FORUM: Ecological networks: the missing links in biomonitoring science.
FORUM: Ecological networks: the missing links in biomonitoring science.
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DOI：
10.1111/1365-2664.12300
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发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Woodward G
中科院分区：
文献类型：
--
作者：
Gray C;Baird DJ;Baumgartner S;Jacob U;Jenkins GB;O'Gorman EJ;Lu X;Ma A;Pocock MJ;Schuwirth N;Thompson M;Woodward G
监测人为影响对于管理和保护生态系统至关重要，但目前的生物监测方法缺乏处理压力源对物种及其在复杂自然系统中相互作用的影响所需的工具。生态网络（营养或互惠）可以为生态系统退化提供新的见解，为当前分类学受限的方案增加价值。我们重点介绍一些例子来展示如何使用新的网络方法来解释生态反应。 合成与应用。用来自文献的相互作用数据增强常规生物监测数据，并在可行的情况下补充来自直接观察的真实数据，使我们能够开始表征跨环境梯度的大量生态网络。通过采用新兴技术和新颖的分析方法可以加速这一过程，使生物监测超越简单的通过/失败方案，并解决许多只能从基于网络的角度理解的生态反应。用来自文献的相互作用数据增强常规生物监测数据，并在可行的情况下补充来自直接观察的真实数据，使我们能够开始表征跨环境梯度的大量生态网络。通过采用新兴技术和新颖的分析方法可以加速这一过程，使生物监测超越简单的通过/失败方案，并解决许多只能从基于网络的角度理解的生态反应。
Monitoring anthropogenic impacts is essential for managing and conserving ecosystems, yet current biomonitoring approaches lack the tools required to deal with the effects of stressors on species and their interactions in complex natural systems. Ecological networks (trophic or mutualistic) can offer new insights into ecosystem degradation, adding value to current taxonomically constrained schemes. We highlight some examples to show how new network approaches can be used to interpret ecological responses. Synthesis and applications. Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground‐truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network‐based perspective. Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground‐truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network‐based perspective.
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影响因子：
6.3
作者：
Kremen, C.;Ullmann, K. S.;Thorp, R. W.
通讯作者：
Thorp, R. W.
影响因子：
56.9
作者：
Burkle, Laura A.;Marlin, John C.;Knight, Tiffany M.
通讯作者：
Knight, Tiffany M.
影响因子：
5.7
作者：
Forup, Mikael Lytzau;Henson, Kate S. E.;Memmott, Jane
通讯作者：
Memmott, Jane
影响因子：
4.8
作者：
Milns, Isobel;Beale, Colin M.;Smith, V. Anne
通讯作者：
Smith, V. Anne
影响因子：
9.2
作者：
Bluethgen, Nico;Menzel, Florian;Bluethgen, Nils
通讯作者：
Bluethgen, Nils