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An updated checklist of Mozambique’s vascular plants is presented. It was compiled referring to several information sources such as existing literature, relevant online databases and herbaria collections. The checklist includes 7,099 taxa (5,957 species, 605 subspecies, 537 varieties), belonging to 226 families and 1,746 genera. There are 6,804 angiosperms, 257 pteridophytes, and 38 gymnosperms. A total of 6,171 taxa are native to Mozambique, while 602 are introduced and the remaining 326 taxa were considered as uncertain status. The endemism level for Mozambique’s flora was assessed at 9.59%, including 278 strict-endemic taxa and 403 near-endemic. 58.2% of taxa are herbaceous, while shrubs and trees account respectively for 26.5% and 9.2% of the taxa. The checklist also includes ferns (3.6%), lianas (1.7%), subshrubs (0.5%) and cycads (0.3%). Fabaceae, Poaceae and Asteraceae are the three most represented families, with 891, 543 and 428 taxa, respectively. The extinction risk of 1,667 taxa is included, with 158 taxa listed as Vulnerable, 119 as Endangered and as 24 Critically Endangered. The geographical distribution, known vernacular names and plants traditional uses are also recorded.

Anogramma leptophylla is one of the rarest fern species in Balkan Peninsula. In Croatia, several localities were noted prior to this study, when its presence was confirmed with a discovery of a small population on the island of Mljet (Southern Adriatic). This was, after almost 80 years, the first reliable finding of this species along Eastern Adriatic. The establishment of A. leptophylla on the western part of the island of Mljet may be attributable to certain favourable environmental conditions, but essentially to higher air and soil humidity. Its unusual bryophyte-like life strategy, with short-living annual sporophytes, facilitates its survival under Mediterranean climate, generally unfavourable for pteridophytes.

In the Peruvian highlands, climate change and inadequate management are causing land degradation and collapse of the pastoral system. Our research project was aimed at assessing the impact of grazing on dry Puna ecosystem, as understanding and predicting vegetation changes in harsh environments in the face of different disturbance regimes is required for aware and effective management. The study area was the Salinas and Aguada Blanca National Reserve. Two experimental areas were selected, characterized by deep soils with gentle slopes and by shallow soils with steeper slopes. In each area, sites with low and high disturbance regimes were identified, and vegetation was sampled using 10 × 10 m plots. The results indicated that the environmental constraints have a marked influence on the species composition, while disturbance quantitatively affects diversity. The floristic changes observed under different disturbance intensities are mainly related to the functional differentiation of the plant communities an...

Aims Facilitation is a key process in vegetation dynamics, driving the response to natural and anthropogenic pressures. In harsh-grazed systems, palatable plants mainly survive when nested under unpalatable tussocks and shrubs. The magnitude and direction of positive interactions are driven by resource availability, extent of herbivory and type of nurse species. We hypothesized that different combinations of disturbance and environmental stress affect community composition in the dry Puna (southern Peruvian Andes) by modifying nurse types and plant interactions in magnitude and specific associations. We investigated whether different combinations of stress and disturbance influence species richness, type and frequency of occurrence of nurse and beneficiary species and magnitude and patterns of plant interactions; whether nurse species influence these interactions and target species change their interactions under different combinations of stress and disturbance and whether plant functional traits differ in the studied communities and influence the pattern of spatial interactions. Methods We selected three plant communities subject to different precipitation and management regimes: in each we laid a number of transects proportional to its extension. Data collected include species presence/absence, type of spatial interactions with nurse species and functional traits. We calculated species richness and rarefaction patterns, described the patterns of plant–plant spatial interactions and investigated the associations between nurse and other species in the three communities using indicator species analysis (ISA). We performed ISA and correlation analysis to investigate whether plant functional traits influenced facilitative interactions. Important Findings We found that different combinations of stress and disturbance shaped a complex set of responses, including changes in the nurse species set. Nurse composition influenced magnitude and direction of plant interactions under different stress intensities. Heavy disturbance increased the relative importance of facilitation, even if the overall number of facilitated species decreased. Under equivalent disturbance regimes, increased abiotic stress led to a greater importance of facilitation. Different combinations of stress and disturbance affected the community assemblage also by changing the behaviour of some non-nurse species. Both heavy disturbance and strong stress led to a decrease of trait states; with certain combinations of stress and disturbance, preferential distribution of these states was observed. We also found Journal of Plant Ecology Advance Access published September 23, 2015

The ecological land scape classification (ELC) allows the identification of homogeneous land units (LUs), which are fundamental for investigation and management purposes. ELC is particularly relevant in international cooperation programmes targeting areas characterized by very scarce and scattered thematic information. In this study, three techniques are compared to find the best classification of LUs of Socotra Island (Yemen): a Self-Organizing Map neural network, the Clustering LARge Applications method and a Two-Step clustering algorithm. In this way, three LU maps of Socotra Island were produced and the relationship between LUs and plant communities, as identified by a phytosociologiacl investigation, was analysed. Based on evaluation procedures, TS method emerged as the most suitable being able to better discriminate the plant communities so as to reach a trade-off between classification complexity and class homogeneity. Even though the identification of LUs depends on the selection of the classifica...

In the last decades, biodiversity is facing many threats related to the expansion and development of human populations. With the aim of mainstreaming conservation together with sustainable development, several conflicting necessities related to the economic, social, environmental and institutional objectives of the society have to be balanced within complex decisionmaking contexts. Conventional approaches hardly cope with these demands, and therefore conceptual models are required for understanding ecosystems form and functions and how human activities impact on them. International organisations committed to conservation and development initiatives have recognised the importance and effectiveness of an integrated, participative and adaptive approach to ecosystem management. In this perspective, computerised tools to facilitate an overall view and support informed and aware decisions are required. The Systemic Spatial Decision Support System, here presented, is a comprehensive tool for a holistic, multi-scale, spatially explicit and tailor-made approach to such complex decisional environments. The core methodology builds upon several years of experience in international conservation and development projects supported by the Italian Development Cooperation, and is complemented by an ad hoc, easily customisable software shell. Its characteristics provide an ideal framework for an effective administration of biodiversity conservation initiatives, as well as for training and consolidating expert knowledge.