| Literature DB >> 26546209 |
João Carvalho1,2, José E Granados3, Jorge R López-Olvera4, Francisco Javier Cano-Manuel5, Jesús M Pérez6, Paulino Fandos7, Ramón C Soriguer8, Roser Velarde9, Carlos Fonseca10, Arian Ráez11,12, José Espinosa13, Nathalie Pettorelli14, Emmanuel Serrano15,16.
Abstract
BACKGROUND: Both parasitic load and resource availability can impact individual fitness, yet little is known about the interplay between these parameters in shaping body condition, a key determinant of fitness in wild mammals inhabiting seasonal environments.Entities:
Mesh:
Year: 2015 PMID: 26546209 PMCID: PMC4636837 DOI: 10.1186/s13071-015-1188-4
Source DB: PubMed Journal: Parasit Vectors ISSN: 1756-3305 Impact factor: 3.876
Fig. 1Location of the study area, the Sierra Nevada Natural Space. The spatial distribution of shot-harvested animals and the degree of mange severity (healthy, mildly and severely infested) are also showed
Fig. 2Spatial variability of NDVI during the (a) green (March – October) and (b) dormant (November – February) periods in SNNS. Pixel values in each map correspond to the pixel average for the relevant season for the period 2000–2008
Fig. 3Intrannual variations of NDVI (a), snow cover (b) and number of ibexes observed (c) in SNNS. The error bars represent the inter-annual (1995–2008) fluctuations of variables values
R-squared and Stone-Geyser’s Q test values for the partial least squares regression (PLSR) analysis. Each model results from the combination between the two time-periods of contrasted vegetation productivity, and mange severity categories. A component is considered significant if Q ≥ 0.0975
| Period | Severity |
|
|
|---|---|---|---|
| Green | Healthy | 25.14 | 0.14 |
| Mildly infested | 3.37 | 0.01 | |
| Severely infested | 0.2 | −0.02 | |
| Dormant | Healthy | 16.86 | 0.11 |
| Mildly infested | 8.43 | 0.06 | |
| Severely infested | 0.01 | −0.02 |
Predictor weights and loads for the first component of partial least squares regression (PLSR) analysis. The contribution of each environmental predictor to the PLSR’s axis X is represented by the predictor weights
| Period | Severity | Predictors | Loads | Weights |
|---|---|---|---|---|
| Green | Healthy | NDVI | 0.68 | 0.62 |
| Snow | −0.71 | −0.77 | ||
| Abundance | −0.35 | −0.04 | ||
| Mildly infested | NDVI | −0.66 | −0.66 | |
| Snow | 0.55 | 0.25 | ||
| Abundance | 0.60 | 0.70 | ||
| Severely infested | NDVI | 0.67 | 0.59 | |
| Snow | −0.65 | 0.75 | ||
| Abundance | −0.38 | 0.38 | ||
| Dormant | Healthy | NDVI | 0.59 | 0.55 |
| Snow | −0.52 | −0.62 | ||
| Abundance | −0.62 | −0.57 | ||
| Mildly infested | NDVI | −0.39 | −0.29 | |
| Snow | 0.91 | 0.96 | ||
| Abundance | 0.66 | 0.02 | ||
| Severely infested | NDVI | −0.62 | −0.61 | |
| Snow | 0.42 | 0.36 | ||
| Abundance | 0.67 | 0.70 |
Fig. 4Relation between body condition (males and females) and the three environmental predictors in healthy, mildly and severely infested animals across two time periods of contrasted vegetation productivity (green and dormant)
Fig. 5Correlation of the environmental predictors and the response with the first two components. Each segment represents a variable. Longer segments, i.e. closer to the perimeter of the circle, indicate that the corresponding variable is better represented. Segments close to each other represent highly and positively correlated variables. On the other hand, segments in opposite extremes indicate negative correlation. Orthogonal segments mean no correlation among predictors