Exploring the causes of high biodiversity of Iberian dehesas: the importance of wood pastures and marginal habitats

Abstract

In extensive low input farming and in agroforestry systems, the importance for biodiversity of managed productive fields with respect to unmanaged marginal habitats that occupy a low proportion of farm surface, is still poorly understood, contrasting with the well-known key importance of marginal habitats in intensive systems. We analyzed the importance of open and wood pastures and marginal habitats for species richness of Iberian dehesas in Central-Western Spain. We sampled 155 plots classified into 9 general habitat categories: wood pastures (n = 41 plots); open pastures dominated by annual plants (n = 11), by perennial plants (n = 15) and co-dominated by annuals and perennial plants (n = 16); shrublands (n = 19); agricultural crops (n = 12); herbaceous strips (n = 10); woody strips (n = 11); and water bodies (n = 10). In each plot we measured the abundance and species richness of four taxonomic groups: vascular plants, bees, spiders, and earthworms. We detected 431 plant species (37 ± 2.5 CI 95 in 100 m 2 on average), 60 bee species (3.1 ± 1.1 in 600 m 2 ), 128 spider species (7.4 ± 1.2 in 1.5 m 2 ) and 18 earthworm species (2.5 ± 1.0 in 0.27 m 2 ) in 145 sampling plots. Wood pastures supported fewer species of spiders and earthworms at the plot level, but more plants and earthworm species at the landscape level than open pastures. The low proportion of shared species among habitats and among plots within each habitat type, and the high proportion of species found in unique plots or habitats indicated that every habitat contributes to farm biodiversity. Overall, our extensive survey confirms the hypothesis that the high diversity of dehesas depends on the coexistence within farms of a wide mosaic of habitats, including marginal habitats, which seemed to harbor a disproportionately high number of species as compared to their small extent. Results support policy measures for the maintenance of farm keystone structures such as linear features, small wood/shrub patches and ponds, and reveal that these measures should not be exclusively applied to more intensive farming systems.

N : P stoichiometry and habitat effects on Mediterranean savanna seasonal root dynamics

“…Minirhizotrons are non-destructive measurements but require the presence of an observatory. Artefacts due to observatory presence are particularly acute close to the time of installation (Joslin et al, 2001) and there is little consensus towards an appropriate time to leave observatories before good data are collected (see Johnson et al, 2001;Mueller et al, 2018;Strand et al, 2018). Slow-growing species may also take considerably longer than this time to equilibrate (Strand et al, 2018) but most (perennial) Q. ilex roots probably reached deeper soil layers than our observations (Moreno et al, 2005), causing both of our methods to mostly sample herbaceous layer roots.…”

“…While root biomass is a direct measure of root C stocks, it is also generally highly inconsistent in experimental responses (e.g. Arnone et al, 2000;Mueller et al, 2018). Other physical attributes (such as spatial distribution of root systems, or traits such as root length density, RLD) may be more relevant for explaining plant function and not just standing biomass as they relate to functional properties; for example as root diameter and density vary, RLD relates more directly than biomass to soil exploration.…”

Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem

“…Migliavacca et al, [40] found that differences in LAD related to nutrient availability could explain strong differences in the optical properties of the grassland layer in the same study site of this article. Former works accounted for 145 different species throughout the year in the study area [44]. Such biodiversity makes unfeasible scaling through species-based metrics such as in [78], and makes valuable use of modeling approaches that can be validated at a proximal sensing scale to later produce remote estimates of vegetation properties, as in this work.…”

“…The grass layer covers almost the totality of the soil, even under the tree canopy, and combines different functional types: grasses, forbs, and legumes [40]. This layer is highly dynamic [41] and biodiverse in space and time, depending on the availability of resources [42][43][44]. Its strong temporal dynamics are characterized by two seasonal biomass peaks with a maximum in spring and a second maximum after the summer decay, following the soil re-wetting phase.…”

Exploring the effects of pasture trees on plant community patterns

“…Most semi-natural grasslands in the area have some wooded cover, but with a large variation in terms of tree density, ranging from just a few to more than 200 trees/ha (Jakobsson & Lindborg, 2015). Wooded pastures like these are essential for biodiversity conservation (Dicks et al, 2014;Mosquera-Losada et al, 2012) due to management continuity and the complex habitat structure that generate high biodiversity values across taxa (Bugalho, Caldeira, Pereira, Aronson, & Pausas, 2011;Hartel & Plieninger, 2014;Moreno et al, 2016).…”