New data on amphibians (Amphibia) and reptiles (Reptilia) in Natural monument“Tajan” (BiH)

U ovom radu autori prezentuju nalaze faune vodozemaca i gmizavaca Spomenika prirode „Tajan“ i njegovog šireg područja koji su prikupljeni prilikom Trećeg međunarodnog biološkog kampa „Tajan 2013“. Pored vlastitih istraživanja, dodani su i postojeći literaturni podaci o koji su vezani za herpetofaunu Spomenika prirode „Tajan“, kao i fotodokumentacija koja je ustupljena ljubaznošću od strane društva SNIK „Atom“. Ovo istraživanje potvrđuje da najmanje deset vrsta vodozemaca i jedanaest vrsta gmizavaca živi na širem području Spomenika prirode „Tajan“. U ovom radu se također navodi i prvi nalaz obrambenog ponašanja (unken refleks) kod vrste Rana graeca.In this paper authors present findings of amphibians and reptiles in wider area of Natural monument “Tajan” during the Third international biology camp \u27\u27Tajan 2013\u27\u27. Besides personal studies, authors include available data related to herpetofauna in Tajan and some foto documentation from association SNIK “Atom”. This study confirmed that at least ten species of amphibians and eleven species of reptiles lives in wider area of Natural monument “Tajan”. This paper also gives the first record of defensive behaviour (unken reflex) in species Rana graeca

Biodiversity of herpetofauna of the Prenj and Čvrsnica Mts. (Bosnia and Herzegovina)

Herpetološka istraživanja planina Prenj i Čvrsnica imaju relativno dugu tradiciju, no znanje o njima još uvijek nije zadovoljavajuće. Literaturni podaci o herpetofauni Prenja i Čvrsnice su stari, sporadični i rijetki. Cilj istraživanja bio je prikupiti sve dostupne podatke o herpetofauni navedenih planina i odrediti važnost područja za bioraznolikost herpetofaune Bosne i Hercegovine (BiH). Analiza podataka je pokazala da na Prenju i Čvrsnici živi 11 vrsta vodozemaca (55 % od ukupnog broja vodozemaca u BiH) i 24 vrste gmazova (82.7% od ukupnog broja gmazova u BiH) te da se razlikuju po vertikalnoj i horizontalnoj distribuciji. Opažena je izuzetno visoka bioraznolikost koja je posljedica zemljopisnog položaja planina koje graniče sa mediteranskom klimatskom zonom u BiH.Herpetological research of the Prenj and Čvrsnica mountains has a relatively long tradition, but not enough scientific attention was devoted to them. Literature data on herpetofauna of Prenj and Čvrsnica is old, sporadic and rare. The aim of this research was to collect all data on the herpetofauna for the given mountains and determine the importance of the area for the herpetofaunal biodiversity of Bosnia and Herzegovina (B-H). The analysis of data showed that the area of Prenj and Čvrsnica is inhabited by 11 species of amphibians (55 % of the total number of amphibians in B-H) and 24 species of reptiles (82.7% of the total number of reptiles in B-H) which differ in vertical and horizontal distribution. The registered biodiversity is extremely high and is a consequence of the geographical position of these mountains which border the Mediterranean climate zone in B-H

Determinants of the distribution of utility-scale photovoltaic power facilities across the globe

Photovoltaic power (PV) is the fastest-growing source of renewable electricity. Making reliable scenarios of PV deployment requires information on what drives the spatial distribution of PV facilities. Here we empirically derive the determinants of the distribution of utility-scale PV facilities across six continents, using a mixed effects logistic regression modelling approach relating the occurrence of over 10 000 PV facilities to a set of potential determinants as well as accounting for country and spatially correlated random effects. Our regression models explain the distribution of PV facilities with high accuracy, with travel times to settlements and irradiation as the main determinants. In contrast, our results suggest that land cover types are not strong determinants of the PV distribution, except for Asia and Africa where the PV distribution is related to the presence of agriculture, short natural vegetation and bare land. For Europe and Asia a considerable part of the variance in PV distribution is explained by inter-country differences in factors not included in our fixed determinants. Relevant determinants identified in our study are in line with the main assumptions made in cost of electricity (COE) maps used in the IMAGE integrated assessment model (IAM). However, we found correlations (Spearman ρ) of −0.18-0.54 between our PV probability maps and IMAGE’s COE maps. These may partly be explained by conceptual differences between our empirically-derived probability maps and the COE maps, but we also recommend using higher-resolution maps of PV potential and COE computations such as used in IAMs

Large carnivore expansion in Europe is associated with human population density and land cover changes

Aim: The recent recovery of large carnivores in Europe has been explained as resulting from a decrease in human persecution driven by widespread rural land abandonment, paralleled by forest cover increase and the consequent increase in availability of shelter and prey. We investigated whether land cover and human population density changes are related to the relative probability of occurrence of three European large carnivores: the grey wolf (Canis lupus), the Eurasian lynx (Lynx lynx) and the brown bear (Ursus arctos).Location: Europe, west of 64 degrees longitude.Methods: We fitted multi-temporal species distribution models using >50,000 occurrence points with time series of land cover, landscape configuration, protected areas, hunting regulations and human population density covering a 24-year period (1992-2015). Within the temporal window considered, we then predicted changes in habitat suitability for large carnivores throughout Europe.Results: Between 1992 and 2015, the habitat suitability for the three species increased in Eastern Europe, the Balkans, North-West Iberian Peninsula and Northern Scandinavia, but showed mixed trends in Western and Southern Europe. These trends were primarily associated with increases in forest cover and decreases in human population density, and, additionally, with decreases in the cover of mosaics of cropland and natural vegetation.Main conclusions: Recent land cover and human population changes appear to have altered the habitat suitability pattern for large carnivores in Europe, whereas protection level did not play a role. While projected changes largely match the observed recovery of large carnivore populations, we found mismatches with the recent expansion of wolves in Central and Southern Europe, where factors not included in our models may have played a dominant role. This suggests that large carnivores' co-existence with humans in European landscapes is not limited by habitat availability, but other factors such as favourable human tolerance and policy

Assessing the reliability of species distribution projections in climate change research

Aim: Forecasting changes in species distribution under future scenarios is one of the most prolific areas of application for species distribution models (SDMs). However, no consensus yet exists on the reliability of such models for drawing conclusions on species’ distribution response to changing climate. In this study, we provide an overview of common modelling practices in the field and assess the reliability of model predictions using a virtual species approach. Location: Global. Methods: We first review papers published between 2015 and 2019. Then, we use a virtual species approach and three commonly applied SDM algorithms (GLM, MaxEnt and random forest) to assess the estimated and actual predictive performance of models parameterized with different modelling settings and violations of modelling assumptions. Results: Most SDM papers relied on single models (65%) and small samples (N < 50, 62%), used presence-only data (85%), binarized models' output (74%) and used a split-sample validation (94%). Our simulation reveals that the split-sample validation tends to be over-optimistic compared to the real performance, whereas spatial block validation provides a more honest estimate, except when datasets are environmentally biased. The binarization of predicted probabilities of presence reduces models’ predictive ability considerably. Sample size is one of the main predictors of the real model accuracy, but has little influence on estimated accuracy. Finally, the inclusion of ecologically irrelevant predictors and the violation of modelling assumptions increases estimated accuracy but decreases real accuracy of model projections, leading to biased estimates of range contraction and expansion. Main conclusions: Our ability to predict future species distribution is low on average, particularly when models’ predictions are binarized. A robust validation by spatially independent samples is required, but does not rule out inflation of model accuracy by assumption violation. Our findings call for caution in the application and interpretation of SDM projections under different climates.Peer reviewe

Behavior of redox – sensitive elements (Ti, As, V and Fe) in a clay pit samples with and without Al-normalization

Graphical abstract

Behavior of redox – sensitive elements (Ti, As, V and Fe) in a clay pit samples with and without Al-normalization

Graphical abstract

Determinants of the distribution of utility-scale photovoltaic power facilities across the globe

Photovoltaic power (PV) is the fastest-growing source of renewable electricity. Making reliable scenarios of PV deployment requires information on what drives the spatial distribution of PV facilities. Here we empirically derive the determinants of the distribution of utility-scale PV facilities across six continents, using a mixed effects logistic regression modelling approach relating the occurrence of over 10 000 PV facilities to a set of potential determinants as well as accounting for country and spatially correlated random effects. Our regression models explain the distribution of PV facilities with high accuracy, with travel times to settlements and irradiation as the main determinants. In contrast, our results suggest that land cover types are not strong determinants of the PV distribution, except for Asia and Africa where the PV distribution is related to the presence of agriculture, short natural vegetation and bare land. For Europe and Asia a considerable part of the variance in PV distribution is explained by inter-country differences in factors not included in our fixed determinants. Relevant determinants identified in our study are in line with the main assumptions made in cost of electricity (COE) maps used in the IMAGE integrated assessment model (IAM). However, we found correlations (Spearman ρ) of −0.18-0.54 between our PV probability maps and IMAGE’s COE maps. These may partly be explained by conceptual differences between our empirically-derived probability maps and the COE maps, but we also recommend using higher-resolution maps of PV potential and COE computations such as used in IAMs

Global Maps of Agricultural Expansion Potential at a 300 m Resolution

The global expansion of agricultural land is a leading driver of climate change and biodiversity loss. However, the spatial resolution of current global land change models is relatively coarse, which limits environmental impact assessments. To address this issue, we developed global maps representing the potential for conversion into agricultural land at a resolution of 10 arc-seconds (approximately 300 m at the equator). We created the maps using artificial neural network (ANN) models relating locations of recent past conversions (2007–2020) into one of three cropland categories (cropland only, mosaics with >50% crops, and mosaics with <50% crops) to various predictor variables reflecting topography, climate, soil, and accessibility. Cross-validation of the models indicated good performance with area under the curve (AUC) values of 0.88–0.93. Hindcasting of the models from 1992 to 2006 revealed a similar high performance (AUC of 0.83–0.91), indicating that our maps provide representative estimates of current agricultural conversion potential provided that the drivers underlying agricultural expansion patterns remain the same. Our maps can be used to downscale projections of global land change models to more fine-grained patterns of future agricultural expansion, which is an asset for global environmental assessments