Ecological Networks in Managed Ecosystems: Connecting Structure to Services
Bibliographic record
Abstract
Introduction Ecological networks represent a cornerstone of ecology: they describe and evaluate the links between form and function in multispecies systems, such as food-web structure and dynamics, and they connect different scales and levels of biological organization (Moore and de Ruiter, 2012; Wall et al., 2015). These properties of being able to elucidate both the structure within complex systems and their scaling indicate that ecological networks and network theory could be widely applied to practical problems, including management decision-making processes such as the design of nature reserves and the preservation of ecosystem services. While the study of networks – initially food-web compartments, then community assemblages, and more recently mutualistic networks – is now firmly embedded in ecology (Levins, 1974; Cohen, 1978; Hunt et al., 1987; Beare et al., 1992; Solé and Montoya, 2001; Berlow et al., 2004; Moore et al., 2004; Cohen and Carpenter, 2005; Thébault and Fontaine, 2010; Moore and de Ruiter, 2012; Pocock et al., 2012; Neutel and Thorne, 2014), the application of such approaches to managed ecosystems has lagged far behind. There are many explanations for this disconnection between agro-ecology and ecology, not least the pervasive view that because they are human managed and disturbed agro-systems are fundamentally “unnatural” and different from natural ecosystems: most ecologists prefer to study so-called natural ecosystems, even though most of these have in fact been heavily influenced by mankind for centuries either directly by local activity or indirectly by long-distance pollution. Network approaches have rarely been applied to agriculture and forestry, which is perhaps surprising given that much of the early, integrated management research (e.g., from the seminal works by Von Carlowitz, 1713, and Von Liebig, 1840, onwards) and the study of networks that stimulated major advances in ecological theory was grounded in attempts to improve agricultural and timber production (Wardle, 2002; Schröter et al., 2003; Coleman et al., 2004; Moore and de Ruiter, 2012, and the references therein). The last two decades have seen a hiatus in advances in agro-ecology in this area, while new network theory and empirical studies have elucidated the roles of body size in ecosystems and the study of plant–pollinator networks and other mutualistic webs have redefined our understanding of general ecology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".