Correlations among plant traits often reflect important trade‐offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to “spectra” or “leading dimensions,” whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the “leaf economics spectrum,” “biomass allocation dimension,” “seed dimension,” and carbon and nitrogen concentrations. This literature‐based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature‐based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below‐ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem‐specific length were “hub” traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature‐based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a “size” module, a “seed” module, two modules representing C and N concentrations in plant organs, and a “partitioning” module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole‐plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.

Context Most protected areas are managed based on objectives related to scientific ecological knowledge of species and ecosystems. However, a core principle of sustainability science is that understanding and including local ecological knowledge, perceptions of ecosystem service provision and landscape vulnerability will improve sustainability and resilience of social-ecological systems. Here, we take up these assumptions in the context of protected areas to provide insight on the effectiveness of nature protection goals, particularly in highly human-influenced landscapes. Objectives We examined how residents’ ecological knowledge systems, comprised of both local and scientific, mediated the relationship between their characteristics and a set of variables that represented perceptions of ecosystem services, landscape change, human-nature relationships, and impacts. Methods We administered a face-to-face survey to local residents in the Sierra de Guadarrama protected areas, Spain. We used bi- and multi-variate analysis, including partial least squares path modeling to test our hypotheses. Results Ecological knowledge systems were highly correlated and were instrumental in predicting perceptions of water-related ecosystem services, landscape change, increasing outdoors activities, and human-nature relationships. Engagement with nature, socio-demographics, trip characteristics, and a rural–urban gradient explained a high degree of variation in ecological knowledge. Bundles of perceived ecosystem services and impacts, in relation to ecological knowledge, emerged as social representation on how residents relate to, understand, and perceive landscapes. Conclusions Our findings provide insight into the interactions between ecological knowledge systems and their role in shaping perceptions of local communities about protected areas. These results are expected to inform protected area management and landscape sustainability.

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