态对集合种群续存有重要影响时, 不同指标的排序结果不同。使用明确考虑了扩散过程的模型可以更好地描述干扰情景对扩散能力弱的物种的影响。集合种群承载力提供了与高度参数化和数据丰富的模型最为一致的排序, 并且可以在几乎没有额外计算和数据成本的情况下加入扩散的信息。我们的结果强调了选择物种续存指标时应清楚地考虑物种的生态特征、栖息地空间结构以及干扰。我们建议使用简单和复杂模型混合的方法来改进多物种评估。【翻译: 胡怡思; 审校: 聂永刚】
Article impact statement: Not explicitly including ecological complexity in biodiversity metrics may result in misleading conclusions when assessing impacts. |
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AbstractList | Abstract
Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data‐rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments.
Medición de los Impactos sobre las Especies con Modelos y Medidas de Complejidad Ecológica y Computacional Variante
Resumen
Las estrategias para evaluar el impacto de los escenarios de perturbación de paisaje sobre la distribución de las especies van desde las medidas basadas en patrones de presencia o hábitat hasta los modelos integrales que incluyen explícitamente a los procesos ecológicos. La elección de medidas y modelos afecta la interpretación de los impactos y las decisiones de conservación. Exploramos los impactos de tres escenarios realistas de perturbación sobre cuatro especies con características ecológicas y taxonómicas diferentes. Usamos progresivamente modelos y medidas más complejas para evaluar el impacto relativo y la clasificación de los escenarios sobre las especies. Los modelos variaron desde aquellos de distribución de especies que dependen de las suposiciones implícitas acerca de los factores ambientales y la presencia de la especie hasta aquellos modelos poblacionales explícitos con una alta parametrización espacial que incluyen los procesos ecológicos y la estocasticidad. Las medidas tuvieron un desempeño uniforme en la clasificación de los diferentes escenarios de acuerdo a la gravedad, principalmente cuando la variación en el impacto fue causada por la cantidad de hábitat presente. Sin embargo, las medidas difirieron en la clasificación para los casos en los que las dinámicas de dispersión fueron significativas en la influencia de la persistencia metapoblacional. Los impactos de los escenarios sobre las especies con una habilidad reducida de dispersión estuvieron mejor caracterizados con el uso de modelos que capturaron explícitamente estos procesos. La capacidad metapoblacional proporcionó categorías de clasificación con la correlación más consistente a aquellas provenientes de los modelos ricos en datos y con una alta parametrización e incorporó información sobre la dispersión con un reducido costo adicional de cómputo y de datos. Nuestros resultados resaltan la importancia de la consideración explícita de la ecología de las especies, la configuración espacial del hábitat y la perturbación cuando se eligen los indicadores de la persistencia de una especie. Sugerimos que se usen estrategias híbridas que mezclen modelos simples y complejos para mejorar las evaluaciones realizadas a múltiples especies.
摘要
评估景观干扰情景对物种影响的方法包括基于物种出现格局或栖息地格局的指标和纳入生态过程的综合模型等。对指标和模型的选择会影响对物种所受影响的解读和保护决策。本研究探索了三种真实干扰情景对四种不同生态学特征和类群的物种的影响。我们使用了逐渐复杂化的模型和指标评估了干扰情景对物种的相对影响和影响等级。本研究涉及的模型包括依赖于环境因素和物种出现的隐式假设的物种分布模型, 以及明确包含生态过程和随机性的高度参数化的空间显式种群模型。当影响的变化是由栖息地数量驱动时, 各种指标对不同情景的影响严重程度排序的结果一致。然而, 当扩散动态对集合种群续存有重要影响时, 不同指标的排序结果不同。使用明确考虑了扩散过程的模型可以更好地描述干扰情景对扩散能力弱的物种的影响。集合种群承载力提供了与高度参数化和数据丰富的模型最为一致的排序, 并且可以在几乎没有额外计算和数据成本的情况下加入扩散的信息。我们的结果强调了选择物种续存指标时应清楚地考虑物种的生态特征、栖息地空间结构以及干扰。我们建议使用简单和复杂模型混合的方法来改进多物种评估。
【翻译: 胡怡思; 审校: 聂永刚】
Article impact statement
: Not explicitly including ecological complexity in biodiversity metrics may result in misleading conclusions when assessing impacts. Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data‐rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments. Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data‐rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments. Medición de los Impactos sobre las Especies con Modelos y Medidas de Complejidad Ecológica y Computacional Variante Resumen Las estrategias para evaluar el impacto de los escenarios de perturbación de paisaje sobre la distribución de las especies van desde las medidas basadas en patrones de presencia o hábitat hasta los modelos integrales que incluyen explícitamente a los procesos ecológicos. La elección de medidas y modelos afecta la interpretación de los impactos y las decisiones de conservación. Exploramos los impactos de tres escenarios realistas de perturbación sobre cuatro especies con características ecológicas y taxonómicas diferentes. Usamos progresivamente modelos y medidas más complejas para evaluar el impacto relativo y la clasificación de los escenarios sobre las especies. Los modelos variaron desde aquellos de distribución de especies que dependen de las suposiciones implícitas acerca de los factores ambientales y la presencia de la especie hasta aquellos modelos poblacionales explícitos con una alta parametrización espacial que incluyen los procesos ecológicos y la estocasticidad. Las medidas tuvieron un desempeño uniforme en la clasificación de los diferentes escenarios de acuerdo a la gravedad, principalmente cuando la variación en el impacto fue causada por la cantidad de hábitat presente. Sin embargo, las medidas difirieron en la clasificación para los casos en los que las dinámicas de dispersión fueron significativas en la influencia de la persistencia metapoblacional. Los impactos de los escenarios sobre las especies con una habilidad reducida de dispersión estuvieron mejor caracterizados con el uso de modelos que capturaron explícitamente estos procesos. La capacidad metapoblacional proporcionó categorías de clasificación con la correlación más consistente a aquellas provenientes de los modelos ricos en datos y con una alta parametrización e incorporó información sobre la dispersión con un reducido costo adicional de cómputo y de datos. Nuestros resultados resaltan la importancia de la consideración explícita de la ecología de las especies, la configuración espacial del hábitat y la perturbación cuando se eligen los indicadores de la persistencia de una especie. Sugerimos que se usen estrategias híbridas que mezclen modelos simples y complejos para mejorar las evaluaciones realizadas a múltiples especies. 摘要 评估景观干扰情景对物种影响的方法包括基于物种出现格局或栖息地格局的指标和纳入生态过程的综合模型等。对指标和模型的选择会影响对物种所受影响的解读和保护决策。本研究探索了三种真实干扰情景对四种不同生态学特征和类群的物种的影响。我们使用了逐渐复杂化的模型和指标评估了干扰情景对物种的相对影响和影响等级。本研究涉及的模型包括依赖于环境因素和物种出现的隐式假设的物种分布模型, 以及明确包含生态过程和随机性的高度参数化的空间显式种群模型。当影响的变化是由栖息地数量驱动时, 各种指标对不同情景的影响严重程度排序的结果一致。然而, 当扩散动态对集合种群续存有重要影响时, 不同指标的排序结果不同。使用明确考虑了扩散过程的模型可以更好地描述干扰情景对扩散能力弱的物种的影响。集合种群承载力提供了与高度参数化和数据丰富的模型最为一致的排序, 并且可以在几乎没有额外计算和数据成本的情况下加入扩散的信息。我们的结果强调了选择物种续存指标时应清楚地考虑物种的生态特征、栖息地空间结构以及干扰。我们建议使用简单和复杂模型混合的方法来改进多物种评估。【翻译: 胡怡思; 审校: 聂永刚】 Article impact statement: Not explicitly including ecological complexity in biodiversity metrics may result in misleading conclusions when assessing impacts. |
Author | Kujala, Heini Whitehead, Amy L. Nicholson, Emily Hallam, Christopher D. Wintle, Brendan A. |
Author_xml | – sequence: 1 givenname: Christopher D. orcidid: 0000-0002-3960-3859 surname: Hallam fullname: Hallam, Christopher D. email: challam@student.unimelb.edu.au organization: University of Melbourne – sequence: 2 givenname: Brendan A. orcidid: 0000-0002-4234-5950 surname: Wintle fullname: Wintle, Brendan A. organization: University of Melbourne – sequence: 3 givenname: Heini orcidid: 0000-0001-9772-3202 surname: Kujala fullname: Kujala, Heini organization: University of Melbourne – sequence: 4 givenname: Amy L. orcidid: 0000-0002-4164-9047 surname: Whitehead fullname: Whitehead, Amy L. organization: National Institute of Water and Atmospheric Research – sequence: 5 givenname: Emily orcidid: 0000-0003-2199-3446 surname: Nicholson fullname: Nicholson, Emily organization: Deakin University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32390253$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.7882/RZSNSW.1991.031 10.1073/pnas.100126797 10.1016/j.biocon.2009.05.010 10.1890/07-1306.1 10.1007/s10021-009-9229-5 10.1111/j.1523-1739.2005.00276.x 10.1073/pnas.1311491110 10.1146/annurev.ecolsys.34.011802.132419 10.1111/j.1523-1739.2006.00369.x 10.1111/ele.12189 10.1111/j.1523-1739.2004.00520.x 10.1126/science.1196624 10.1371/journal.pcbi.1004251 10.1071/WR9930387 10.1111/j.1461-0248.2006.00956.x 10.1371/journal.pone.0064852 10.1111/j.1523-1739.2005.00418.x 10.1016/0006-3207(94)90167-8 10.1093/besa/15.3.237 10.1111/j.2005.0906-7590.04285.x 10.1086/498655 10.1111/j.1461-0248.2007.01004.x 10.1111/j.1442-9993.2005.01514.x 10.1515/9781400833023.177 10.1111/j.1523-1739.2008.01066.x 10.1016/j.biocon.2011.06.015 10.5751/ES-00184-040116 10.1016/j.mbs.2008.12.004 10.1038/35008063 10.1016/j.ecolmodel.2005.03.026 10.1017/S0952836903004631 10.1017/S136794300100141X 10.1111/conl.12202 10.1111/j.1365-2664.2010.01917.x 10.1126/science.1116030 10.1016/B978-0-12-373631-4.00002-2 10.1086/338991 10.1038/23876 10.1111/conl.12159 10.1016/B978-012323448-3/50007-6 10.1111/cobi.12047 10.1002/eap.1739 10.1086/428293 10.1023/B:BIOC.0000004318.10051.48 10.1034/j.1600-0706.2002.980208.x 10.1146/annurev.ecolsys.110308.120159 10.1023/B:BIOC.0000004319.91643.9e 10.1016/j.biocon.2012.09.014 |
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Keywords | metapopulation models metapopulation capacity capacidad metapoblacional medidas de la biodiversidad 集合种群承载力 生物多样性指标 modelos metapoblacionales evaluación de impacto 影响评价 集合种群模型 biodiversity metrics impact assessment |
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References | 2009; 40 2013; 27 2000; 48 2013; 24 2000; 4 1993; 20 2002; 98 2005a; 19 2002; 159 2013; 8 1998; 396 2005; 28 2009; 12 2006; 20 2013; 16 2001 2000; 404 2000; 97 2013; 157 2005; 309 2013; 110 1994; 70 2006; 167 2009; 23 2018; 28 2012 2010 2004; 262 2008; 18 2015; 11 2006; 9 2009 2008 2007 2006 2005b; 30 2005 2004 1969; 15 1991 2009; 218 2007; 10 1999 2003; 34 2005; 19 2004; 18 2005; 165 2006; 190 2001; 4 2004; 13 2010; 330 2016 2015 2011; 48 2009; 142 2016; 9 2011; 144 e_1_2_6_51_1 e_1_2_6_53_1 Citroen S. (e_1_2_6_14_1) 2006 Santini L (e_1_2_6_54_1) 2013; 24 e_1_2_6_30_1 e_1_2_6_19_1 e_1_2_6_13_1 e_1_2_6_36_1 e_1_2_6_59_1 e_1_2_6_11_1 e_1_2_6_34_1 Possingham H (e_1_2_6_52_1) 2001 e_1_2_6_17_1 e_1_2_6_55_1 e_1_2_6_15_1 e_1_2_6_38_1 e_1_2_6_57_1 e_1_2_6_62_1 e_1_2_6_43_1 e_1_2_6_20_1 e_1_2_6_41_1 e_1_2_6_60_1 e_1_2_6_9_1 e_1_2_6_5_1 e_1_2_6_7_1 e_1_2_6_24_1 e_1_2_6_49_1 e_1_2_6_3_1 e_1_2_6_22_1 e_1_2_6_28_1 e_1_2_6_45_1 e_1_2_6_26_1 e_1_2_6_47_1 Akcakaya HR (e_1_2_6_2_1) 2000; 48 e_1_2_6_10_1 e_1_2_6_31_1 e_1_2_6_50_1 e_1_2_6_35_1 e_1_2_6_12_1 e_1_2_6_33_1 e_1_2_6_18_1 e_1_2_6_39_1 e_1_2_6_56_1 e_1_2_6_16_1 e_1_2_6_37_1 e_1_2_6_58_1 e_1_2_6_63_1 e_1_2_6_42_1 e_1_2_6_21_1 e_1_2_6_40_1 e_1_2_6_61_1 e_1_2_6_8_1 e_1_2_6_4_1 e_1_2_6_6_1 e_1_2_6_25_1 e_1_2_6_48_1 e_1_2_6_23_1 e_1_2_6_29_1 e_1_2_6_44_1 Hanski I. (e_1_2_6_32_1) 2010 e_1_2_6_27_1 e_1_2_6_46_1 |
References_xml | – volume: 23 start-page: 225 year: 2009 end-page: 229 article-title: Sensitivity analyses of spatial population viability analysis models for species at risk and habitat conservation planning publication-title: Conservation Biology – start-page: 33 year: 2009 end-page: 49 – volume: 110 start-page: 12715 year: 2013 end-page: 12720 article-title: Species–fragmented area relationship publication-title: Proceedings of the National Academy of Sciences – volume: 48 start-page: 23 year: 2000 end-page: 38 article-title: Population viability analyses with demographically and spatially structured models publication-title: Ecological Bulletins – volume: 18 start-page: 526 year: 2004 end-page: 537 article-title: Integrating landscape and metapopulation modeling approaches: viability of the Sharp‐Tailed Grouse in a dynamic landscape publication-title: Conservation Biology – year: 2005 – volume: 16 start-page: 1424 year: 2013 end-page: 1435 article-title: Predicting species distributions for conservation decisions publication-title: Ecology Letters – volume: 70 start-page: 227 year: 1994 end-page: 236 article-title: Metapopulation viability analysis of the greater glider in a wood production area publication-title: Biological Conservation – volume: 28 start-page: 1354 year: 2018 end-page: 1361 article-title: Reserve design to optimize the long‐term persistence of multiple species publication-title: Ecological Applications – volume: 24 start-page: 1 year: 2013 end-page: 6 article-title: Ecological correlates of dispersal distance in terrestrial mammals publication-title: Hystrix – volume: 48 start-page: 9 year: 2011 end-page: 13 article-title: Monitoring species abundance and distribution at the landscape scale publication-title: Journal of Applied Ecology – volume: 11 year: 2015 article-title: Metapopulation persistence in random fragmented landscapes publication-title: PLOS Computational Biology – volume: 12 start-page: 374 year: 2009 end-page: 390 article-title: GLOBIO3: a framework to investigate options for reducing global terrestrial biodiversity loss publication-title: Ecosystems – volume: 330 start-page: 1496 year: 2010 end-page: 1501 article-title: Scenarios for global biodiversity in the 21st century publication-title: Science – volume: 9 start-page: 181 year: 2016 end-page: 190 article-title: Climate and fire scenario uncertainty dominate the evaluation of options for conserving the great desert skink: resolving uncertainty in fire management publication-title: Conservation Letters – volume: 15 start-page: 237 year: 1969 end-page: 240 article-title: Some demographic and genetic consequences of environmental heterogeneity for biological control publication-title: Bulletin of the Entomological Society of America – year: 2008 – volume: 13 start-page: 189 year: 2004 end-page: 206 article-title: Ecologically differentiated rules of thumb for habitat network design–lessons from a formula publication-title: Biodiversity & Conservation – volume: 20 start-page: 387 year: 1993 end-page: 403 article-title: Home‐range estimates and habitat of the yellow‐bellied glider ( ) at Waratah Creek, New South Wales publication-title: Wildlife Research – volume: 27 start-page: 520 year: 2013 end-page: 530 article-title: Estimating extinction risk with metapopulation models of large‐scale fragmentation: metapopulation analyses of large‐ranged species publication-title: Conservation Biology – volume: 8 year: 2013 article-title: Ranking landscape development scenarios affecting natterjack toad ( ) population dynamics in central Poland publication-title: PLOS ONE – volume: 167 start-page: 260 year: 2006 end-page: 275 article-title: Distributions of habitat suitability and the abundance‐occupancy relationship publication-title: The American Naturalist – volume: 34 start-page: 487 year: 2003 end-page: 515 article-title: Effects of habitat fragmentation on biodiversity publication-title: Annual Review of Ecology, Evolution, and Systematics – volume: 18 start-page: 1002 year: 2008 end-page: 1013 article-title: Sensitivity of population viability to spatial and nonspatial parameters using grip publication-title: Ecological Applications – year: 2015 – volume: 190 start-page: 231 year: 2006 end-page: 259 article-title: Maximum entropy modeling of species geographic distributions publication-title: Ecological Modelling – volume: 30 start-page: 719 year: 2005b end-page: 738 article-title: Fauna habitat modelling and mapping: a review and case study in the Lower Hunter Central Coast region of NSW publication-title: Austral Ecology – volume: 165 start-page: 374 year: 2005 end-page: 388 article-title: Metapopulation persistence in heterogeneous landscapes: lessons about the effect of stochasticity publication-title: The American Naturalist – volume: 396 start-page: 41 year: 1998 end-page: 49 article-title: Metapopulation dynamics publication-title: Nature – volume: 144 start-page: 2354 year: 2011 end-page: 2361 article-title: Linking cost efficiency evaluation with population viability analysis to prioritize wetland bird conservation actions publication-title: Biological Conservation – volume: 9 start-page: 1049 year: 2006 end-page: 1060 article-title: A new method for conservation planning for the persistence of multiple species publication-title: Ecology Letters – volume: 20 start-page: 871 year: 2006 end-page: 881 article-title: Objectives for multiple‐species conservation planning publication-title: Conservation Biology – volume: 4 start-page: 351 year: 2001 end-page: 355 article-title: Expected minimum population size as a measure of threat publication-title: Animal Conservation – year: 2007 – volume: 40 start-page: 677 year: 2009 end-page: 697 article-title: Species Distribution models: ecological explanation and prediction across space and time publication-title: Annual Review of Ecology, Evolution, and Systematics – volume: 157 start-page: 156 year: 2013 end-page: 162 article-title: Achieving no net loss in habitat offset of a threatened frog required high offset ratio and intensive monitoring publication-title: Biological Conservation – start-page: 167 year: 2010 end-page: 188 – volume: 19 start-page: 1930 year: 2005a end-page: 1943 article-title: Utility of dynamic‐landscape metapopulation models for sustainable forest management publication-title: Conservation Biology – year: 2016 – volume: 142 start-page: 2438 year: 2009 end-page: 2448 article-title: Modelling human impacts on the Tasmanian wedge‐tailed eagle ( ) publication-title: Biological Conservation – volume: 218 start-page: 59 year: 2009 end-page: 71 article-title: Predicting metapopulation lifetime from macroscopic network properties publication-title: Mathematical Biosciences – year: 2012 – start-page: 105 year: 2004 end-page: 133 – volume: 4 start-page: 1 year: 2000 end-page: 16 article-title: Scaling of natal dispersal distances in terrestrial birds and mammals publication-title: Conservation Ecology – volume: 159 start-page: 530 year: 2002 end-page: 552 article-title: A formula for the mean lifetime of metapopulations in heterogeneous landscapes publication-title: The American Naturalist – volume: 309 start-page: 1239 year: 2005 end-page: 1241 article-title: Multiple causes of high extinction risk in large mammal species publication-title: Science – year: 2006 – volume: 19 start-page: 534 year: 2005 end-page: 546 article-title: Metapopulation extinction risk under spatially autocorrelated disturbance publication-title: Conservation Biology – start-page: 177 year: 2009 end-page: 185 – volume: 28 start-page: 593 year: 2005 end-page: 602 article-title: Low dispersal ability and habitat specificity promote extinctions in rare but not in widespread species: the Orthoptera of Germany publication-title: Ecography – volume: 10 start-page: 219 year: 2007 end-page: 229 article-title: Dispersal of Amazonian birds in continuous and fragmented forest publication-title: Ecology Letters – volume: 98 start-page: 263 year: 2002 end-page: 270 article-title: Metapopulation persistence in dynamic landscapes: the role of dispersal distance publication-title: Oikos – start-page: 1 year: 2001 end-page: 18 – volume: 404 start-page: 755 year: 2000 end-page: 758 article-title: The metapopulation capacity of a fragmented landscape publication-title: Nature – year: 1991 – volume: 262 start-page: 271 year: 2004 end-page: 280 article-title: Home range and spatial organization of the marsupial carnivore, (Marsupialia: Dasyuridae) in south‐eastern Australia publication-title: Journal of Zoology – volume: 9 start-page: 5 year: 2016 end-page: 13 article-title: Projecting global biodiversity indicators under future development scenarios: projecting biodiversity indicators publication-title: Conservation Letters – volume: 97 start-page: 5954 year: 2000 end-page: 5959 article-title: Umbrellas and flagships: efficient conservation surrogates or expensive mistakes? publication-title: Proceedings of the National Academy of Sciences – volume: 13 start-page: 207 year: 2004 end-page: 251 article-title: Predictors of species sensitivity to fragmentation publication-title: Biodiversity & Conservation – year: 1999 – ident: e_1_2_6_27_1 doi: 10.7882/RZSNSW.1991.031 – ident: e_1_2_6_7_1 doi: 10.1073/pnas.100126797 – ident: e_1_2_6_9_1 doi: 10.1016/j.biocon.2009.05.010 – ident: e_1_2_6_13_1 doi: 10.1890/07-1306.1 – ident: e_1_2_6_5_1 doi: 10.1007/s10021-009-9229-5 – ident: e_1_2_6_62_1 doi: 10.1111/j.1523-1739.2005.00276.x – ident: e_1_2_6_34_1 doi: 10.1073/pnas.1311491110 – ident: e_1_2_6_20_1 doi: 10.1146/annurev.ecolsys.34.011802.132419 – ident: e_1_2_6_45_1 doi: 10.1111/j.1523-1739.2006.00369.x – ident: e_1_2_6_29_1 doi: 10.1111/ele.12189 – ident: e_1_2_6_4_1 doi: 10.1111/j.1523-1739.2004.00520.x – volume-title: Bachelor of Forest Science, Honours year: 2006 ident: e_1_2_6_14_1 contributor: fullname: Citroen S. – ident: e_1_2_6_59_1 – ident: e_1_2_6_36_1 – ident: e_1_2_6_47_1 doi: 10.1126/science.1196624 – ident: e_1_2_6_26_1 doi: 10.1371/journal.pcbi.1004251 – ident: e_1_2_6_28_1 doi: 10.1071/WR9930387 – ident: e_1_2_6_46_1 doi: 10.1111/j.1461-0248.2006.00956.x – ident: e_1_2_6_24_1 doi: 10.1371/journal.pone.0064852 – ident: e_1_2_6_39_1 doi: 10.1111/j.1523-1739.2005.00418.x – ident: e_1_2_6_51_1 doi: 10.1016/0006-3207(94)90167-8 – ident: e_1_2_6_40_1 doi: 10.1093/besa/15.3.237 – ident: e_1_2_6_53_1 doi: 10.1111/j.2005.0906-7590.04285.x – ident: e_1_2_6_25_1 doi: 10.1086/498655 – ident: e_1_2_6_3_1 – ident: e_1_2_6_60_1 doi: 10.1111/j.1461-0248.2007.01004.x – ident: e_1_2_6_63_1 doi: 10.1111/j.1442-9993.2005.01514.x – ident: e_1_2_6_31_1 doi: 10.1515/9781400833023.177 – ident: e_1_2_6_44_1 doi: 10.1111/j.1523-1739.2008.01066.x – ident: e_1_2_6_6_1 – ident: e_1_2_6_56_1 doi: 10.1016/j.biocon.2011.06.015 – volume: 48 start-page: 23 year: 2000 ident: e_1_2_6_2_1 article-title: Population viability analyses with demographically and spatially structured models publication-title: Ecological Bulletins contributor: fullname: Akcakaya HR – ident: e_1_2_6_58_1 doi: 10.5751/ES-00184-040116 – start-page: 1 volume-title: Conservation biology: research priorities for the next decade year: 2001 ident: e_1_2_6_52_1 contributor: fullname: Possingham H – ident: e_1_2_6_15_1 doi: 10.1016/j.mbs.2008.12.004 – ident: e_1_2_6_33_1 doi: 10.1038/35008063 – ident: e_1_2_6_48_1 doi: 10.1016/j.ecolmodel.2005.03.026 – ident: e_1_2_6_10_1 doi: 10.1017/S0952836903004631 – ident: e_1_2_6_42_1 doi: 10.1017/S136794300100141X – ident: e_1_2_6_11_1 doi: 10.1111/conl.12202 – ident: e_1_2_6_38_1 doi: 10.1111/j.1365-2664.2010.01917.x – ident: e_1_2_6_12_1 doi: 10.1126/science.1116030 – ident: e_1_2_6_8_1 doi: 10.1016/B978-0-12-373631-4.00002-2 – ident: e_1_2_6_23_1 doi: 10.1086/338991 – ident: e_1_2_6_41_1 – ident: e_1_2_6_19_1 – ident: e_1_2_6_30_1 doi: 10.1038/23876 – start-page: 167 volume-title: Spatial ecology year: 2010 ident: e_1_2_6_32_1 contributor: fullname: Hanski I. – ident: e_1_2_6_61_1 doi: 10.1111/conl.12159 – volume: 24 start-page: 1 year: 2013 ident: e_1_2_6_54_1 article-title: Ecological correlates of dispersal distance in terrestrial mammals publication-title: Hystrix contributor: fullname: Santini L – ident: e_1_2_6_16_1 – ident: e_1_2_6_18_1 doi: 10.1016/B978-012323448-3/50007-6 – ident: e_1_2_6_55_1 doi: 10.1111/cobi.12047 – ident: e_1_2_6_57_1 doi: 10.1002/eap.1739 – ident: e_1_2_6_22_1 doi: 10.1086/428293 – ident: e_1_2_6_21_1 doi: 10.1023/B:BIOC.0000004318.10051.48 – ident: e_1_2_6_37_1 doi: 10.1034/j.1600-0706.2002.980208.x – ident: e_1_2_6_17_1 doi: 10.1146/annurev.ecolsys.110308.120159 – ident: e_1_2_6_43_1 – ident: e_1_2_6_35_1 doi: 10.1023/B:BIOC.0000004319.91643.9e – ident: e_1_2_6_49_1 – ident: e_1_2_6_50_1 doi: 10.1016/j.biocon.2012.09.014 |
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SubjectTerms | Benchmarking biodiversity metrics capacidad metapoblacional Complexity Computer applications Conservation of Natural Resources Dispersal Dispersion Disturbance Ecological effects Ecosystem Environmental factors evaluación de impacto Geographical distribution Habitats impact assessment medidas de la biodiversidad metapopulation capacity metapopulation models Metapopulations modelos metapoblacionales Models, Biological Parameterization Population Dynamics Species Stochasticity 影响评价 生物多样性指标 集合种群承载力 集合种群模型 |
Title | Measuring impacts on species with models and metrics of varying ecological and computational complexity |
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