264 research outputs found
Species-people correlations and the need to account for survey effort in biodiversity analyses
Aim Positive regional correlations between biodiversity and human population
have been detected for several taxonomic groups and geographical regions.
Such correlations could have important conservation implications and have
been mainly attributed to ecological factors, with little testing for an artefactual
explanation: more populated regions may show higher biodiversity because they
are more thoroughly surveyed. We tested the hypothesis that the correlation
between people and herptile diversity in Europe is influenced by survey effor
Positive regional species-people correlations: A sampling artefact or a key issue for sustainable development?
Many studies are documenting positive large-scale species–
people correlations (Luck, 2007; Schuldt & Assmann, 2010).
The issue is scale dependent: the local association of species
richness and people is in many cases a negative one (Pautasso,
2007; Pecher et al., 2010). This biogeographical
pattern is thus important for conservation. If species-rich
regions are also densely populated, preserving biodiversity
becomes more difficult, ceteris paribus, than if species-rich
regions were sparsely populated. At the same time, positive,
regional species–people correlations are an opportunity for
the biodiversity education of the majority of the human
population and underline the importance of conservation in
human-modified landscapes (e.g. Sheil & Meijaard, 2010;
Ward, 2010)
Is the human population a large-scale indicator of the species richness of ground beetles?
Aim Positive regional correlations between biodiversity and human population
have been detected for several taxonomic groups and geographical regions.
Such correlations could have important conservation implications and have
been mainly attributed to ecological factors, with little testing for an artefactual
explanation: more populated regions may show higher biodiversity because they
are more thoroughly surveyed. We tested the hypothesis that the correlation
between people and herptile diversity in Europe is influenced by survey effor
The 'rotiferologist' effect and other global correlates of species richness in monogonont rotifers
Global biodiversity patterns are often driven by diff erent environmental variables at diff erent scales. However, it is still controversial
whether there are general trends, whether similar processes are responsible for similar patterns, and/or whether
confounding eff ects such as sampling bias can produce misleading results. Our aim is twofold: 1) assessing the global
correlates of diversity in a group of microscopic animals little analysed so far, and 2) inferring the infl uence of sampling
intensity on biodiversity analyses. As a case study, we choose rotifers, because of their high potential for dispersal across
the globe. We assembled and analysed a new worldwide dataset of records of monogonont rotifers, a group of microscopic
aquatic animals, from 1960 to 1992. Using spatially explicit models, we assessed whether the diversity patterns conformed
to those commonly obtained for larger organisms, and whether they still held true after controlling for sampling intensity,
variations in area, and spatial structure in the data. Our results are in part analogous to those commonly obtained for
macroorganisms (habitat heterogeneity and precipitation emerge as the main global correlates), but show some divergence
(potential absence of a latitudinal gradient and of a large-scale correlation with human population). Moreover, the eff ect
of sampling eff ort is remarkable, accounting for 50% of the variability; this strong eff ect may mask other patterns such
as latitudinal gradients. Our study points out that sampling bias should be carefully considered when drawing conclusions
from large-scale analyses, and calls for further faunistic work on microorganisms in all regions of the world to better
understand the generality of the processes driving global patterns in biodiversity
Discrimination capacity in species distribution models depends on the representativeness of the environmental domain
[Aim]: When faced with dichotomous events, such as the presence or absence of a species, discrimination capacity (the ability to separate the instances of presence from the instances of absence) is usually the only characteristic that is assessed in the evaluation of the performance of predictive models. Although neglected, calibration or reliability (how well the estimated probability of presence represents the observed proportion of presences) is another aspect of the performance of predictive models that provides important information. In this study, we explore how changes in the distribution of the probability of presence make discrimination capacity a context-dependent characteristic of models. For the first time, we explain the implications that ignoring the context dependence of discrimination can have in the interpretation of species distribution models. [Innovation]: In this paper we corroborate that, under a uniform distribution of the estimated probability of presence, a well-calibrated model will not attain high discrimination power and the value of the area under the curve will be 0.83. Under non-uniform distributions of the probability of presence, simulations show that a well-calibrated model can attain a broad range of discrimination values. These results illustrate that discrimination is a context-dependent property, i.e. it gives information about the performance of a certain algorithm in a certain data population. [Main conclusions]: In species distribution modelling, the discrimination capacity of a model is only meaningful for a certain species in a given geographic area and temporal snapshot. This is because the representativeness of the environmental domain changes with the geographical and temporal context, which unavoidably entails changes in the distribution of the probability of presence. Comparative studies that intend to generalize their results only based on the discrimination capacity of models may not be broadly extrapolated. Assessment of calibration is especially recommended when the models are intended to be transferred in time or space.The study was partially supported by projects CGL2009-11316/BOS-FEDER and CGL2011-25544. A.J.-V. was supported by the MEC Juan de la Cierva Program. P.A. was supported by the Vicerrectorado de Investigación of the University of Málaga. A.M.B. was supported by a post-doctoral fellowship from Fundação para a Ciência e aTecnologia (Portugal), co-financed by the European Social Fund. The ‘Rui Nabeiro’ Biodiversity Chair receives funding from Delta Cafés.Peer Reviewe
Predictors of red fox (Vulpes vulpes) helminth parasite diversity in the provinces of Spain
We analysed the viscera of 321 red foxes collected over the last 30 years in 34
of the 47 provinces of peninsular Spain, and identified their helminth
parasites. We measured parasite diversity in each sampled province using four
diversity indices: Species richness, Marg a l e f’s species richness index,
Shannon’s species diversity index, and inverse Simpson’s index. In order to
find geographical, environmental, and/or human-related predictors of fox
parasite diversity, we recorded 45 variables related to topography, climate,
lithology, habitat heterogeneity, land use, spatial situation, human activity,
sampling effort, and fox presence probability (obtained after environmental
modelling of fox distribution). We then performed a stepwise linear regression
of each diversity index on these variables, to find a minimal subset of
statistically significant variables that account for the variation in each diversity
index. We found that most parasite diversity indices increase with the mean
distance to urban centres, or in other words, foxes in more rural provinces have
a more diverse helminth fauna. Sampling effort and fox presence probability
(probably related to fox density) also appeared as conditioning variables for
some indices, as well as soil permeability (related with water availability). We
then extrapolated the models to predict these fox parasite diversity indices in
non-sampled provinces and have a view of their geographical trends
Distribution modelling of wild rabbit hunting yields in its original area (S Iberian Peninsula)
In this work we used the information of the Annual Hunting Reports (AHRs) to obtain a high-resolution model of the
potential favourableness for wild rabbit harvesting in Andalusia (southern Spain), using environmental and land-use
variables as predictors. We analysed 32,134 AHRs from the period 1993/2001 reported by 6049 game estates to estimate
the average hunting yields of wild rabbit in each Andalusian municipality (n5771). We modelled the favourableness for
obtaining good hunting yields using stepwise logistic regression on a set of climatic, orographical, land use, and vegetation
variables. The favourability equation was used to create a downscaled image representing the favourableness of obtaining
good hunting yields for the wild rabbit in 161 km squares in Andalusia, using the Idrisi Image Calculator. The variables that
affected hunting yields of wild rabbit were altitude, dry wood crops (mainly olive groves, almond groves, and vineyards),
temperature, pasture, slope, and annual number of frost days. The 161 km squares with high favourableness values are
scattered throughout the territory, which seems to be caused mainly by the effect of vegetation. Finally, we obtained quality
categories for the territory by combining the probability values given by logistic regression with those of the environmental
favourability function
Conservation biogeography of ecologically interacting species: The case of the Iberian lynx and the European rabbit
Aim
To relate the recent Iberian lynx decline to changes in the distribution of the
European rabbit after the haemorrhagic disease outbreak of 1989. As Iberian rabbits
evolved in two geographically separated lineages, being the recent lynx range practically
restricted to the southwestern lineage, we also test if differential range dynamics
exists for these lineages, with the consequent implications for lynx conservation and
reintroduction planning
Cardiovascular dysfunction in obesity and new diagnostic imaging techniques: the role of noninvasive image methods
Obesity is a major public health problem affecting adults and children in both developed and developing countries. This condition often leads to metabolic syndrome, which increases the risk of cardiovascular disease. A large number of studies have been carried out to understand the pathogenesis of cardiovascular dysfunction in obese patients. Endothelial dysfunction plays a key role in the progression of atherosclerosis and the development of coronary artery disease, hypertension and congestive heart failure. Noninvasive methods in the field of cardiovascular imaging, such as measuring intima-media thickness, flow-mediated dilatation, tissue Doppler, and strain, and strain rate, constitute new tools for the early detection of cardiac and vascular dysfunction. These techniques will certainly enable a better evaluation of initial cardiovascular injury and allow the correct, timely management of obese patients. The present review summarizes the main aspects of cardiovascular dysfunction in obesity and discusses the application of recent noninvasive imaging methods for the early detection of cardiovascular alterations
Sampling effects on the identification of roadkill hotspots: Implications for survey design
Although locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the
accuracy of hotspot identification, using a dataset of vertebrate roadkills (n = 4427) recorded over a year of daily surveys along 37 km of roads. “True” hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of roadkills per segment. “Estimated” hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1e30 days). Overall,24.3% of segments were “true” hotspots, concentrating 40.4% of roadkills. For different groups, “true” hotspots accounted from 6.8% (bats) to 29.7% (small birds) of road segments, concentrating from 60% (lizards, lagomorphs, carnivores) of roadkills. Spatial congruence between
“true” and “estimated” hotspots declined rapidly with increasing time interval between surveys, due primarily to increasing false negatives (i.e., missing “true” hotspots). There were also false positives
(i.e., wrong “estimated” hotspots), particularly at low sampling frequencies. Spatial accuracy decay with increasing time interval between surveys was higher for smaller-bodied (amphibians, reptiles, small
birds, small mammals) than for larger-bodied species (birds of prey, hedgehogs, lagomorphs, carnivores).
Results suggest that widely used surveys at weekly or longer intervals may produce poor estimates of roadkill hotspots, particularly for small-bodied species. Surveying daily or at two-day intervals may be required to achieve high accuracy in hotspot identification for multiple species
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