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1 December 2015 Factors Affecting Red-Legged Partridge Alectoris rufa Abundance on Big-Game Hunting Estates: Implications for Management and Conservation
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Abstract

The red-legged partridge Alectoris rufa is not only the most important bird game species but also an important prey species for many predators in Iberia. However, its populations have significantly declined in recent decades, principally as the result of agricultural intensification on arable land. Its abundance has also undergone a significant decline in forested areas over the last few decades, where wild ungulate management and abundance have increased. In this scenario, we aimed to test the factors that affect red-legged partridge abundance in relation to high wild ungulate (wild boar and red deer) abundance in south-central Spain. The factors included as predictors were carnivore, wild boar and red deer abundances, vegetation features, nest predation rate and invertebrate availability. Red deer abundance showed a negative relationship with partridge abundance in spring (non-significant negative trends were also evident for carnivore and wild boar), whereas variables related to food availability (grass biomass, Hemipteran abundance and total invertebrate mass) had a positive effect in the same season. Moreover, deer and carnivore abundances and spring nest predation rate were negatively associated with partridge abundance in autumn. Plant biomass and Hemipteran abundance were negatively correlated with wild boar abundance, whereas maximum pasture height was negatively related to red deer and wild boar abundance. Overall, our results show that high ungulate densities may negatively affect partridge abundance, which may be mediated by (i) a reduction in food availability (invertebrate and herbaceous plant biomass) and (ii) nest predation by wild boar. This research has shown that current intensive big-game hunting management schemes in south-central Spain are often incompatible with red-legged partridge conservation, and that these effects should be taken into account when defining big-game management and conservation policies.

Introduction

The abundance and range of wild ungulates have increased throughout Europe and North America over the last century (Clutton-Brock and Albon, 1992; Côté et al., 2004; Gordon et al., 2004). This expansion has been facilitated by several factors, including the regulation of exploitation and the control of poaching (Gortázar et al., 2000), the abandoning of agricultural land in mountain and forest areas (Acevedo et al., 2006; Vargas et al., 2007), and the establishment of protected and conservation areas (Côté et al., 2004). However, the key factor is considered to have been anthropogenic expansion, which has primarily been carried out for hunting purposes (Gortázar et al., 2000; Acevedo and Cassinello, 2009).

In the Iberian Peninsula, and particularly in central and southern areas, there are high densities of red deer Cervus elaphus hispanicus and wild boar Sus scrofa on many hunting estates. Indeed, in areas with intensive game management aimed to boost biggame species, red deer can reach densities of over 50 individuals/km2 (Vicente et al., 2007; Acevedo et al., 2008), and wild boar densities can even attain 90 individuals/km2 (Acevedo et al., 2007; Bosch et al., 2012). However, despite the large increase in the densities of wild boar and deer, little is known about the ecological impacts of the overabundance of these species on Mediterranean ecosystems (but see Carpio et al. [2014a; 2014b; 2014c] for its impacts on other species; Gortázar et al. [2006] for diseaserelated constraints; Perea et al. [2014] for impacts on vegetation).

One species that could be sensitive to the abundance of wild ungulates is the red leggedpartridge Alectoris rufa, which has high socio-economic and ecological value as a game species and through its role as important prey for several species of predators in Iberia (Calderón, 1983). Despite the importance of the red-legged partridge in Spain and Portugal, its natural populations are estimated to have undergone a significant decline of over 50% between 1973–2002 (Blanco-Aguiar, 2007). Furthermore, recent results of the SACRE programme (SEO/BirdLife, 2014) show that the red-legged partridge is one of the ten species that have declined most severely in recent years (the abundance was 33% lower in 2013 with respect to that in 1998). However, despite the negative population trend, the red-legged partridge is currently listed as “least concern” worldwide (BirdLife International, 2012,  www.iucnredlist.org).

According to several studies, the most harmful factor for partridge distribution is habitat change resulting from agricultural intensification (Vargas et al., 2006; Blanco-Aguiar et al., 2007), which has had direct effects, such as the deterioration of suitable nesting sites (Newton et al., 2004), a reduction in food availability, an increase of predation risk owing to habitat simplification (Benton et al., 2003) and exposure to toxic biocides, for example through ingestion of dressed seeds (Mineau and Palmer, 2013; López-Antia et al., 2015). In addition, other factors such as overhunting and releases of farmed partridges have also been identified as harmful to wild partridges (Caro et al., 2014).

The factors affecting partridge populations in forest and mountain areas have received less attention than those acting in lowland and agricultural areas. In woodland and forest ecosystems from southern Spain (often devoted to big-game), one of the main factors that explains the decrease in partridge populations is the impoverishment of habitat quality as a consequence of land-use changes (Delibes-Mateos et al., 2012). Such changes include increases in large patches of dense homogeneous scrublands, pine reforestation characterised by a high tree density that prevents the growth of scrubland and pastureland, and the spread of oak-savannas (“dehesas”) that offer scarce scrub cover (refuge) as a consequence of intensive grazing pressure (Fernández-Alés et al., 1992). This has led to a loss of habitat heterogeneity, thus making many woodland and mountain areas unsuitable as partridge habitat (see Lucio, 1991).

Nonetheless, in these areas, one factor that may also affect partridge populations could be the high densities of wild ungulates: resulting in food competition, trampling or changes in habitat structure, and nest predation by wild boars (Carpio et al., 2014a). High densities of wild ungulates are known to affect the growth, reproduction and survival of plants, since they consume their stems, flowers, leaves and fruits, thus favouring species that are less frequently consumed (Côté et al., 2004; Mohr et al., 2005; Acevedo et al., 2008; Putman et al., 2011; Cuevas et al., 2012; Perea et al., 2014). Plant species, moreover, closely determine the insects and other invertebrates that are present and that are critical for partridge nestlings during their first weeks after hatching (Holland et al., 2006). Therefore, an intense disturbance in plant communities as a result of high ungulate densities may reduce their diversity and the species richness that is available for partridges (Stein et al., 2010). We consequently hypothesise that high abundances of wild ungulates could reduce partridge abundances as a consequence of a decrease in food availability (plants and insects), and nest predation by wild boar. To assess this, the factors that affect red-legged partridge abundance in relation to high wild ungulate (wild boar and red deer) abundances were tested on big-game estates in south-central Spain.

Material and methods

Study area

Data were collected on nine different hunting estates in southern Spain (fig. 1), averaging 2,470 hectares in extent (range 1,480–3,600 ha; table 1). The dominant vegetation includes tree species such as holm oak Quercus ilex and cork oak Quercus suber, together with pine plantations (Pinus pinea and Pinus pinaster) and scrubland dominated by species of Cistus, Erica, Pistacia, Phyllirea and Rosmarinus with scattered pastures. The study sites are mainly devoted to recreational hunting of wild boar and red deer. The red-legged partridge is not hunted in the study area and no management measures, such as releases or habitat improvement, are applied to enhance their populations.

Estimating ungulate and carnivore abundances

Deer population size was estimated at the hunting estate level, each estate being considered as a discrete management unit. Two spotlight counting events (two replicates on consecutive days) between September and October 2011 were used to estimate the deer population size on each estate. Transects (mean length = 20.3 km ± 2.34 S.E.) were driven at 10–15 km/h along dirt tracks covering the whole estate but excluding those tracks close to the estate boundary. The distance from the observer to the deer or to the centre of a deer group was measured with a Leica LRF 1200 Scan telemeter (Solms, Germany) (range 15–1100 m; precision ±1m/±0.1%), and compass bearings were taken to determine the angle between these and the transect line. Deer population densities (individuals per hectare) were estimated using Distance 5.0 software (Buckland et al., 2004). Half-normal, uniform and hazard rate models for the detection function were fitted against the data using cosine, hermite polynomial and simple polynomial adjustment terms, which were fitted sequentially. The selection of the best model and adjustment term was based on Akaike's Information Criterion (AIC).

Fig. 1.

Map of Córdoba Province showing the location of the sampling sites.

[Mapa de la provincia de Córdoba mostrando la localización de los puntos de muestreo].

f01_283.jpg

Table 1

Description of the nine study areas. Red deer density (red deer/ha), wild boar abundance (FBII: frequency based indirect index), carnivore abundance (KAI: droppings/km), carnivore abundance (Spotlight: carnivores/ km), spring and autumn partridge abundance (KAI: partridges/km), surface area (ha), scrubland, woodland and pasture (% of total surface area) and transect length for red deer census (Total km: census 1 + census 2).

[Descripción de las nueve áreas de estudio. Densidad de ciervos (ciervos/ha), abundancia de jabalí (FBII: índice de frecuencia), abundancia de carnívoros (IKA: excrementos/km), abundancia de perdiz en primavera y otoño (IKA: perdices/km), área (ha), matorral, arbolado y pastizal (% con respecto a la superficie total) y longitud de los transectos para los censos de ciervo (kilómetros totales: censo 1 + censo 2).]

t01_283.gif

Wild boar abundance was estimated following the methodology employed by Acevedo et al. (2007) based on dung frequency along a walked transect. According to this method, two 4-km transects per estate, located at least two kilometres apart, were performed in September and October 2011. Each transect comprised 40 segments 100 m in length and 1 m wide, divided into ten sectors of 10 m in length. Sign frequency was defined as the average number of 10 m sectors containing dung per 100-m transect (Carpio et al., 2014a), and a mean value of wild boar abundance was calculated per estate using the following formula:

e01_283.gif
where Si is the number of sign-positive sectors and n the total number of sampled sectors.

The number of carnivore scats per km in these transects was also recorded (similarly to Carpio et al., 2014a). Carnivore abundances were additionally estimated through the use of spotlight counts during July and August 2011 in order to obtain a kilometric abundance index (KAI). Two 20-km routes (two replicates on consecutive days) were spotlighted per estate, and any carnivores observed were noted. Those detected were the red fox Vulpes vulpes, stone marten Martes foina and common genet Genetta genetta.

Estimating red-legged partridge abundance

Red-legged partridge abundance was estimated during two seasons in 2011 (April and October), coinciding with the population minimum just before breeding and the population peak following juvenile recruitment respectively (Borralho et al., 1996; Gortázar et al., 2002). The transects on each estate, whose average length was 20.6 km ± 3.5 (± S.E.), were measured by driving at a speed of 10–15 km/h, and two replicates of each transect per estate and season were carried out, at no more than 3-day intervals. The transects were conducted by two people (one driver and one observer) during the first three hours after sunrise and in good weather conditions (Gortázar et al., 2002), and they covered optimal habitats for partridges (oak savannahs, pastures and sparse scrublands), avoiding dense pine forest and dense scrubland patches, in which detectability/visibility is poor. Simple counts were made and a kilometric abundance index (KAI) was calculated for each estate by dividing the number of observations by the total length of the transect (the low number of observations preventing using “Distance software” to estimate partridge densities).

Invertebrate sampling

Since invertebrates are important food resources for partridge chicks, two invertebrate surveys were conducted at random points 50–100 m from transects for estimating partridge abundance. The first took place in the last two weeks of March 2012 while the second was carried out in late April 2012. Five sampling points were established on each of the nine estates and two pitfall traps were placed at each one (90 pitfalls in total). The pitfall traps were buried at ground level and consisted of plastic receptacles with a capacity of 0.75 litres and an opening diameter of 12 cm (Paschetta et al., 2013). They were half-filled with a solution of salts (to preserve the specimens caught) and soap (to break the water surface tension). The trapped invertebrates were collected 14 days after the traps had been set (Allombert et al., 2005) and were preserved in 100 ml plastic containers with 70% alcohol. The invertebrates were subsequently identified to order level under a stereomicroscope, this degree of identification having figured in earlier studies of partridge diet (Holland et al., 2006). The diversity and structure of invertebrates larger than 0.02 mm (mesofauna and macrofauna) were studied and any microfauna (< 0.02 mm) were excluded. The invertebrate dry mass and taxon richness were calculated for each sampling point. In order to obtain the dry mass, pitfall trap contents were dehydrated in an oven at 80ºC for 24 hours before weighing on a precision scale (0.001 g). All index values were calculated from the average of the two pitfall traps in each pair of sampling periods. In addition, for each sampling point, the number of invertebrates belonging to the following groups was determined: a) Hemiptera (including Homoptera and Heteroptera), b) Coleoptera (both larvae and adults), c) Hymenoptera, d) Diptera, e) Collembola and f) class Arachnida (which includes subclass Acari, and the orders Scorpionida, Pseudoscorpionida, Opilionida, Solifugae and Araneae). These groups are considered to be the most important in the partridge diet (Holland et al., 2006).

Vegetation structure and plant sampling

Ten circular walking transects were conducted on each estate during May 2011 around the insect sampling points, using a 50 m cord to measure the distance. Shrub and pasture cover, along with maximum grass height, were measured on these transects, since these indexes have been considered as indirect measures of pasture availability for different herbivore species (Affleck et al., 2005). Finally, all individuals of the plant families identified as the most important in the partridge diet (Fabaceae, Poaceae and Asteraceae, according to Holland et al., 2006) within the transect were noted and the percentage cover of each family was calculated.

In addition, plant biomass (g) was assessed from cuttings in an area of 25 cm2 of herbaceous vegetation randomly selected around every transect. The vegetation sampled was dried to constant mass in a drying oven with hot air circulation at 60°C and weighed using an electric balance (precision: 0.01 g).

Nest predation

The nest predation rate by wild boar was obtained using data recorded by Carpio et al. (2014a) on the same hunting estates in 2012, using only nests located in areas accessible to wild boars (N = 45), i.e. five artificial nests per estate. In this experiment, nests were formed using four natural red-legged partridge eggs supplied by a game farm and two plaster eggs (N = 270). Egg predators were identified from tooth marks on the plaster eggs and by automatic cameras placed at 14 nests. All nests were checked for predation after 23 days and to discover the percentage of eggs depredated by different predators (for more details see Carpio et al., 2014a).

Statistical analysis

The variables red deer density, vegetation height, Collembola and Coleoptera, were log-transformed to fit the parameters of normality in accordance with the Kolmogorov-Smirnov test. A Principal Component Analysis was performed for carnivore abundance, which brought together the two carnivore abundance estimates (scats/km and KAI) into a single factor that explained 90.3% of the variance. The absence of spatial autocorrelation was checked by calculating the Moran's indices of each variable. The Partial Least Squares Regression (PLSR) technique was used to construct two initial general models and four specific models (see below). PLSR is a useful regression calibration technique when the number of predictor variables is similar to or higher than the number of observations, and/or the predictors are highly correlated (Carrascal et al., 2009). This modelling procedure was based on a linear transformation of the original descriptors into a small number of orthogonal factors (latent variables), and an attempt was made to maximise the covariance between the descriptors and the dependent variable. In the general models, the dependent variables were partridge abundances in spring and autumn respectively, and the independent variables were: red deer, wild boar and carnivore abundances; plant biomass, maximum pasture height, rate of nest predation, percentage cover of shrub and pasture land, invertebrate species richness and biomass, frequency of the most important invertebrate groups (Collembola, Coleoptera, Diptera, Hemiptera, Hymenoptera and Arachnida), and finally, percentage cover of the plant families that are most important to partridges (Fabaceae, Asteraceae and Poaceae). Final models were constructed using only the variables with the highest standardised regression coefficient obtained in the full models, which allowed the optimal of the regression coefficient (Q2) to be obtained, and both models were validated by following the full cross-validation technique.

In addition, four specific PLSRs were performed using as response variables those previously indentify as important predictors in the partridge abundance models (PLSR general models) that could be affected by high ungulate density (Hemiptera, invertebrate mass, vegetal biomass and maximum height of grass). In these specific models, red deer and wild boar abundances together with habitat related variables were included as independent ones. Statistical analyses were performed using Unscrambler 9.7 software.

Results

Red deer density ranged from 25 to 67 individuals per km2 (mean 39 ± 0.14 S.E.), and the abundance index for wild boar ranged from 0.04 to 0.47 (mean 0.26 ± 0.15 S.E.). The kilometric abundance index (KAI) for partridge ranged from 0.11 to 0.64 individuals/ km (mean 0.34 ± 0.15 S.E.) in spring and from 0 to 1.02 (mean 0.51 ± 0.27 S.E.) in autumn. 65% of the eggs were predated, and only 20% of nests were not totally or partially predated. The wild boar was the main predator and consumed 45.8% of predated eggs (for more details on predation rates see Carpio et al., 2014a). With regard to invertebrate sampling, 2,580 animals were identified, 2,047 of which were of the most important taxa in the partridge diet (fig. 2).

The general PLSR analysis for spring abundance resulted in a significant model (with two principal components) that explained 59% (R2X = 0.59) of the variance from the independent variables (R2XPC1 = 0.45 & R2XPC2 = 0.14) and 83% (R2Y = 0.83) of the variance of the dependent variable (R2YPC1 = 0.71 & R2YPC2 = 0.12). The PLS autumn abundance analysis resulted in another significant model (with only one principal component) that explained 37% (R2X = 0.37) of the variance from the independent variables and 60% (R2Y = 0.60) of the variance in the dependent variable. Table 2 shows the regression coefficients of the variables retained in the final models, which summarise the effect of each parameter on partridge abundance in the spring and autumn models. In the spring model, three parameters had a significant effect on partridge abundance: red deer abundance had a negative effect, whereas Hemiptera, invertebrate mass and vegetal biomass had a positive correlation. In the autumn model, deer density and carnivore abundance had a negative effect on partridge abundance, and only the percentage of unpredated eggs had a positive effect.

Fig. 2.

Mean number of individuals (±S.E.) per pitfall trap belonging to the most important invertebrate taxa in the partridge diet, according to Holland et al. (2006).

[Número medio de individuos (±S.E.) por trampa de caída pertenecientes a los taxones de invertebrados más importantes en la dieta de la perdiz según Holland et al. (2006)].

f02_283.jpg

Table 2

Regression coefficients of the variables retained in the final PLSR general models. *p < 0.05.

[Coeficientes de regresión de las variables importantes en los modelos PLSR generales. *p < 0,05].

t02_283.gif

Finally, the specific PLSR models (table 3), using as response variables those which affect red-legged partridge abundance (Hemiptera, vegetal biomass, invertebrate mass and maximum grass height), showed that the wild boar abundance index was negatively correlated with Hemiptera, vegetal biomass and grass height, whereas red deer abundance was only negatively correlated with grass height. The PLSR model using the invertebrate mass as a response variable was not significant (R2X = 0.5; R2Y = 0.11; Q2 = −0.041), and therefore those results are not given.

Discussion

This study has shown that red legged partridge abundance on big-game hunting estates in Southern Spain is (i) negatively associated with high red deer abundance, (ii) positively associated with variables indicative of higher food availability, some of which were affected by both wild boar and red deer, and (iii) negatively affected by nest predation. This highlights the fact that big and small game species are currently spatially segregated in southern Spain (Vargas et al., 2007; Delibes-Mateos et al., 2009), probably not only as a consequence of landuse changes and big game management leading to high abundances, but also through direct and indirect effects of wild ungulates on small game species. Therefore, the high population densities that ungulates reach in some woodland areas could be considered as an additional threat to partridge populations. Among other aspects, Caughley, 1981 (reviewed by Côté et al., 2004 in the case of red deer) proposed that animals are overabundant when they cause ecosystem dysfunction, including a loss of biodiversity. In the light of this consideration, our results suggest that the current ungulate densities attained on many hunting estates can be considered as cases of overabundance, since they can reduce the abundance of other species as a consequence of a reduction in food resources (invertebrate and vegetation) and an increase in nest predation rates (by wild boars), particularly in the case of groundnesting birds (Barrios-García and Ballari, 2012). What is more, this reduction in numbers of partridges and other birds may result in additional trophic cascade effects, thus affecting the prey resources of endangered predators (Lozano et al., 2007).

Table 3

Regression coefficients of the important variables retained in the PLSR specific models. *p < 0.05.

[Coeficientes de regresión de las variables importantes en los modelos PLSR específicos *p < 0,05].

t03_283.gif

Our results further show that partridge abundance was negatively correlated with red deer density in both seasons (fig. 3). These negative relationships could result from a decrease in food availability as a consequence of overgrazing and trampling in areas of high red deer densities. In fact, our results show that partridge abundance was positively related with vegetal biomass, which is a good estimator of pasture availability (Lazo et al., 1991). Although the maximum grass height did not show a significant effect, it was included in the best model showing a negative association with partridge abundance in spring, being in turn negatively affected by red deer density. Grass shortening may not only affect partridges as a result of food reduction but may also indirectly affect their vulnerability to predation (Hudson and Rands, 1988), since partridges (and their nests) are much more vulnerable in low herbaceous cover (Lucio, 1991).

Although wild boar abundance was not significantly correlated with partridge abundance, our results indicate that they may affect partridges by direct predation of nests (Carpio et al., 2014a), by a negative impact on invertebrates (Carpio et al., 2014c), and by reducing grass biomass and height. In the present study, wild boar abundance was negatively correlated with Hemiptera frequency (table 2), which showed a significant positive relationship with partridge abundance in spring, suggesting that wild boar overabundance could also decrease the availability of insects for partridges. Moreover, this negative effect on invertebrates could affect chick development, since invertebrates are the main protein source for young chicks and protein intake is essential for proper growth and the development of thermoregulatory mechanisms (Liukkonen-Anttila et al., 2002; Southwood and Cross, 2002). Wild boar abundance was also negatively correlated with grass biomass and height, which were previously identified as important predictors of red-legged partridge abundance in spring. This highlights the strong impact that boar rooting behaviour can have on grassland communities (Bueno et al., 2010).

Fig. 3.

Red-legged partridge abundance in spring (grey) and autumn (dark) as a function of red deer density.

[Abundancia de perdiz roja en primavera (gris) y otoño (negro) en función de la densidad de ciervo].

f03_283.jpg

Our results also show that partridge abundance in autumn was also negatively affected by egg predation in spring, wild boar being the main nest predators in the study area (Carpio et al., 2014a). This negative association in autumn suggests that juvenile recruitment and population growth (which takes place from late spring to autumn) may be strongly affected by nest predation, and the role of the wild boar as a nest predator can therefore be considered as an important harmful factor on hunting estates with high densities of this ungulate. Boar feeding behaviour may not only affect red-legged partridge populations but also those of other ground-dwelling birds (Barrios-García and Ballari, 2012). Indeed, Selva et al. (2014) have similarly recently shown that the proportion of depredated nests was higher in areas adjacent to ungulate feeding sites than at control sites, suggesting that game management should always consider potential indirect effects and the complex interactions that occur at ecosystem level.

Finally, it is also noteworthy that partridge abundance was negatively correlated with carnivore abundance in autumn. However, considering only this negative relationship may not be sufficient for understanding the possible effects of predation on partridges, and it is necessary to test the dietary and numerical responses of the carnivores to red-legged partridge abundance in order to elucidate predator-partridge relationships (Fernández de Simón, 2013).

Although this was a short study at a limited number of sites we consider that our results may be extrapolated to other hunting estates characterised by high densities of wild ungulates. The relationships between partridge abundance, food availability indicators and ungulate densities shown here may similarly be extrapolated to other areas of Spain in which there is an increase in the abundance of wild ungulates but it is necessary to confirm plausible effects of wild ungulates on partridges and other birds over a wider range of habitats and locations. This matter may be of major conservation concern in woodland areas in Southern Spain, in which several endangered predators persist and rabbits and red-legged partridges remain at low densities (Delibes-Mateos et al., 2009; Guerrero-Casado et al., 2013). In conclusion, this paper further shows that current big-game hunting management schemes in South Central Spain are often incompatible with the conservation of the main bird game species. The effects shown must therefore be considered as signs of ungulate overabundance and should be taken into account when deciding the most appropriate big-game management and conservation policies. Wild ungulate density should be therefore managed in order to make big-game hunting compatible with partridge conservation, although more studies are needed to determine the threshold value of ungulate abundance. An additional management option to promote partridge populations in areas of south-central Spain that are devoted to big game could be the establishment of ungulate exclusion areas, since nest predation rates are lower in the absence of wild boar (Carpio et al., 2014a); and pasture cover and height as well as invertebrate richness is higher within ungulate exclusion fences (Carpio et al., 2014c).

Acknowledgements.—

We should like to thank E. López, L. Ruiz-Aizpurua, Jesús Castro, Óscar, David and Macarena for their help in collecting field data. We are also grateful to the estate managers for their hospitality and assistance in the fieldwork, and to the Environmental Council of the Andalusian Autonomous Government for financing this work via a project to improve the habitat of the black vulture Aegypius monachus in Córdoba province, thanks to which we have been able to carry out this work.

Bibliography

1.

P. Acevedo , M. A. Escudero , R. Muñoz and C. Gortázar 2006. Factors affecting wild boar abundance across an environmental gradient in Spain. Acta Theriologica , 51: 327–336. Google Scholar

2.

P. Acevedo , J. Vicente , U. Hofle , J. Cassinello , F. Ruiz-Fons and C. Gortázar 2007. Estimation of European wild boar relative abundance and aggregation: a novel method in epidemiological risk assessment. Epidemiology & Infection , 135: 519–527. Google Scholar

3.

P. Acevedo , F. Ruiz-Fons , J. Vicente , A. R. Reyesgarcía , V. Alzaga and C. Gortázar 2008. Estimating red deer abundance in a wide range of management situations in Mediterranean habitats. Journal of Zoology , 276: 37–47. Google Scholar

4.

P. Acevedo and J. Cassinello 2009. Biology, ecology and status of iberian ibex Capra pyrenaica: A critical review and research prospectus. Mammal Review , 39: 17–32. Google Scholar

5.

D. L. Affleck , T. G. Gregoire , H. T. Valentine 2005. Design unbiased estimation in line intersect sampling using segmented transects. Environmental and Ecological Statistics , 12: 139–154. Google Scholar

6.

S. Allombert , S. Stockton and J. L. Martin 2005. A natural experiment on the impact of overabundant deer on forest invertebrates. Conservation Biology , 19: 1917–1929. Google Scholar

7.

T. G. Benton , J. A. Vickery and J. D. Wilson 2003. Farmland biodiversity: is habitat heterogeneity the key? Trends in Ecology & Evolution , 18: 182–188. Google Scholar

8.

M. N. Barrios-GarcÍA and S. A. Ballari 2012. Impact of wild boar (Sus scrofa) in its introduced and native range: a review. Biological Invasions , 14: 2283–2300. Google Scholar

9.

J. A. Blanco-Aguiar 2007. Variación espacial en la biología de la perdiz roja (Alectoris rufa): una aproximación multidisciplinar. Tesis doctoral, Universidad Complutense. Madrid. Google Scholar

10.

BIRDLIFE INTERNATIONAL. 2012. Species factsheet: Alectoris rufa [www document]. URL  http://www.birdlife.org/datazone/speciesfactsheet.php?id=144 (Accessed on 11/08/2015). Google Scholar

11.

R. Borralho , F. Rego and P. V. Pinto 1996. Is driven transect sampling suitable for estimating red-legged partridge Alectoris rufa densities? Wildlife Biology , 2: 259–268. Google Scholar

12.

J. Bosch , S. Peris , C. Fonseca , M. Martínez , A. De La Torre , I. Iglesias and M. J. Muñoz 2012. Distribution, abundance and density of the wild boar on the Iberian Peninsula, based on the CORINE program and hunting statistics. Folia Zoologica , 61: 138–151. Google Scholar

13.

S. T. Buckland , D. R. Anderson , K. P. Burnham , J. L. Laake , D. L. Borchers and L. Thomas 2004. Introduction to Distance Sampling: Estimating Abundance of Biological Population. Oxford University Press. Oxford. Google Scholar

14.

C. G. Bueno , I. C. Barrio , R. García-González , C. L. Alados and D. Gómez-García 2010. Does wild boar rooting affect livestock grazing areas in alpine grasslands? European Journal Wildlife Research , 56: 765–770. Google Scholar

15.

J. Calderón 1983. La perdiz roja, Alectoris rufa (L.). Aspectos morfológicos, taxonómicos y biológicos. Tesis doctoral, Universidad Complutense. Madrid. Google Scholar

16.

J. Caro , M. Delibes-Mateos , J. Vicente and B. Arroyo 2014. A quantitative assessment of the release of farm-reared red-legged partridges (Alectoris rufa) for shooting in central Spain. European Journal Wildlife Research , 60: 919–926. Google Scholar

17.

A. J. Carpio , J. Guerrero-Casado , F. S. Tortosa and J. Vicente 2014a. Predation of simulated red-legged partridge nests in big game estates from South Central Spain. European Journal Wildlife Research , 60: 391–394. Google Scholar

18.

A. J. Carpio , J. Guerrero-Casado , L. Ruizaizpurua , F. S. Tortosa and J. Vicente 2014b. Is high abundance of wild ungulates in a Mediterranean region compatible with the European rabbit? Wildlife Biology , 20: 161–166. Google Scholar

19.

A. J. Carpio , J. Castro-López , J. Guerrero-Casado , L. Ruiz-Aizpurua , J. Vicente and F. S. Tortosa 2014c. Effect of wild ungulate density on invertebrates in a Mediterranean ecosystem. Animal Biodiversity and Conservation , 37: 115–125. Google Scholar

20.

L. M. Carrascal , I. GalvÁN and O. Gordo 2009. Partial least squares regression as an alternative to current regression methods used in ecology. Oikos , 118: 681–690. Google Scholar

21.

G. Caughley 1981. Overpopulation. In, P. A. Jewell , S. Holt and D. Hart (Eds.): Problems in management of locally abundant wild mammals , pp. 7–19. Academic Press. New York. Google Scholar

22.

T. H. Clutton-Brock and S. D. Albon 1992. Trial and error in the Highlands. Nature , 358: 11–12. Google Scholar

23.

S. D. CÔTÉ , T. P. Rooney , J. P. Trembley , C. Dussault and D. M. Waller 2004. Ecological impacts of deer overabundance. Annual Review of Ecology, Evolution and Systematics , 35: 113–147. Google Scholar

24.

M. F. Cuevas , L. Mastrantonio , R. A. Ojeda and F. M. Jaksic 2012. Effects of wild boar disturbance on vegetation and soil properties in the Monte Desert, Argentina. Mammalian Biology , 77: 299–306. Google Scholar

25.

M. Delibes-Mateos , M. A. Farfán , J. Olivero , A. L. Márquez and J. M. Vargas 2009. Longterm changes in game species over a long period of transformation in the Iberian Mediterranean landscape. Environmental Management , 43: 1256–1268. Google Scholar

26.

M. Delibes-Mateos , M. A. Farfán , J. Olivero and J. M. Vargas 2012. Impact of land-use changes on red-legged partridge conservation in the Iberian Peninsula. Environmental Conservation , 39: 337–346. Google Scholar

27.

R. FernÁNdez-AlÉS , A. Martín , F. Ortega and E.E. Ales 1992. Recent changes in landscape structure and function in a Mediterranean region of SW Spain (1950–1984). Landscape Ecology 7: 3–18. Google Scholar

28.

J. Fernández De Simón 2013. Predation and the recovery of European rabbit populations in central-southern Iberian Peninsula. An assessment of the predator pit hypothesis. PhD Thesis, Universidad de Castilla-La Mancha. Google Scholar

29.

I. J. Gordon , A. J. Hester and M. Festa-Bianchet 2004. The management of wild large herbivores to meet economic, conservation and environmental objectives. Journal of Applied Ecology , 41: 1021–1031. Google Scholar

30.

C. Gortázar , J. Herrero , R. Villafuerte and J. Marco 2000. Historical examination of the status of large mammals in Aragon, Spain. Mammalia , 64: 411–422. Google Scholar

31.

C. GortÁZar , R. Villafuerte , M. A. Escudero and J. Marco 2002. Post-breeding densities of the red-legged partridge (Alectoris rufa) in agrosystems: A large-scale study in Aragon, northeastern Spain. Zeitschrift für Jagdwissenschaft , 48: 94–101. Google Scholar

32.

C. Gortázar , P. Acevedo , F. Ruiz-Fons and J. Vicente 2006. Disease risks and overabundance of game species. European Journal Wildlife Research , 52: 81–87. Google Scholar

33.

J. Guerrero-Casado , A. J. Carpio , L. Ruizaizpurua and F. S. Tortosa 2013. Restocking a keystone species in a biodiversity hotspot: recovering the European rabbit on a landscape scale. Journal of Nature Conservation, 21: 444–448. Google Scholar

34.

J. M. Holland , M. A. S. Hutchison , B. Smith and N. J. Aebischer 2006. A review of invertebrates and seed-bearing plants as food for farmland birds in Europe. Annals of Applied Biology , 148: 49–71. Google Scholar

35.

P. Hudson and M. Rands 1988. Ecology and management of gamebirds. BSP Professional Books. Oxford. Google Scholar

36.

A. Lazo , P. Fandos and R. C. Soriguer 1991. Inventario de la capacidad de carga de la Vera del Parque Nacional de Doñana. Unpublished report. CSIC-ICONA. Sevilla. Google Scholar

37.

I. Liukkonen-Anttila , A. Putaala and R. Hissa 2002. Feeding of hand-reared grey partridge Perdix perdix chicks - importance of invertebrates. Wildlife Biology , 8: 11–19. Google Scholar

38.

A. López-Antia , M. E. Ortiz-Santaliestra , E. G. D. Blas , P. R. Camarero , F. Mougeot and R. Mateo 2015. Adverse effects of thiram-treated seed ingestion on the reproductive performance and the offspring immune function of the red-legged partridge. Environmental Toxicology and Chemistry , 34: 1320–1329. Google Scholar

39.

J. Lozano , E. Virgós , S. Cabezas-Díaz and J. G. Mangas 2007. Increase of large game species in Mediterranean areas: Is the European wildcat (Felis silvestris) facing a new threat? Biological Conservation , 138: 321–329. Google Scholar

40.

A. J. Lucio 1991. Selección de hábitat de la perdiz roja (Alectoris rufa) en matorrales supramediterráneos del NW de la cuenca del Duero. Aplicaciones para la gestión del hábitat cinegético. Ecología , 5: 337–353. Google Scholar

41.

P. Mineau and C. Palmer 2013. The impact of the nation's most widely used insecticides on birds. American Bird Conservancy , 1–96. Google Scholar

42.

D. Mohr , L. W. Cohnstaedt and W. Topp 2005. Wild boar and red deer affect soil nutrients and soil biota in steep oak stands of the Eifel. Soil Biology & Biochemistry , 37: 693–700. Google Scholar

43.

I. Newton 2004. The recent declines of farmland bird populations in Britain: an appraisal of causal factors and conservation actions. Ibis , 146: 579–600. Google Scholar

44.

M. Paschetta , V. La Morgia , D. Masante , M. Negro , A. Rolando and M. Isaia 2013. Grazing history influences biodiversity: a case study on ground-dwelling arachnids (Arachnida: Araneae, Opiliones) in the Natural Park of Alpi Marittime (NW Italy). Journal of Insect Conservation , 17: 339–356. Google Scholar

45.

R. Perea , M. Girardello and A. San Miguel 2014. Big game or big loss? High deer densities are threatening woody plant diversity and vegetation dynamics. Biodiversity and Conservation , 23: 1303–1318. Google Scholar

46.

R. Putman , P. Watson and J. Langbein 2011. Assessing deer densities and impacts at the appropriate level for management: a review of methodologies for use beyond the site scale. Mammal Review , 41: 197–219. Google Scholar

47.

N. Selva , T. Berezowska-Cnota and I. Elgueroclaramunt 2014. Unforeseen effects of supplementary feeding: Ungulate baiting sites as hotspots for ground-nest predation. PLoS ONE 9: e90740. Google Scholar

48.

SEO/BIRDLIFE, 2014. Resultados del Programa SACRE. Informe 1998–2013. SEO/BirdLife. Madrid. Google Scholar

49.

T. R. E. Southwood and D. J. Cross 2002. Food requirements of grey partridge Perdix perdix chicks. Wildlife Biology , 8: 175–183. Google Scholar

50.

C. Stein , S. B. Unsicker , A. Kahmen , M. Wagner , V. Audorff , H. Auge , D. Prati and W. W. Weisser 2010. Impact of invertebrate herbivory in grasslands depends on plant species diversity. Ecology , 91: 1639–1650. Google Scholar

51.

J. M. Vargas , J. C. Guerrero , M. A. Farfán , A. M. Barbosa and R. Real 2006. Land use and environmental factors affecting red-legged partridge (Alectoris rufa) hunting yields in southern Spain. European Journal of Wildlife Research , 52: 188–195. Google Scholar

52.

J. M. Vargas , M. A. Farfán , J. C. Guerrero , A. M. Barbosa and R. Real 2007. Geographical and environmental correlates of big and small game in Andalusia (southern Spain). Wildlife Research , 34: 498–506. Google Scholar

53.

J. Vicente , U. HöFle , I. G. Fernández-De-Mera and C. Gortázar 2007. The importance of parasites life histories and host density in predicting the impact of infections in red deer. Oecologia , 152: 655–664. Google Scholar
A. J. Carpio, J. Oteros, J. Vicente, F. S. Tortosa, and J. Guerrero-Casado "Factors Affecting Red-Legged Partridge Alectoris rufa Abundance on Big-Game Hunting Estates: Implications for Management and Conservation," Ardeola 62(2), 283-297, (1 December 2015). https://doi.org/10.13157/arla.62.2.2015.283
Received: 23 February 2015; Accepted: 1 June 2015; Published: 1 December 2015
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