Long-term deforestation in NW Spain: linking the Holocene fire history to vegetation change and human activities

The Holocene fire regime is thought to have had a key role in deforestation and shrubland expansion in Galicia (NW Spain) but the contribution of past societies to vegetation burning remains poorly understood. This may be, in part, due to the fact that detailed fire records from areas in close proximity to archaeological sites are scarce. To fill this gap, we performed charcoal analysis in five colluvial soils from an archaeological area (Campo Lameiro) and compared the results to earlier studies from this area and palaeo-ecological literature from NW Spain. This analysis allowed for the reconstruction of the vegetation and fire dynamics in the area during the last ca 11 000 yrs. In the Early Holocene, Fabaceae and Betula sp. were dominant in the charcoal record. Quercus sp. started to replace these species around 10 000 cal BP, forming a deciduous forest that prevailed during the Holocene Thermal Maximum until ～5500 cal BP. Following that, several cycles of potentially fire-induced forest regression with subsequent incomplete recovery eventually led to the formation of an open landscape dominated by shrubs (Erica sp. and Fabaceae). Major episodes of forest regression were (1) ～5500–5000 cal BP, which marks the mid-Holocene cooling after the Holocene Thermal Maximum, but also the period during which agropastoral activities in NW Spain became widespread, and (2) ～2000–1500 cal BP, which corresponds roughly to the end of the Roman Warm Period and the transition from the Roman to the Germanic period. The low degree of chronological precision, which is inherent in fire history reconstructions from colluvial soils, made it impossible to distinguish climatic from human-induced fires. Nonetheless, the abundance of synanthropic pollen indicators (e.g. Plantago lanceolata and Urtica dioica) since at least ～6000 cal BP strongly suggests that humans used fire to generate and maintain pasture.     

Ressi experimental catchment: Ecohydrological research in the Italian pre-Alps

Ressi is a small (2.4 ha) forested catchment located in the Italian pre-Alps. The site became an experimental catchment to investigate the water fluxes in the soil–plant–atmosphere continuum and the impact of vegetation on runoff generation in 2012. The elevation of the catchment ranges from 598 to 721 m a.s.l. and the climate is humid temperate. The bedrock consists of rhyolites and dacites; the soil is a Cambisol. The catchment is covered by a dense forest, dominated by beech, chestnut, maple, and hazel trees. The field set up includes measurements of the rainfall in an open area, streamflow at the outlet, soil moisture at various depths and locations, and depth to water table in six piezometers at a 5- or 10-min interval. Samples of precipitation, stream water, shallow groundwater and soil water are collected monthly for tracer analysis (stable isotopes (²H and ¹⁸O), electrical conductivity and major ions), and during selected rainfall–runoff events to determine the contribution of the various sources to runoff. Since 2017, soil and plant water samples have been collected to determine the sources of tree transpiration. Data collected in the period 2012–2016 are publicly available. Data collection is ongoing, and the data set is expected to be updated on an annual basis to include the most recent measurements.     

Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Bismuth‐melt trails trapped in cassiterite–quartz veins

Native bismuth in the form of metallic melt has been considered instrumental to the formation of some metallic ore deposits via a mechanism dubbed the “Liquid Bismuth Collector Model.” Here, we provide petrographical documentation of trail‐forming, μm‐sized blebs of native bismuth in cassiterite–quartz veins from the Santa Bárbara greisen Sn deposit in the Rondônia tin province of northern Brazil. These inclusions suggest the trapping of a Bi melt that took place during vein formation, in a mechanism similar to the entrapment of fluid inclusions.     

Upper Cretaceous marine‐continental transition (Leonese Area,NW Spain) defined from integrated outcrop and seismic stratigraphy

The Upper Cretaceous succession of the Leonese Area (NW Spain) comprises mixed clastic and carbonate sediments. This succession is divided into two lithostratigraphic units, the Voznuevo Member and the Boñar Formation, which represent fluvial, shoreface, intertidal, subtidal and open‐shelf sedimentary environments. Regional seismic interpretation and sequence stratigraphic analysis have allowed the study of lateral and vertical changes in the sedimentary record and the definition of third‐order levels of stratigraphic cyclicity. On the basis of these data, the succession can be divided into two second‐order depositional sequences (DS‐1 and DS‐2), incorporating three system tracts in a lowstand to transgressive to highstand system tract succession (LST–TST–HST). These sequences are composed of fluvial systems at the base with palaeocurrents that flowed westward and south‐westward. The upper part of DS‐1 (Late Albian–Middle Turonian) shows evidence of intertidal to subtidal and offshore deposits. DS‐2 (Late Turonian–Campanian) comprises intertidal to subtidal, tidal flat, shallow marine and lacustrine deposits and interbedded fluvial deposits. Two regressive–transgressive cycles occurred in the area related to eustatic controls. The evolution of the basin can be explained by base‐level changes and associated shifts in depositional trends of successive retrogradational episodes. By using isobath and isopach maps, the main palaeogeographic features of DS‐1 and DS‐2 were constrained, namely coastline positions, the existence and orientation of corridors through which fluvial networks were channelled and the location of the main depocentres of the basin. Sedimentation on the Upper Cretaceous marine platform was mainly controlled by (i) oscillations of sea level and (ii) the orientation of Mesozoic faults, which induced sedimentation along depocentres. Copyright © 2013 John Wiley & Sons, Ltd.     

Integrating cellular automata,artificial neural network,and fuzzy set theory to simulate threatened orchards: application to Maragheh,Iran

Urbanization processes challenge the growth of orchards in many cities in Iran. In Maragheh, orchards are crucial ecological, economical, and tourist sources. To explore orchards threatened by urban expansion, this study first aims to develop a new model by coupling cellular automata (CA) and artificial neural network with fuzzy set theory (CA–ANN–Fuzzy). While fuzzy set theory captures the uncertainty associated with transition rules, the ANN considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes. Second, the CA–ANN–Fuzzy model is compared with two existing approaches, namely a basic CA and a CA coupled with an ANN (CA–ANN). Third, we quantify the amount of orchard loss during the last three decades as well as for the upcoming years up to 2025. Results show that CA–ANN–Fuzzy with 83% kappa coefficient performs significantly better than conventional CA (with 51% kappa coefficient) and CA–ANN (with 79% kappa coefficient) models in simulating orchard loss. The historical data shows a considerable loss of 26% during the last three decades, while the CA–ANN–Fuzzy simulation reveals a considerable future loss of 7% of Maragheh’s orchards in 2025 due to urbanization. These areas require special attention and must be protected by the local government and decision-makers.