Sex differences in nest defence by the red-backed shrike<Emphasis Type="Italic"> Lanius collurio</Emphasis>: effects of offspring age,brood size,and stage of breeding season

The red-backed shrike Lanius collurio is an open-cup nesting passerine bird, which protects its nest aggressively attacking predators near the nest. The response of parents to a human observer was investigated during the nesting period 1999–2001 in Poland. The intensity of nest defence increased as the breeding cycle progressed in accordance to the offspring value hypothesis. However, we did not find an increase in the level of aggression according to the number of offspring and the time of season. Contrary to previous predictions, we did not find gender differences in nest defence. More aggressive parents, both females and males, have significantly better breeding success than quieter individuals.     

Phylogeography of the fiscal shrike (Lanius collaris): a novel pattern of genetic structure across the arid zones and savannas of Africa

Aim Savanna occupies a substantial part of Africa, being distributed around the two major tropical rain forest blocks in what is referred to as the Savanna Belt. Our current understanding of the genetic structure within species distributed across the Savanna Belt is primarily derived from mammalian taxa, studies of which have revealed a suture zone or transition between northern and east/southern Africa clades in south‐western Kenya and north‐western Tanzania. We conduct a phylogeographic study of the fiscal shrike (Lanius collaris), a polytypic species distributed across the Savanna Belt of Africa and for which morphological and vocal data are in agreement with the suture zone recovered for mammalian taxa, to test the hypothesis of a spatially congruent genetic break across several taxa, including birds. Location Africa, south of the Sahara. Methods We analysed DNA sequences recovered from four loci (one mitochondrial, two autosomal and one Z‐linked) in 66 individuals, representing all recognized subspecies, as well as putatively closely related species. We make use of a combination of tree‐building and population genetic methods to investigate the phylogeographic structure of the fiscal shrike across Africa. Results The fiscal shrike consists of two primary lineages with a strong geographic component: a northern group distributed from southern Tanzania to Senegal, and a southern group distributed from Botswana/Zambia to South Africa with isolated populations in Tanzania and northern Malawi. Unexpectedly, Souza’s shrike (L. souzae) was nested within L. collaris, as the sister group of the southern group. The positions of Mackinnon’s shrike (L. mackinnoni) and that of the São Tomé shrike (L. newtoni) were variable, being either nested within the fiscal shrike or sister to the L. collaris–L. souzae clade. Our divergence time analyses suggest that the Lanius collaris species complex started to diversify around 2.2 Ma. Main conclusions Our study reveals a distinct biogeographic pattern for a savanna distributed species in Africa, with the transition between the two primary genetic lineages occurring at a latitude of c. 15–16° S, 10° S further south than shown elsewhere for several mammalian species.     

The contributions of topoclimate and land cover to species distributions and abundance: fine‐resolution tests for a mountain butterfly fauna

Aim Models relating species distributions to climate or habitat are widely used to predict the effects of global change on biodiversity. Most such approaches assume that climate governs coarse‐scale species ranges, whereas habitat limits fine‐scale distributions. We tested the influence of topoclimate and land cover on butterfly distributions and abundance in a mountain range, where climate may vary as markedly at a fine scale as land cover. Location Sierra de Guadarrama (Spain, southern Europe) Methods We sampled the butterfly fauna of 180 locations (89 in 2004, 91 in 2005) in a 10,800 km² region, and derived generalized linear models (GLMs) for species occurrence and abundance based on topoclimatic (elevation and insolation) or habitat (land cover, geology and hydrology) variables sampled at 100‐m resolution using GIS. Models for each year were tested against independent data from the alternate year, using the area under the receiver operating characteristic curve (AUC) (distribution) or Spearman's rank correlation coefficient (r_s) (abundance). Results In independent model tests, 74% of occurrence models achieved AUCs of > 0.7, and 85% of abundance models were significantly related to observed abundance. Topoclimatic models outperformed models based purely on land cover in 72% of occurrence models and 66% of abundance models. Including both types of variables often explained most variation in model calibration, but did not significantly improve model cross‐validation relative to topoclimatic models. Hierarchical partitioning analysis confirmed the overriding effect of topoclimatic factors on species distributions, with the exception of several species for which the importance of land cover was confirmed. Main conclusions Topoclimatic factors may dominate fine‐resolution species distributions in mountain ranges where climate conditions vary markedly over short distances and large areas of natural habitat remain. Climate change is likely to be a key driver of species distributions in such systems and could have important effects on biodiversity. However, continued habitat protection may be vital to facilitate range shifts in response to climate change.     

Population trends and spatial synchrony in peripheral populations of the endangered Lesser grey shrike in response to environmental change

Regional synchronization in species dynamics as well as particular ecological and demographic characteristics of peripheral populations poses special challenges for conservation purposes, particularly under the current scenario of global climate change. Here, we study the population trend and spatial synchrony of several peripheral populations of the endangered Lesser grey shrike Lanius minor at the western limit of its breeding range (southern France and northeast Spain). In an attempt to ascertain the effect of environmental change on the decline of the species we also look for evidence of climate changes in the breeding and wintering area of this shrike and related effects on vegetation by using the normalized difference vegetation index (NDVI). We found that the interannual fluctuations of the peripheral populations in France and Spain are strongly correlated, therefore suggesting that their decline can be under the influence of a common factor. We obtained clear evidence of climatic change (an increased thermal oscillation) in one peripheral population that could have resulted in a decrease of the NDVI index in the area. Our study finds correlational evidence that climatic variables in the breeding area may account for fluctuations in abundances of some populations and that environmental conditions experimented by some population could influence the fate of the neighboring populations. Our results indicate that the studied peripheral populations are spatially synchronized, so that conservation efforts should be applied at a large-scale encompassing all the isolated populations at the western border of the range of the species in the Mediterranean area.     

Heat-shock and seed germination of a group of Mediterranean plant species growing in a burned area: An approach based on plant functional types

Many plants from Mediterranean-type ecosystems show enhanced germination when exposed to heat and other fire-related cues. Whether Mediterranean-type plants are fire recruiters and need fire to germinate is subject of discussion. In the present work, we tested the above hypothesis by subjecting seeds from 57 species representative of a recently burned plant community to various heat pulses. Differences in germination among species, taking into account their phylogeny, were studied by dividing them according to their life-form (chamaephytes, hemicryptophytes), regeneration strategy (non-sprouters, sprouters) and geographical distribution range (Iberian Peninsula endemics, Mediterranean, widely distributed species). Seeds were exposed to 80, 100 and 120 °C during 10 min, and then, incubated at 17.5 °C for 6 weeks in darkness. Maximum germination was reached at 80 °C and control treatments and minimum germination was at 120 °C. Most species were tolerant to heat-shocks, only a few of them were stimulated by heat, and around 20% suffered a reduction in germination with heat. The germination response to heat-shock differed according to regenerative strategy and distribution range, but not to life-form. These results were supported independently of phylogeny. As expected, sprouters and Iberian endemics were more sensitive to heat-shock than non-sprouters and widely distributed species, respectively. As a conclusion, the studied plant group appears to exhibit resistance to heat but not dependence on it for germination. Therefore, recruitment could be high after low intensity fires, but might be significantly reduced for most species after more intense fires.     

Modelling of the effects of environmental factors on rice grain discoloration incidence in Corrientes province,Argentina

Rice grain discoloration (RGD) is a disease of complex aetiology for which there are no resistant varieties. Due to the need to better define the environmental conditions that favour the disease, the aims of this work were to (i) identify the predominant fungi associated, (ii) determine the meteorological variables most closely related, and (iii) develop preliminary weather-based models to predict binary levels of RGD incidence. After analysing 123 rice grain samples under natural infection conditions from rice-cropping regions throughout Corrientes province, Argentina, we found that RGD was mainly associated with Alternaria padwickii (14.2%) and Microdochium albescens (13.7%). The strongest associations between weather variables and RGD incidence were observed in a susceptible critical period (Scp) that extended from the rice flowering stage until 870 accumulated degree days (Scp lasting 32 days, ±7 days). The binary response logistic model including the weather variables DPrecT (which combined the effect of the simultaneous daily occurrence of precipitation lower than 12 mm and air temperature between 13 and 28°C), and DDMnT (sum of the exceeding amounts of daily min temperature from 23°C), was the most appropriate, showing prediction accuracy (PA) values of 84.6%. The univariate model that included DPrecT presented a PA of 82.1%. The logistic regression techniques here used to develop weather-based models to estimate the probabilities of occurrence of binary levels of RGD can not only help to clarify and quantify the environmental effect on the development of RGD but also be useful tools to be included in future management strategies.     

Predicting species richness and distribution ranges of centipedes at the northern edge of Europe

In recent decades, interest in understanding species distributions and exploring processes that shape species diversity has increased, leading to the development of advanced methods for the exploitation of occurrence data for analytical and ecological purposes. Here, with the use of georeferenced centipede data, we explore the importance and contribution of bioclimatic variables and land cover, and predict distribution ranges and potential hotspots in Norway. We used a maximum entropy analysis (Maxent) to model species' distributions, aiming at exploring centres of distribution, latitudinal spans and northern range boundaries of centipedes in Norway. The performance of all Maxent models was better than random with average test area under the curve (AUC) values above 0.893 and True Skill Statistic (TSS) values above 0.593. Our results showed a highly significant latitudinal gradient of increased species richness in southern grid-cells. Mean temperatures of warmest and coldest quarters explained much of the potential distribution of species. Predictive modelling analyses revealed that south-eastern Norway and the Atlantic coast in the west (inclusive of the major fjord system of Sognefjord), are local biodiversity hotspots with regard to high predictive species co-occurrence. We conclude that our predicted northward shifts of centipedes' distributions in Norway are likely a result of post-glacial recolonization patterns, species' ecological requirements and dispersal abilities.     

Geographic disparities of breast cancer incidence in Portugal at the district level: A spatial age-period-cohort analysis, 1998-2011

BackgroundBreast cancer is the most common malignancy in women world-wide and the most common cause of cancer deaths, which can often be managed with early diagnosis and subsequent treatment. Here, we focus on geographic disparities in incidence within Portugal for three age groups of women (30−49; 50−69; 70−84 years).MethodsAge-period-cohort (APC) models are widely used in cancer surveillance, and these models have recently been extended to allow spatially-varying effects. We apply novel spatial APC models to estimate relative risk and age-adjusted temporal trends at the district level for the 20 districts in Portugal. Our model allows us to report on country-wide trends, but also to investigate geographic disparities between districts and trends within districts.ResultsAge-adjusted breast cancer incidence was increasing over 1998–2011 for all three age groups and in every district in Portugal. However, we detect spatially-structured between-district heterogeneity in relative risk and age-adjusted trends (Net Drifts) for each of the three age groups, which is most pronounced in the highly-screened (50−69yo) and late-onset (70−84yo) groups of women.ConclusionsWe present evidence of disparities in breast cancer incidence at a more granular geographic level than previously reported. Some disparities may be due to latent risk factors, which cannot be accounted for by age, birth year, and geographic location alone.ImpactOur study motivates resuming data collection for breast cancer incidence at the district level in Portugal, as well as the study of exogenous risk factors.     

Modelling the distribution of badgers Meles meles: comparing predictions from field-based and remotely derived habitat data

• 1 Environmental heterogeneity is important in determining the distribution and abundance of organisms at various spatial scales. The ability to understand and predict distribution patterns is important for solving many management problems in conservation biology and wildlife epidemiology.
• 2 The badger Meles meles is a highly adaptable, medium‐sized carnivore, distributed throughout temperate Eurasia, which shows a wide diversity of social and spatial organization. Within Britain, badgers are not only legally protected, but they also serve as a wildlife host for bovine tuberculosis Mycobacterium bovis. An evaluation of the role of badgers in the dynamics of this infection depends on understanding the responses of badgers to the environment at different spatial scales.
• 3 The use of digital data to provide information on habitats for distribution models is becoming common. Digital data are increasingly accessible and are generally cheaper than field surveys. There has been little research, however, to compare the accuracy of models based on field‐derived and remotely derived data.
• 4 In this paper, we make quantified comparisons between large‐scale presence/absence models for badgers in Britain, based on field‐surveyed habitat data and remotely derived digital data, comprising elevation, geology and soil.
• 5 We developed four models: 1980s badger survey data using field‐based and digital data, and 1990s badger survey data using field‐based and digital data. We divided each of the four datasets into two subsets and used one subset for training (developing) the model and the other for testing it.
• 6 All four training models had classification accuracies in excess of 69%. The models generated from digital data were slightly more accurate than those generated from field‐derived habitat data.
• 7 The high classificatory ability of the digital‐based models suggests that the use of digital data may overcome many of the problems associated with field data in wildlife‐habitat modelling, such as cost and restricted geographical coverage, without any significant impact on model performance for some species. The more widespread use of digital data in wildlife‐habitat models should enhance their accuracy, repeatability and applicability and make them better‐suited as tools to aid policy‐ and decision‐making processes.

     

Energy–water and seasonal variations in climate underlie the spatial distribution patterns of gymnosperm species richness in China

Studying the pattern of species richness is crucial in understanding the diversity and distribution of organisms in the earth. Climate and human influences are the major driving factors that directly influence the large‐scale distributions of plant species, including gymnosperms. Understanding how gymnosperms respond to climate, topography, and human‐induced changes is useful in predicting the impacts of global change. Here, we attempt to evaluate how climatic and human‐induced processes could affect the spatial richness patterns of gymnosperms in China. Initially, we divided a map of the country into grid cells of 50 × 50 km² spatial resolution and plotted the geographical coordinate distribution occurrence of 236 native gymnosperm taxa. The gymnosperm taxa were separated into three response variables: (a) all species, (b) endemic species, and (c) nonendemic species, based on their distribution. The species richness patterns of these response variables to four predictor sets were also evaluated: (a) energy–water, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human influences. We performed generalized linear models (GLMs) and variation partitioning analyses to determine the effect of predictors on spatial richness patterns. The results showed that the distribution pattern of species richness was highest in the southwestern mountainous area and Taiwan in China. We found a significant relationship between the predictor variable set and species richness pattern. Further, our findings provide evidence that climatic seasonality is the most important factor in explaining distinct fractions of variations in the species richness patterns of all studied response variables. Moreover, it was found that energy–water was the best predictor set to determine the richness pattern of all species and endemic species, while habitat heterogeneity has a better influence on nonendemic species. Therefore, we conclude that with the current climate fluctuations as a result of climate change and increasing human activities, gymnosperms might face a high risk of extinction.     

The influence of environmental factors on the spatial distribution of saxicolous lichens in a Norwegian coastal community

Abstract. The effects of vegetation cover, radiation, micro‐habitat variables and maritime influence on the floristic composition of a saxicolous community in Vingen, western Norway were studied. Particular emphasis is put on the local distribution of Fuscidea cyathoides, Ochrolechia tartarea, Ophioparma ventosa and Pertusaria corallina. Very little of the variation in the lichen community composition is directly related to measured micro‐environmental variables but variance partitioning shows that vegetation cover explains more of the floristic variation than radiation, maritime influence and microhabitat variables. Logistic regression analyses nevertheless indicate that the micro‐environment influences the spatial distribution of the four species. The high fraction of unexplained floristic variation, 91%, is suggested to result from (1) lack of fit of data to the response model; (2) some influential environmental variables that have not been recorded; (3) local historical factors that affect present day distribution and/or (4) apparent randomness in colonization. The results also agree with the view that the four lichen species in this study are able to co‐exist in the long‐term because of different spatial distributions resulting from different strategies with respect to ecology, dispersion and interaction.     

Past distribution and ecology of the cork oak (Quercus suber) in the Iberian Peninsula: a pollen-analytical approach

Abstract.  This study presents pollen-analytical data from continental and offshore Iberian Peninsula sites that include pollen curves of Quercus suber , to provide information on the past distribution and ecology of the cork oak ( Q. suber ). Results centre on a new pollen record of Navarrés (Valencia, eastern Spain), which shows that the cork oak survived regionally during the Upper Pleistocene and was important during a mid-Holocene replacement of a local pine forest by Quercus -dominated communities. This phenomenon appears linked to the recurrence of fire and reinforces the value of the cork oak for reforestation programmes in fire-prone areas. In addition to Navarrés, other Late Quaternary pollen sequences (Sobrestany, Casablanca-Almenara, Padul, SU 8103, SU8113, 8057B) suggest last glacial survival of the cork oak in southern and coastal areas of the Peninsula and North Africa. Important developments also occur from the Late Glacial to the middle Holocene, not only in the west but also in the eastern Peninsula. It is suggested that, in the absence of human influence, Q. suber would develop in non-monospecific forests, sharing the arboreal stratum both with other sclerophyllous and deciduous Quercus and Pinus species.     

Multivariate analysis of a fine-scale breeding bird atlas using a geographical information system and partial canonical correspondence analysis: environmental and spatial effects

Aim To assess the relative roles of environment and space in driving bird species distribution and to identify relevant drivers of bird assemblage composition, in the case of a fine‐scale bird atlas data set. Location The study was carried out in southern Belgium using grid cells of 1 × 1 km, based on the distribution maps of the Oiseaux nicheurs de Famenne: Atlas de Lesse et Lomme which contains abundance for 103 bird species. Methods Species found in < 10% or > 90% of the atlas cells were omitted from the bird data set for the analysis. Each cell was characterized by 59 landscape metrics, quantifying its composition and spatial patterns, using a Geographical Information System. Partial canonical correspondence analysis was used to partition the variance of bird species matrix into independent components: (a) ‘pure’ environmental variation, (b) spatially‐structured environmental variation, (c) ‘pure’ spatial variation and (d) unexplained, non‐spatial variation. Results The variance partitioning method shows that the selected landscape metrics explain 27.5% of the variation, whilst ‘pure’ spatial and spatially‐structured environmental variables explain only a weak percentage of the variation in the bird species matrix (2.5% and 4%, respectively). Avian community composition is primarily related to the degree of urbanization and the amount and composition of forested and open areas. These variables explain more than half of the variation for three species and over one‐third of the variation for 12 species. Main conclusions The results seem to indicate that the majority of explained variation in species assemblages is attributable to local environmental factors. At such a fine spatial resolution, however, the method does not seem to be appropriated for detecting and extracting the spatial variation of assemblages. Consequently, the large amount of unexplained variation is probably because of missing spatial structures and ‘noise’ in species abundance data. Furthermore, it is possible that other relevant environmental factors, that were not taken into account in this study and which may operate at different spatial scales, can drive bird assemblage structure. As a large proportion of ecological variation can be shared by environment and space, the applied partitioning method was found to be useful when analysing multispecific atlas data, but it needs improvement to factor out all‐scale spatial components of this variation (the source of ‘false correlation’) and to bring out the ‘pure’ environmental variation for ecological interpretation.     

Geographical patterns of morphological variation and environmental correlates in contact zones: a multi-scale approach using two Mediterranean vipers (Serpentes)

Adaptation to similar selective pressures can explain morphological convergence between closely related species in contact zones. Geostatistics and Geographical Information System were used to identify multi-scale patterns of morphological variability and test the hypothesis of morphological convergence due to local environmental pressures in the contact areas between Vipera aspis and Vipera latastei in the Iberian Peninsula. Nine morphological traits from 630 and 362 vipers at regional and local scale, respectively, were interpolated by Kriging to generate surfaces of morphological variation. Kriging is a geostatistical algorithm that allows investigating the spatial structure of data with statistical models. At both scales, a convergent north–south pattern in morphological variability was observed and the contact areas were identified as integration zones where intermediate vipers are found. Significant correlations were found between surfaces of univariate and multivariate traits, with precipitation and temperature seasonality. Thus, several morphological traits were apparently under local environmental selection. Nevertheless, the influence of biotic pressures and gene flow on morphological convergence of vipers in contact zones deserves further study.     

Habitat-based statistical models for predicting the spatial distribution of butterflies and day-flying moths in a fragmented landscape

1.  Most species' surveys and biodiversity inventories are limited by time and money. Therefore, it would be extremely useful to develop predictive models of animal distributions based on habitat, and to use these models to estimate species' densities and range sizes in poorly sampled regions.
2.  In this study, two sets of data were collected. The first set consisted of over 2000 butterfly transect counts, which were used to determine the relative density of each species in 16 major habitat types in a 35-km² area of fragmented landscape in north-west Wales. For the second set of data, the area was divided into 140 cells using a 500-m grid, and the extent of each habitat and the presence or absence of each butterfly and moth species was determined for each cell.
3.  Logistic regression was used to model the relationship between species' distribution and predicted density, based on habitat extent, in each grid square. The resultant models were used to predict butterfly distributions and occupancy at a range of spatial scales.
4.  Using a jack-knife procedure, our models successfully reclassified the presence or absence of species in a high percentage of grid squares (mean 83% agreement). There were highly significant relationships between the modelled probability of species occurring at regional and local scales and the number of grid squares occupied at those scales.
5.  We conclude that basic habitat data can be used to predict insect distributions and relative densities reasonably well within a fragmented landscape. It remains to be seen how accurate these predictions will be over a wider area.