Animal Biology, Vol. 57, No. 3, pp. 301-314 (2007) Koninklijke Brill NV, Leiden, 2007.
Also available online - www.brill.nl/ab
Habitat associations of small mammals in farmed landscapes: implications for agri-environmental schemes CARLOS RODRÍGUEZ 1,∗ , SALVADOR J. PERIS 2 1 Department
of Applied Biology, Estación Biológica de Doñana, CSIC, Avda María Luisa s/n., Pabellón del Perú, 41013 Sevilla, Spain 2 Departament of Animal Biology, Universidad de Salamanca, Campus Miguel de Unamuno, edificio de Farmacia, 37071 Salamanca, Spain
Abstract—The small mammal community in 21 localities of north-western Spain was evaluated in the light of land use composition. The two geomorphologic categories characterising the study area, the main use of the land (arable/pastoral) and main crop types of each sampling locality were used as potential predictors of the relative abundance of five common small mammal species. The Common vole, Microtus arvalis showed a weak relationship with land uses, probably due to the recent colonisation process this species experienced in the study area. The relative abundance of the Algerian mouse, Mus spretus and the Lusitanian pine vole, Microtus lusitanicus was best explained by models built at the broadest regional scale, the former being more abundant in the eastern area, the latter in the western area. The Greater white-toothed shrew, Crocidura russula showed a positive relationship with grassland coverage, whilst the Wood mouse, Apodemus sylvaticus benefited from increasing proportions of fallow lands within the landscape. These two species are then expected to respond positively to those agri-environmental schemes including the increase of fallows and grassy vegetation within the arable landscape (EU recommendations). However, further efforts are needed to predict, at least qualitatively, the response of other small mammal species to the changing farmed landscape. This is especially true for two endemic species occurring at this area: the Cabrera vole, Microtus cabrerae and the Lusitanian pine vole, and for which this kind of information is almost absent. Keywords: agri-environment schemes; biodiversity; habitat preferences; Mediterranean; small mammals.
∗ Corresponding author; e-mail:
[email protected] Current address: Institute of Ecology, University of Jena, Dornburger Str. 159, D-07743 Jena, Germany, Tel: +49 3641 949453; Fax: +49 3641 949402
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INTRODUCTION
Changes in land uses have been identified as one of the most important global threats for biodiversity (Sala et al., 2000). In Western Europe, the agricultural subsidies of the European Union’s (EU) Common Agricultural Policy (CAP) that encouraged agricultural production have had deleterious effects both on the ranges and numbers of many populations of farmland organisms (Love et al., 2000; Donald et al., 2001; Thorbek and Bilde, 2004). For this reason, it is considered that modern agriculture constitutes a major anthropogenic threat to biodiversity, comparable to climate change in its ability to affect vast areas (Donald et al., 2002). Recently however, the EU decoupled subsidies from agricultural production and made agrienvironment schemes, which can be used to benefit biodiversity, compulsory in all EU countries. These schemes include, as recommendations, the reduction of pesticide and fertilizer applications, changes in the time of ploughing or mowing to increase the availability of stubbles and fallows, or direct management actions such as increasing field margins, which are known to benefit biodiversity in farmed landscapes (e.g. Kleijn et al., 2006). Despite the importance of agri-environmental schemes as policy instruments to protect biodiversity in agricultural landscapes (EEA, 2004), their effectiveness has been shown to be marginal to moderate in the last decade (Kleijn et al., 2006). The lack of clear and unambiguous biodiversity objectives at the start of the scheme, and a low scientific basis, are some of the reasons argued to explain this low effectiveness (Kleijn and Sutherland, 2003; Kleijn et al., 2006). In addition, the scientific knowledge required to appropriately design agri-environmental schemes is clearly skewed towards avian populations, for which ecologists are currently able to predict, at least qualitatively, the potential effect of different features belonging to agriculture intensification (Ormerod et al., 2003). However, for some organisms and geographical areas, the lack of information hinders the development of appropriate conservation schemes. Such is the case of small mammals in Mediterranean environments and their associated high levels of endemicity and rarity (Baquero and Tellería, 2001; Krystufek and Griffiths, 2002). Few investigations have addressed the response of small mammal species to changing farmed landscapes (but see Torre et al., 1996; Cagnin et al., 1998; de la Peña et al., 2003). With the main aim of increasing knowledge on this topic, we investigated how land use influences small mammal diversity and the relative abundance of five common small mammal species in a Mediterranean landscape. Rather than focusing on microhabitat preferences, our approach intended to find those variables which best explained the habitat associations of these species at two different spatial scales from a landscape perspective. Thus, a broader, regional scale accounts for geomorphologic features and latitude/longitude gradients to which small mammals may respond (Moreno and Barbosa, 1992), whilst a more detailed scale accounts for the composition of crop types around each sampling locality that indicate the associations of these species with particular crop types or land uses (e.g. Olson and Brewer, 2003).
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Study area The study was conducted in the South of the Province of Zamora, north-western Spain (fig. 1). The area belongs to the Northern Plateau and ranges in altitude from 350 to 500 m. Mean daily temperatures in July, the warmest month of the year, range from 16-18◦ C in the north-western border to 22-24◦ C in the south-western border, but most of the area has a mean July temperature of 20-22◦ C. Mean daily temperatures in January, the coldest month of the year, range from 2-3◦ C in the west to 6-9◦ C in the east. Because of the Atlantic influence, the rainfall pattern follows a west-east gradient with mean annual values of 600-800 mm in the west and values below 450 mm in the east. In agreement with this pattern, eastern localities are dominated by arable land with dry cereal crops, vineyards and irrigated crops (mainly corn and beet), whilst in western localities, crops alternate with patches of oak forests (Quercus ilex, Q. faginea and Q. pyrenaica), and Mediterranean dehesas (savannah-like grasslands) where a low input grazing system still exists.
Figure 1. Sampling localities in the study area, Province of Zamora, Spain. Gray plots indicate the municipalities where pellets and land use information were collected. Latitude and longitude range is indicated.
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MATERIAL AND METHODS
Sampling We analyzed Barn Owl (Tyto alba) pellets as a way of assessing the relative abundance of small mammals species. This owl is a common species in the study area, and it is well distributed among different environments (Marti and del Moral, 2003). Because of the relatively low home range and euryphagic habits of the species (Taylor, 1994), it is considered that barn owl pellets accurately reflect the relative abundance of small mammals in the field (Clark and Bunck, 1991; Taylor, 1994). In addition, previous studies have explicitly compared this method against live-trapping in Mediterranean environments, and both provided very similar results (Luiselli and Capizzi, 1996). Nonetheless, the method may be inappropriate to evaluate the relative proportion of rare species. For this reason, and despite its higher value from the conservation point of view, we only focused on the five most common small mammal species, generally widespread in the study area (Palomo and Gisbert, 2002) to analyze their relationships with land uses composition. These species were: the Algerian mouse Mus spretus Lataste, 1883, the Wood mouse Apodemus sylvaticus Linnaeus, 1758, the Greater whitetoothed shrew Crocidura russula Hermann, 1780, the Common vole Microtus arvalis asturianus Miller, 1908, and the Lusitanian pine vole Microtus lusitanicus Gerbe, 1879. The whole set of small mammal species recorded in the study area was only used to calculate the Simpson diversity index. We used this index because it performs well with heterogeneous and modest sample sizes (Lande, 1996), the Kemp’ transformation of the index being the most appropriate for our data sets (see Magurran, 2003). Pellets were collected during 1993 and 1994 at 21 barn owl resting places within villages. The home range of the barn owl varies from 2 to 7 km2 , and it is frequently assumed that a radius of 3 km around resting/breeding sites is sufficient to characterize barn owl’s habitat (Martinez and Zuberogoitia, 2004; Bond et al., 2005). The minimum distance between each collecting point and its closest neighbour was 3.8 km (median = 10 km) so they are far enough away to be considered independent samples. A mean of 156 prey-items (range 27-606) were collected in these places. We used dichotomic guides (Dueñas and Peris, 1985; Gosàlbez, 1987; Paz and Benzal, 1990) and zoological collections to identified prey items at the species level. Land use information According to geomorphologic criteria, the western part of the study area was characterised by an erosive plain, whilst a sedimentary plain characterized the eastern part. The sampling localities were then classified as belonging to the western or eastern part. We also used agrarian statistics from the Spanish Ministry of Agriculture to obtain the relative coverage of land uses around sampling localities. Each locality showed a particular combination of herbaceous crops, woody crops,
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fallow land, threshing land (plots formerly used to separate the grain from their chaff and straw by means of the thresher), forests, natural grasslands, meadows, and unproductive land. The relative proportion of these crop types with respect to the total surface was obtained on a municipality basis. This is considered to be an appropriate scale because they occupy an estimated mean radius of 3.6 km around sampling sites. For each locality, we also considered the main use of the land: arable or grassland. Statistical analyses Generalised Linear Models or GLMs were used as a mathematical description of the relationship between the above defined habitat’s features and the relative abundance of each small mammal species at each locality. A set of GLMs was built using the SAS V.8 Genmod procedure setting a binomial distribution of errors and a logit link function. Starting from a null model, we followed a forward stepwise GLM procedure to build a multivariate model that included the set of variables that best explained the relative proportion of each species. We used p < 0.05 as a criterion to include/exclude new variables in the models. Because the response variable was defined by the quotient between the number of individuals belonging to a given species and the total number of prey items in each sampling point, models were able to correct for different sample sizes (see Jovani and Tella, 2006). Models built for diversity values used a normal distribution of errors and the identity link. To correct for inter-annual and seasonal fluctuations in the Barn Owl diet (Clark and Bunck, 1991) we tested the significance of both year and season. For comparing levels within a factor, the first level was assigned the value 0 and then other levels measured the change from the first level. Interactions were nonsignificant unless otherwise stated. Models were corrected for data over-dispersion using the dscale option of the Genmod procedure, which uses the square root of deviance divided by the degrees of freedom as scale parameter (SAS institute, 2000). In these cases, we used F tests instead of Chi tests as recommended by Crawley (1993). Because of the high number of land use variables characterizing each sampling locality, and to avoid autocorrelation among them, we used Principal Component Analysis (PCA) as a data reduction method. The three main axes resulting from PCA were then used as potential predictors of the relative abundance of each small mammal species. During the statistical procedure, we first modelled the effect of each group of explanatory variables: eastern vs. western localities, arable vs. pastoral use and the three main PCA axes, separately. We then, attempted to build models that included variables from any of the groups, which potentially could explain more variation than the initial models. To evaluate the information content of models together with their degree of complexity, we used the Akaike Information Criterion (AIC; Sakamoto et al., 1986). According to this criterion, from a set of models built for the same response variable, we should select the one showing the smallest value of AIC. For all models built for the same response variable,
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we calculate their AIC weights (ranging from 0 to 1; highest being the best) as a way to indicate the probability that the model was the best among the whole set of candidate models (Johnson and Omland, 2004). PCA were made in Statistica’99. AIC values were calculated with S-Plus.
RESULTS
We identified a total of 5644 prey items at the species level, including 12 small mammal species (table 1). With the exception of M. arvalis, the relative abundance of the selected small mammal species was independent of either year or season. For this reason, only models for M. arvalis included both year and season in order to correct for the effect of these variables. Mus spretus was more abundant in the eastern area and in arable land, while the opposite result was found for Crocidura russula, Microtus lusitanicus and Apodemus sylvaticus (table 2). M. arvalis did not show any pattern at this spatial scale. PC analyses grouped the proportion of crop types around each sample point in three main axes. Axis 1 accounted for the relative contribution of herbaceous crops (negative loadings), and pastures (positive loadings), axis 2 for the relative contribution of woody crops and fallow lands at positive loadings, and axis 3 for the relative contribution of irrigated crops at negative loadings. For a better understanding, these axes will be referred as grassland axis, fallow axis, and irrigation axis, respectively. According to PCA, the variation posed by the composition of crop types in the study area could be thus summarized in the dichotomy between grasslands and herbaceous crops, and the relative abundance of fallow lands, woody crops and irrigated crops (70% of total variation). More information on PC analysis could be found in appendix 1. Table 1. Percentage of occurrence of small mammal species in barn owl pellets. Asterisks identify endemic species. Latin name
Common name
Arvicola sapidus Apodemus sylvaticus Crocidura russula Microtus agrestis Microtus arvalis Microtus cabrerae* Microtus duodecimcostatus Microtus lusitanicus* Mus domesticus Mus spretus Rattus norvegicus Rattus rattus
Southern water vole Wood mouse Greater white-toothed shrew Field vole Common vole Cabrera vole Mediterranean Pine vole Lusitanian Pine vole Harvest mouse Algerian mouse Brown rat Black rat
% of occurrence
