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We measured LHS traits in 41 Anemone nemorosa and 44 Milium effusum populations along a 1900-2300 km latitudinal gradient from N France to N Sweden. We then applied multilevel models to identify the effects of regional (temperature, latitude) and local (soil fertility and acidity, overstorey canopy cover) environmental factors on LHS traits. Both species displayed a significant 4% increase in plant height with every degree northward shift (almost a two-fold plant height difference between the southernmost and northernmost populations). Neither seed mass nor SLA showed a significant latitudinal cline. Temperature had a large effect on the three LHS traits of Anemone. Latitude, canopy cover and soil nutrients were related to the SLA and plant height of Milium. None of the investigated variables appeared to be related to the seed mass of Milium. The variation in LHS traits indicates that the ecological strategy determined by the position of each population in this three-factor triangle is not constant along the latitudinal gradient. The significant increase in plant height suggests greater competitive abilities for both species in the northernmost populations. We also found that the studied environmental factors affected the LHS traits of the two species on various scales: spring-flowering Anemone was affected more by temperature, whereas early-summer flowering Milium was affected more by local and other latitude-related factors. Finally, previously reported cross-species correlations between LHS traits and latitude were generally unsupported by our within-species approach

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Freshwater ponds deliver a broad range of ecosystem services (ESS). Taking into account this broad range of services to attain cost-effective ESS delivery is an important challenge facing integrated pond management. To assess the strengths and weaknesses of an ESS approach to support decisions in integrated pond management, we applied it on a small case study in Flanders, Belgium. A Bayesian belief network model was developed to assess ESS delivery under three alternative pond management scenarios: intensive fish farming (IFF), extensive fish farming (EFF) and nature conservation management (NCM). A probabilistic cost-benefit analysis was performed that includes both costs associated with pond management practices and benefits associated with ESS delivery. Whether or not a particular ESS is included in the analysis affects the identification of the most preferable management scenario by the model. Assessing the delivery of a more complete set of ecosystem services tends to shift the results away from intensive management to more biodiversity-oriented management scenarios. The proposed methodology illustrates the potential of Bayesian belief networks. BBNs facilitate knowledge integration and their modular nature encourages future model expansion to more encompassing sets of services. Yet, we also illustrate the key weaknesses of such exercises, being that the choice whether or not to include a particular ecosystem service may determine the suggested optimal management practice.