Land abandonment in European mountains threatens habitats shaped for centuries by low-intensity agriculture and grazing. Hence, it is important to identify spatiotemporal patterns in rural abandonment, and relate them to biophysical and socioeconomic drivers. We pursued these goals in the theoretical context of transitions from traditional to productivist and then to post-productivist agriculture. We conducted a case study in a representative of southern Europe sub-mountainous marginal area that was once traditionally exploited (Pindus range, Epirus, Greece). Land cover was mapped from the outset of abandonment (years 1945, 1970, 1996 and 2015), and we subsequently calculated landscape metrics. An Intensity Analysis facilitated the comparison of rates of land cover change between time periods. By employing random forest modelling, we related socioeconomic, physiographic, geological and climatic predictors to land type occurrence and succession intensity. We found that farmland decreased from 30% to 3% during the 70 years of the study period, and that forest increased from 22% to 63%. The landscape’s heterogeneity, ecotone diversity, and spatial aggregation decreased. Abandonment and succession accelerated and relocated to lower elevation, especially during the latest time period, which was related to a second depopulation wave and livestock decrease. The remaining lowland farmlands were of productivist agriculture, and no widespread post-productivist regime was found. Thus, our study supports the view that policies, which have been mainly based on the linear transition of agricultural regimes in northern Europe, must take into account southern European mountains, where widespread abandonment can coexist with limited intensification and extensification.

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1. Individual-level traits mediate interaction outcomes and community structure. It is important, therefore, to identify the minimum number of traits that characterise ecological networks, that is, their 'minimum dimensionality'. Existing methods for estimating minimum dimensionality often lack three features associated with increased trait numbers: alternative interaction modes (e.g. feeding strategies such as active vs. sit-and-wait feeding), trait-mediated 'forbidden links' and a mechanistic description of interactions. Omitting these features can underestimate the trait numbers involved, and therefore, minimum dimensionality. We develop a 'minimum mechanistic dimensionality' measure, accounting for these three features. 2. The only input our method requires is the network of interaction outcomes. We assume how traits are mechanistically involved in alternative interaction modes. These unidentified traits are contrasted using pairwise performance inequalities between interacting species. For example, if a predator feeds upon a prey species via a typical predation mode, in each step of the predation sequence, the predator's performance must be greater than the prey's. We construct a system of inequalities from all observed outcomes, which we attempt to solve with mixed integer linear programming. The number of traits required for a feasible system of inequalities provides our minimum dimensionality estimate.

Filamentous fungi contribute to ecosystem and human-induced processes such as primary production, bioremediation, biogeochemical cycling and biocontrol. Predicting the dynamics of fungal communities can hence improve our forecasts of ecological processes which depend on fungal community structure. In this work, we aimed to develop simple theoretical models of fungal interactions with ordinary and partial differential equations, and to validate model predictions against community dynamics of a three species empirical system. We found that space is an important factor for the prediction of community dynamics, since the performance was poor for models of ordinary differential equations assuming well-mixed nutrient substrate. The models of partial differential equations could satisfactorily predict the dynamics of a single species, but exhibited limitations which prevented the prediction of empirical community dynamics. One such limitation is the arbitrary choice of a threshold local density above which a fungal mycelium is considered present in the model. In conclusion, spatially explicit simulation models, able to incorporate different factors influencing interaction outcomes and hence dynamics, appear as a more promising direction towards prediction of fungal community dynamics.2010 Mathematics Subject Classification. Primary: 92B05; Secondary: 34A34, 35Q92, 92D40.