Development of a hybrid model to interpolate monthly precipitation maps incorporating the orographic influence

[EN] This paper proposes an interpolation model for monthly rainfall in large areas of complex orography. It has been implemented in the Iberian Peninsula (continental territories of Spain and Portugal), Balearic and Canary Islands covering a territory of almost 600.000km(2). To do this a data set that comprises a total number of 11,822 monthly precipitation series has been created (11,042 provided by the Spanish Meteorological Agency and 780 provided by the National Water Resources Information System of the Portuguese Water Institute). The data set covers the period from October 1940 until September 2005. The interpolation model has been based on the assumption of two different components on monthly precipitation. The first component reflects local and seasonal characteristics and 24 different mean monthly precipitation maps (12) and SDs maps (12) compose it. It considers the varying influence of physiographic variables such as altitude and orientation. The second precipitation component reflects the synoptic pattern that dominated each month of the series and it is composed by series of anomalies of monthly precipitation (780). Anomalies have been interpolated by means of ordinary kriging once local spatial continuity was assumed. Gridded maps of each variable have been developed at 200m resolution following a hybrid methodology that implements two different interpolation techniques. The first technique applies a regression analysis to derive maps depending on altitude and orientation; the second one is a weighting technique to consider the non-linearity of the precipitation/altitude dependence. Cross validation has been applied to estimate the goodness of both techniques. Results show an average annual precipitation of 655mm/year. Although this figure is only 4% less than the estimate of MAGRAMA (2004), regional and local differences are highlighted when the spatial distribution is considered. The model constitutes a comprehensive implementation considering the availability of historical records and the need of avoiding slow calculations in large territories.Ministry of Economy, Industry and Competitiveness, Grant/Award Number: CGL2014-52571-RÁlvarez-Rodríguez, J.; Llasat, M.; Estrela Monreal, T. (2019). Development of a hybrid model to interpolate monthly precipitation maps incorporating the orographic influence. International Journal of Climatology. 39(10):3962-3975. https://doi.org/10.1002/joc.6051S396239753910AEMET.2011Atlas Climático Ibérico. (Iberian Climate Atlas) VV.AA. Agencia Estatal de Meteorología. Ministerio de Medio Ambiente. ISBN: 978‐84‐7837‐079‐5. 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Water sources and mixing in riparian wetlands revealed by tracers and geospatial analysis

Acknowledgments We thank the European Research Council (ERC) (project GA 335910 VEWA) and Natural Environment Research Council (NERC) (project NE/K000268/1) for funding and the Airborne Research and Survey Facility for conducting the aerial survey. The data used are available from the authors. In addition, we would like to thank the additional support from Audrey Innes for the sample analysis and Maria Blumstock and Mike Kennedy for assisting with field work.Peer reviewedPublisher PD

Impacts of 21st‐century climate change on montane habitat in the Madrean Sky Island Archipelago

Aim The Madrean Sky Island Archipelago is a North American biodiversity hotspot composed of similar to 60 isolated mountains that span the Cordilleran Gap between the Rocky Mountains and the Sierra Madre Occidental. Characterized by discrete patches of high-elevation montane habitat, these "sky islands" serve as stepping stones across a "sea" of desert scrub/grassland. Over this coming century, the region is expected to shift towards a warmer and drier climate. We used species distribution modelling to predict how the spatial distribution of montane habitat will be affected by climate change. Location Madrean Sky Island Archipelago, south-west United States and north-west Mexico (latitude, 29-34 degrees N; longitude, 107-112 degrees W). Methods To approximate the current distribution of montane habitat, we built species distribution models for five high-elevation species (Ceanothus fendleri, Pinus strobiformis, Quercus gambelii, Sciurus aberti, and Synuchus dubius). The resulting models were projected under multiple climate change scenarios-four greenhouse gas concentration trajectories (RCP 2.6, 4.5, 6.0, and 8.5) for each of three climate models (CCSM4, MPI-ESM-LR, and NorESM1-M)-to generate predicted distributions for the years 2050 and 2070. We performed chi-squared tests to detect any future changes to total montane habitat area, and Conover-Iman tests to evaluate isolation among the discrete montane habitat patches. Results While the climate models differ with respect to their predictions as to how severe the effects of future climate change will be, they all agree that by as early as year 2050, there will be significant montane habitat loss and increased montane habitat patch isolation across the Madrean Archipelago region under a worst-case climate change scenario (RCP 8.5). Main conclusions Our results suggest that under 21st-century climate change, the Madrean Sky Islands will become increasingly isolated due to montane habitat loss. This may affect their ability to serve as stepping stones and have negative implications for the region's biodiversity.University of Arizona Center for Insect ScienceOpen access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps

The role of competition for light among plants has long been recognized at local scales, but its potential importance for plant species' distribution at larger spatial scales has largely been ignored. Tree cover acts as a modulator of local abiotic conditions, notably by reducing light availability below the canopy and thus the performance of species that are not adapted to low-light conditions. However, this local effect may propagate to coarser spatial grains. Using 6,935 vegetation plots located across the European Alps, we fit Generalized Linear Models (GLM) for the distribution of 960 herbs and shrubs species to assess the effect of tree cover at both plot and landscape grain sizes (~ 10-m and 1-km, respectively). We ran four models with different combinations of variables (climate, soil and tree cover) for each species at both spatial grains. We used partial regressions to evaluate the independent effects of plot- and landscape-scale tree cover on plant communities. Finally, the effects on species' elevational range limits were assessed by simulating a removal experiment comparing the species' distribution under high and low tree cover. Accounting for tree cover improved model performance, with shade-tolerant species increasing their probability of presence at high tree cover whereas shade-intolerant species showed the opposite pattern. The tree cover effect occurred consistently at both plot and landscape spatial grains, albeit strongest at the former. Importantly, tree cover at the two grain sizes had partially independent effects on plot-scale plant communities, suggesting that the effects may be transmitted to coarser grains through meta-community dynamics. At high tree cover, shade-intolerant species exhibited elevational range contractions, especially at their upper limit, whereas shade-tolerant species showed elevational range expansions at both limits. Our findings suggest that the range shifts for herb and shrub species may be modulated by tree cover dynamics

A new model for ancient DNA decay based on paleogenomic meta-analysis

The persistence of DNA over archaeological and paleontological timescales in diverse environments has led to a revolutionary body of paleogenomic research, yet the dynamics of DNA degradation are still poorly understood. We analyzed 185 paleogenomic datasets and compared DNA survival with environmental variables and sample ages. We find cytosine deamination follows a conventional thermal age model, but we find no correlation between DNA fragmentation and sample age over the timespans analyzed, even when controlling for environmental variables. We propose a model for ancient DNA decay wherein fragmentation rapidly reaches a threshold, then subsequently slows. The observed loss of DNA over time may be due to a bulk diffusion process in many cases, highlighting the importance of tissues and environments creating effectively closed systems for DNA preservation. This model of DNA degradation is largely based on mammal bone samples due to published genomic dataset availability. Continued refinement to the model to reflect diverse biological systems and tissue types will further improve our understanding of ancient DNA breakdown dynamics

New methods for reconstructing geographical effects on dispersal rates and routes from large-scale radiocarbon databases

© 2014 The Authors. We introduce a methodology for reconstructing geographical effects on dispersal and diffusion patterns, using georeferenced archaeological radiocarbon databases. Fast Marching methods for modelling front propagation enable geographical scenarios to be explored regarding barriers, corridors, and favoured and unfavoured habitat types. The use of genetic algorithms as optimal search tools also enables the derivation of new geographical scenarios, and is especially useful in high-dimensional parameter spaces that cannot be characterized exhaustively due to computer runtime constraints. Model selection is guided by goodness-of-fit statistics for observed and predicted radiocarbon dates.We also introduce an important additional model output, namely, modelled phylogenies of the dispersing population or diffusing cultural entity, based on branching networks of shortest or 'least cost' paths. These 'dispersal trees' can be used as an additional tool to evaluate dispersal scenarios, based on their degree of congruence with phylogenies of the dispersing population reconstructed independently from other kinds of information.We illustrate our approach with a case study, the spread of the Neolithic transition in Europe, using a database from the literature (Pinhasi, Fort and Amerman 2005). Our methods find support for a geographical model in which dispersal is limited by an altitudinal cut-off and in which there is a climate-related latitudinal gradient in rate of spread. This model leads to a deceleration in front propagation rate with geodesic distance, which is also consistent with models of the propagation of the Neolithic transition under space competition with pre-existing populations of hunter-gatherers. Our genetic algorithms meanwhile searched the parameter space and found support for an alternative model involving fast spread along the northern Mediterranean coast and the Danube/Rhine riverine corridor. Both these models outperformed the geography-free Great Circle distance model, and both also outperformed another, almost geography-free, model that constrains dispersal to land to and near-offshore coastal waters. The adjusted coefficient of determination for modelled and observed radiocarbon dates for first arrival supports the GA-derived model; the shortest path network analysis, however, gives greater support to the model with altitudinal cut-off and latitudinal gradient in dispersal rate, since it produces branching 'dispersal trees' that are more congruent with these archaeological sites' clade memberships (as defined by archaeological material culture)