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Ground nesting birds in roadside borders of the Argentine Pampas: habitat use and predation risk of artificial nests

Ground nesting birds in roadside borders of the Argentine Pampas: habitat use and predation risk... Revista Brasileira de Ornitologia 27(4): 261–274. ARTICLE December 2019 Ground nesting birds in roadside borders of the Argentine Pampas: habitat use and predation risk of artificial nests 1,2,3 1 Daniela María Depalma & Myriam Emilia Mermoz Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA-CONICET), Buenos Aires, Argentina. Departamento de Ecología, Genética y Evolución, Universidad de Buenos Aires, Buenos Aires, Argentina. Corresponding author: danieladepalma@ege.fcen.uba.ar Received on 19 February 2019. Accepted on 18 November 2019. ABSTRACT: Habitat loss and fragmentation have led to grassland bird declines, with ground nesters particularly vulnerable. Roadsides could provide habitat, although their suitability depends on several roadside and field characteristics. Vegetation structure determines foraging and nesting site availability. In addition, road delimits sharp edges where the activity of nest predators is usually higher, whereas herbaceous vegetation determines ground nest concealment. Trees could provide lookouts to predators, and modified habitat and woodlands in surrounding fields could offer additional resour ces to predators. Our objective was to assess habitat suitability for ground nester birds in roadsides belonging to one modified grassland of the Argentine Pampas. We surveyed birds (90 plots) and monitored artificial nests (60 plots) in different road types: unpaved, paved of one-lane per side, and paved of two-lanes per side. Within each road type, we evaluated the relationship that ground nesters abundance had with vegetation structure of roadsides and surrounding fields. In addition, we related predation of artificial nests with t he proximity to the road, roadside vegetation, and modified land and woodlands of surrounding fields. We made 2832 recor ds of 84 species using roadsides, including 1083 records of 13 ground nesting species. Abundance of ground nesters increased with tall grass cover of roadsides and decreased with the number of native trees within roadsides. Roughly half (31/60) of the artificial nests were pre dated and 82.6% of the identified egg-marks were of mammal teeth. Nest predation decreased with nest proximity to the road. Our results emphasize the importance of tall grass cover of roadsides for the conservation of ground nesting species, and the necessity of monitoring natural nests in order to clarify the effect of trees, proximity to the road, and other environmental variables on nest success. KEY-WORDS: corridors, field margins, grassland bir ds, habitat remnants, survival analysis. INTRODUCTION determines the availability of shelter, foraging sites and nesting sites (Meunier et al. 1999, Kociolek et al. 2011). Habitat loss and fragmentation have led to the decline of Moreover, habitat availability in the surrounding fields grassland bird populations worldwide (Askins et al. 2007, may also promote bird abundance in roadsides (Huijser Zuckerberg et al. 2009, Azpiroz et al. 2012, Reif 2013). & Clevenger 2006), while woodlands and modified Amongst them, ground nesting birds are particularly land (i.e., crops or human settlements) have exhibited vulnerable due to the greater exposure of eggs, chicks a negative association with the abundance of birds and incubating adults to mammalian and bird predators inhabiting grassland remnants (Leston 2013, Dotta (Pietz et al. 2009, Fletcher et al. 2010), which increases et al. 2016, Pretelli et al. 2018). Some grassland birds with habitat fragmentation due to higher amounts of might avoid these areas since woodlands can increase the habitat edges with which predators are associated (Evans abundance of specialist predators (Vickery et al. 2009, 2004, Huijser & Clevenger 2006). Thus, conservation Ellison et al. 2013) and brood parasites (Patten et al. researchers have become interested in habitat remnants 2006, Pietz et al. 2009), and modified land may offer that could benefit the conservation of these species resources to generalist predators (Evans 2004, Benítez- (Weidman & Litvaitis 2011, Duchardt et al. 2016, Port López et al. 2010). & Schottler 2017). In this context, it has been proposed In addition, roadside characteristics can affect ground that roadside networks can provide habitat (Meunier et nesting bird populations due to their influence on nest al. 1999, Bergin et al. 2000), although their suitability for predation risk. Nest detectability by predators decreases grassland birds depends on several factors affecting bird with greater structural complexity of the vegetation, abundance and nest predation. which contributes to nest concealment (Weidinger 2002, One key factor influencing the abundance of Conover et al. 2011). In contrast, detectability may be grassland birds in roadsides is vegetation structure, which increased by the proximity to trees, which offer lookouts Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz o o to avian predators that use visual cues (Söderström et al. city (37 0'7''S; 57 8'10''W), Buenos Aires province, 1998, Bergin et al. 2000, Flaspohler et al. 2001) as well Argentina, within the flooding Pampa. In the flooding as to brood parasites (Patten et al. 2006). Moreover, roads Pampa, mean temperature varies from 23 C in January lack structural complexity, and nest proximity to the road to 13 C in July with mean annual precipitation of 1000 could imply the proximity to hard habitat edges where mm (Soriano et al. 2001). The area exhibits subtle predator activity is higher (Fletcher & Koford 2003, topographic variations (most lands are less than 4 m Weldon & Haddad 2005, King et al. 2009). Likewise, above sea level), with lowlands remaining flooded for predation can depend on wider scale factors such as the long periods. For this reason, the flooding Pampa is the prevalence of woodlands and modified lands, which offer least cropped portion of the Pampas and the distribution resources to generalist predators and may enhance their of many native bird species is restricted to this area, abundance in the landscape (Hogrefe et al. 1998, Vickery giving it a high conservation value (Codesido et al. 2011). et al. 2009, Ellison et al. 2013). However, since 1990's increasing crop lands and cattle Analyzing factors that affect both abundance and production pose conservation implications (Agra et al. predation risk, therefore, constitutes an appropriate 2015). Vegetation in this area is a mosaic of extensive method to assess roadsides' suitability for birds in grasslands disrupted by wetlands with a high presence of threatened grasslands. In particular, some of the Schoenoplectus californicus (Family Cyperaceae), Solanum most important Neotropical grasslands are those of glaucophyllum (Solanaceae), Senecio spp. (Asteraceae), and southeastern South America, constituted by a part of Typha spp. (Typhaceae), and by smaller patches of native Uruguay, southern Brazil and mainly by the Pampas in woodlands comprised mostly of Celtis ehrenbergiana Argentina (Soriano et al. 2001). The conservation status (Cannabaceae) in the higher areas (Vervoorst 1967). of the Pampas is critical since currently more than 75% of About 70% of the area is used for cattle production, with their extent has been converted into croplands (Viglizzo land crops covering 20% (Codesido & Bilenca 2011) and et al. 2011). Such habitat loss has caused a decrease in the remaining land consisting in deep water bodies, tree the abundance and distribution of many grassland bird plantations, dunes, salt marshes, and urban areas (Baldi species, including a high proportion of ground nesting & Paruelo 2008).We conducted our study in October– birds (Fraga 2003, Di Giacomo & Di Giacomo 2004, November 2015, which comprises the peak of the Filloy & Bellocq 2007, Azpiroz et al. 2012). Roadside breeding season for most bird species (de la Peña 2015). conservation and management practices are still Within an area of approximately 80,000 ha, we sampled uncommon in the region, although it has been reported roads representing the three types of roads present in the that ground nesting birds and many other bird species area. Sampled road types were: unpaved roads of local use use roadsides more frequently than adjacent pastures (three roads), one paved road of one-lane per side that and crops (i.e., soy and maize, Leveau & Leveau 2011), connects General Madariaga city with Las Armas town, and that grassland nesting bird richness increase with the and one paved road of two-lanes per side that connects amount of roadside borders in rural areas (Codesido & General Madariaga city with Pinamar city. All these roads Bilenca 2011). could be considered as transects, being the mean distance Our objective here was to assess breeding habitat among transects' midpoints 20.4 km (range: 6.2–26.5 suitability for ground nesting birds in roadsides belonging km). Road types have different speed limits (two-lanes per to one modified grassland of the Argentine Pampas. side: 110 km/h, one-lane per side: 100 km/h, unpaved: In particular, we analyzed the effects that roadside and 60 km/h). In addition, road types could have different surrounding field characteristics have on bird abundance traffic intensity in terms of vehicles per unit of time. The and nest predation. To achieve that aim, in different two-lanes per side probably has the highest amount of road types, we performed bird surveys and evaluated the vehicles per unit of time since it connects two cities and relationship of bird abundance with vegetation structure leads to one of the most important touristic spots along of roadsides and surrounding fields. A dditionally, we the coast of Buenos Aires province. We further considered conducted an experiment with artificial nests to identify the potential differences among road types from a birds' nest predators, and to evaluate the effects that proximity perspective (see Statistical analysis), since it has been to the road and vegetation structure of roadsides and reported that traffic-related factors such as noise can affect surrounding fields have on ground nest predation. bird distribution and behavior (Seiler 2001, Kociolek et al. 2011). Along each road we selected points at random METHODS distances from the beginning of the sampling section of the road (one-lane per side: n = 30 points, two-lanes Study area and sampling sites per side: n = 30, unpaved: n = 30), being the minimum distance between neighbour points 400 m. Then, in each Field work was carried out near General Madariaga point we established one sampling plot, which was a Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz fragment of roadside borders of 200-m length that was exotic pasture Festuca arundinacea –with low presence of centred in the point and comprised the area between the Bromus catharticus, Dactylis glomerata, Triticum aestivum, edge of the road, either right or left, and the fence of its Nassella neesiana, Avena sativa and Phalaris minor), adjacent field. Since the width of our roadside borders Pampa grass (individuals of the native grass Cortaderia had a range of 6.0–45.6 m, the area of our sampling plots selloana of 0.7–2 m height), dicotyledoneous (grassland varied between 0.12 and 1.08 ha. of 30–80 cm height dominated by exotic flowering plants with non-negligible presence of native flowering plants), Bird sampling wetland vegetation (S. californicus and Typha spp.), water, native trees (C. ehrenbergiana and Scutia buxifolia) and In each sampling plot, we performed bird surveys using exotic trees (mainly Populus spp.). All flowering plants 10-min point counts, during the first 4 h after sunrise and were classified into the finest level possible, and t hus in good weather conditions (Bibby 2000). Sampling plots we determined that exotic flowering plants belonging were divided in two 100-m length subplots, and each of to the family Brassicaceae represented 55% of the total two observers recorded every bird seen or heard in one flowering plants, and p lants belonging to the native subplot, disregarding those birds flying above the plot. species Matricaria chamomila represented 32%. We also We considered that there was minimal need to account counted individual trees within the entire area of each for detection probability given the high visibility in these sampling plot. In all statistical analyses, the number of roadside borders mainly constituted by grassland, and trees was incorporated instead of tree cover, since it may because each observer recorded individuals at a maximum be a more accurate variable to measure in linear fragments distance of 50 m (Smucker et al. 2005). To increase the (McDonald & Johnson 1995; Table 1). The number of accuracy of abundance estimations, we surveyed each trees has been also mentioned as one of the major factors plot twice (one visit during October and the other influencing bird richness and abundance in field borders one during November), and the maximum number of (Hinsley & Bellamy 2000). individuals recorded for each species was considered the In addition, while measuring vegetation cover at species' abundance. Later, we classified species by their plot scale, we described the cover of surrounding fields. nesting sites (de la Peña 2015). We only considered in Later, we estimated the cover of surrounding fields in further analyses the abundance of those grassland birds satellite images of November 2015 (Image 2017 Digital ® TM that build their nests directly on the ground, or very close Globe, source: Google Earth ) with Google Earth Pro to the ground on clumps of grasses (de la Peña 2015), Software (Sullivan 2009). Validating the images with hereafter designated as “ground nesting birds”. We also our observations recorded in the field, we measured t he noted which of these ground nesting bird species are percentage of short grassland, seminatural grassland, considered as grassland obligates (Azpiroz & Blake 2009). native woodland, exotic woodland, and modified land Scientific nomenclature was in accor dance with South within a 200-m radius circular area around each plot American Classification Committee (SACC–American (Table 1). Short grassland consisted in extremely short Ornithologists' Union, Remsen-Jr. et al. 2019). grass intensively grazed or mowed. Seminatural grassland consisted in tall grass often moderately disturbed by Vegetation sampling grazing. Modified land consisted in crops (mainly maize and soy), stubble, and human settlements. Finally, native In each sampling plot, we estimated local vegetation woodland consisted in groups of trees mainly composed cover based on three transects perpendicular to the road, by C. ehrenbergiana and S. buxifolia, and exotic woodland separated by 75 m. One observer (D. Depalma) measured were composed by at least 80% of exotic trees (mostly the length of intersection of each vegetation type (see Eucalyptus spp., Table 1). We considered the percentage below) on each transect, by walking along the transect of seminatural grasslands as available habitat for grassland using a measuring tape (Matteucci & Colma 1982). birds, and the percentage of native and exotic woodlands When there was no accessibility (e.g., wetlands), the length and modified land as potential sour ces of predators. of intersection of vegetation types was measured with a ® TM rangefinder (Redfield Raider 550). Then we expressed Artificial nests experiment the lengths of intersection as percentages. Finally, in every plot, for each vegetation type we used the average of the Artificial nests carry a certain bias since their visual three transects. The perpendicular orientation of transects signals (absence of parental activity) and chemical allowed us to account for the vegetation gradient present signals differ from those of natural nests, and t hus they in roadside borders. may underestimate or overestimate the actual predation Vegetation types consisted of short grass (areas risk, according to nest type and predator community consisting mainly in grasses shorter than 30 cm), tall composition (Thompson & Burhans 2004). However, grass (grassland of 30–80 cm height dominated by the they provided us a possibility to evaluate the relationship Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Table 1. Characteristics of roadside borders of the Argentine Pampas. Frequencies of occurrence and mean value ± standard deviation per sampling plot are shown. Ranges are in parentheses. Vegetation type Frequency of occurrence (%) Value per plot Roadsides     Short grass (%) 86.6 10.8 ± 10.5 (0–39.5) Tall grass (%) 70 32.7 ± 28.5 (0–95.8) Pampa grass (%) 47.7 5.7 ± 10.1 (0–48.5) Dicotyledonous (%) 82.2 5.4 ± 6.9 (0–32.9) Wetland (%) 72.2 21.4 ± 21.8 (0–87) Native trees (n) 55.5 7.4 ± 14.5 (0–71) Exotic trees (n) 5.5 1.4 ± 7.6 (0–50) Total trees (n) 58.8 8.8 ± 17.4 (0–89) Surrounding fields   Seminatural grassland (%) 46.6 12.3 ± 17.2 (0–72.1) Short grass (%) 60  2.7 ± 23.9 (0–81.2) Wetland (%) 76.6 14.4 ± 15.1 (0–52.8) Modified land (%) 44.4 8.6 ± 14.3 (0–55.4) Native woodland (%) 43.3 1.3 ± 2.6 (0–11.5) Exotic woodland (%) 22.2 0.6 ± 1.4 (0–6.5) Total woodland (%) 66.6 2.5 ± 3.8 (0–24.19) between predation risk and environmental variables we observed the natural and the paraffin-filled eggs and through a field experiment, controlling for nest location, looked for marks. We interpreted the marks based on clutch size and differences in parental a ctivity around the criteria used by Cozzani & Zalba (2012) to identify the nest (Thompson & Burhans 2004). In addition, we ground nest predators in Buenos Aires province. Thus, were able to identify types of predators by the marks left we considered incisor marks on the paraffin-filled egg as on artificial eggs (Zanette & Jenkins 2000). Within a predation by small mammals, while bigger and deeper representative subsample of 60 plots (i.e., one-lane per teeth marks, and horseshoe shape marks on the natural side: n = 20, two-lanes per side: n = 20, unpaved: n = 20), egg were considered as predation by medium-sized we placed one artificial nest made of hemp on the ground. mammals. Likewise, unique, deep marks on the paraffin- To resemble the nesting sites of ground nesting birds, all filled egg were considered as predation by birds, and the nests were located beneath a clump of tall grass, therefore presence of two marks separated by a distance of 0.9 cm equally sheltered. Monitoring was performed every four was considered predation by ophidians. days until predation occurred or during 16 days, which encompassed the approximate duration of laying plus Statistical analysis incubation periods of most ground nesting passerines (de la Peña 2015). The artificial nest (10.5 cm diameter All statistical analyses were conducted using the R × 5.5 cm depth) was always placed in the center of the environment (R Core Team 2019). We evaluated the 200 m of the plot, beneath the first clump of tall grass relationship between total abundance of ground nesting encountered by walking from the road into the roadside birds and environmental variables using a Generalized border. We used this method instead of selecting fixed Linear Mixed Model (GLMM) with the “glmadmb” locations because, due to the presence of wetlands within function of the “glmmADMB” package (Bolker et al. most roadsides, many locations were unsuitable for nest 2012). Since overdispersion occurred when adjusting placement (Table 1). In each nest, we put two quail the model to a Poisson distribution, we solved this eggs (Coturnix coturnix): one natural egg and the other problem by using a Negative Binomial distribution. filled with paraffin and tied to the nest b y a nylon thread We accounted for potential interdependencies among (Svagelj et al. 2003). We considered the removal and/ plots belonging to the same road type by incorporating or break of at least one of the eggs as a predation event. “road type” as a random factor. Furthermore, since plots When predation was detected, nests were immediately along unpaved roads were grouped in three different removed and no longer monitored. After monitoring, roads, we incorporated the random factor “road identity” Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz nested within road type. The dependent variable in the the occurrence of predation (0 or 1). The coefficient of model was total abundance of ground nesting birds. an independent variable indicates its relationship with We considered nine candidate independent variables the occurrence of predation: a positive coefficient means measured at plot scale: the percentage (%) of short that the variable is positive associated with the occurrence grass, tall grass, dicotyledonous, Pampa grass, wetland of predation. Coefficients were calculated by the partial vegetation and water, the number of native trees, the maximum likelihood method. Likewise, for every number of exotic trees, and the number of total trees. independent variable the model estimates a Hazard Ratio We also considered five candidate independent variables (HR). A HR > 1 indicates that the variable is positively of surrounding fields (200-m radius): available habitat associated with the probability of predation, while a HR for grassland birds (percentage of seminatural grassland), < 1 indicates the opposite. We considered nine candidate and sources of predators (percentage of native woodland, independent variables measured at plot scale: the percentage of exotic woodland, percentage of total percentage (%) of short grass, tall grass, dicotyledonous, woodland and percentage modified land). Since sampling Pampa grass, wetland vegetation and water, the number plots had different widths, we incorporated p lot area as an of native trees, the number of exotic trees, and the offset, which specifies an a priori known component to be number of total trees. We also considered four candidate included in the linear predictor during fitting (Crawley independent variables of surrounding fields (sources of 2012). predators within the 200-m radius): percentage of native We evaluated the support for predictor variables by woodland, percentage of exotic woodland, percentage of information theoretic procedures (Burham & Anderson total woodland, and percentage of modified land. 2002), using the “MuMIn” package (Bartoń 2013). We To improve the parsimony of a potential global used Akaike's information criterion corrected for small model, we first built one univariate mixed model to sample size (AIC ). In order to improve the parsimony test the effect of each independent variable on survival (in terms of model parameters) of the global model, and separately, in order to further incorporate relevant to avoid generating an excessively large set of models parameters only. The only independent variable that had based on sample size which could lead to spurious results a significant effect on survival was “ distance to road”. We (Grueber et al. 2011), we only incorporated relevant checked the assumptions about the linear functional form parameters. In order to define relevant parameters, we of the independent variables and hazards proportionality first built 14 univariate models, each of them having one (i.e., the ratio of the survival rates remaining constant candidate independent variable as the only predictor. We through time; Santabárbara et al. 2016). To accomplish incorporated to the global model only those variables that this, we deleted two nests belonging to the two-lanes per lowered the AICc in more than 2 units relative to the null side road that impeded the linear functional form of the model. Those variables were the per centage of tall grass variable “distance to road”. These nests (i.e., outliers) were within roadsides and the number of native trees within removed from all the analyses. roadsides (the correlation between these two variables was not significant). In addition, we also included t he interaction between both variables. We considered RESULTS models with all possible combinations of the three final predictor variables and ranked them by their AIC . Finally, Bird abundance we obtained parameter estimates by averaging models with a ΔAIC < 4 from the best model, and calculated We made 2832 records of 84 species using roadside 95% confidence interval limits of parameter estimates borders. Amongst them, 1083 individuals (38.2%) (Grueber et al. 2011). belonging to 13 species (15.5%) were ground nesting To test the effects of environmental variables on species (Appendix I). Seven of these species are considered artificial nests' survival we used a mixed Cox proportional grassland obligates (Leistes superciliaris, Anthus correndera, hazards model (Cox 1972) with the “coxme” package Sicalis luteola, Embernagra platensis, Vanellus chilensis, (Therneau & Therneau 2018). This model is an extension Nothura maculosa and Rynchotus rufescens; Appendix I). As of survival analysis similar to a logistic regression, and is shown by the GLMM, ground nesting birds' abundance able to evaluate the relationship between independent was positively associated with the percentage of tall grass variables and the rate of occurrence of predation within roadsides, and negatively associated with the (Santabárbara et al. 2016). As with the model of bird number of native trees within roadsides (Table 2). abundance, we accounted for potential interdependencies among plots belonging to the same road and road type by Survival of artificial ground nests incorporating the random factor “road identity” nested within the random factor “road type”. The dependent Of the 60 artificial nests we set out, 31 were predated variable was composed of the survival time (days) and within the 16-day period (one-lane per side: n = 10, two- Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz lanes per side: n = 10, unpaved: n = 11). Thus, artificial Moreover, during field work we detected potential nest survival was 48.3%. According to the criteria used mammalian predators: Galictis cuja (Order Carnivora), by Cozzani & Zalba (2012), 43.7% of predated nests (14 Conepatus chinga (Order Carnivora), Cavia aperea nests) exhibited small mammal marks, 15.6% (5 nests) (Order Rodentia) and Didelphis albiventer (Order were predated by medium sized-mammals, 9.4% (3 nests) Didelphimorphia). We also detected potential ophidian were predated by birds and 3.1% (1 nest), by ophidians predators: Liophis poecilogyrus and Liophis anomalus (Fig. 1). In 25% of nests (8 nests), we could not identify (Order Squamata). Likewise, we recorded potential avian the predator, since in five cases the artificial egg had non predators during bird surveys: Caracara plancus, Milvago identifiable marks (Fig. 1), and in three cases it had been chimango, Chroicocephalus maculipennis, Circus buffoni removed. In such situations, we could not identify the and Guira guira (Appendix I). predator using the natural egg either, since it had been As shown by the results of mixed univariate Cox removed in four nests, and it exhibited unidentifiable regressions, only distance to road had a significant effect marks in the remaining nests. on nest survival. The probability of nest predation was Table 2. Candidate Generalized Linear Mixed Models with factors influencing the abundance of grassland ground nesting bird species in roadside borders of the Argentine Pampas, listed in decreasing order of importance. Only those models with a ΔAIC < 4 from the best model and the null model are included. Averaged estimates of parameters are shown in the second part of the table. Those parameters whose 95% Confidence Intervals ex cluded 0 are in bold. K: number of parameters. TGR: tall grass of roadsides; NTR: native trees of roadsides; TGR*NTR: interaction term. SE: unconditional Standard Error. CI: 95% Confidence Interval. Candidate models K Log-likelihood AIC ΔAIC Weight c c TGR + NTR 6 -262.22 537.5 0 0.58 TGR 5 -264.39 539.5 2.04 0.21 TGR + NTR + TGR*NTR (Global model) 7 -262.1 539.6 2.13 0.2 Null model 4 -268.91 546.3 8.83 0.01  Model averaging Estimate SE CI Relative importance TGR 0.247 0.07 0.097, 0.397 1 NTR -0.092 0.07 -0.229, -0.005 0.79 TGR*NTR 0.001 0.02 -0.073, 0.119 0.2 Figure 1. Predated natural and paraffin-filled Coturnix coturnix eggs on roadside borders of the Argentine Pampas. Examples of marks produced by small-sized mammals' incisors (A), medium-sized mammals' teeth marks (B), a horseshoe-shaped mark produced by a medium-sized mammal (C), one unique bird's beak mark (D), two marks produced by an ophidian predator (E) and one unidentifiable mark (F). Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz positively associated with the distance to road (P < 0.05; DISCUSSION Table 3, Fig. 2). Nevertheless, the probability of nest predation also exhibited a marginal positive association In order to assess the suitability of roadsides for ground with the number of native trees within roadsides (P = nesting birds in one modified grassland of the Argentine 0.05, Table 3). Pampas, we evaluated the influence of roadside factors and surrounding field factors on bir d abundance, and on the predation of artificial nests. We found t hat bird abundance was positively associated with tall grass cover of roadsides and negatively associated with the number of native trees of roadsides, while evidence of predation decreased with proximity of nests to the road. Regarding bird abundance, our results indicate that tall grass cover of roadsides favors their use by ground nesting birds, while the number of native trees reduces it. Similarly, it has been previously reported that ground nesting birds of the Pampas such as Sicalis luteola use grassy field margins more frequently than margins with trees (Leveau & Leveau 2011). In another study of birds inhabiting field margins of the Argentine Espinal region, authors found that while total bird density increased with the number of trees, the density of some ground nesters decreased (Di Giacomo & Lopez-de-Casenave 2010). In this sense, it is possible that tall grass increase the amount of escape cover and nest concealment for most ground Figure 2. Expected survival curves for artificial nests located at nesters considered in our study (Isacch & Martínez 2001, different distances to the road in roadside borders of Argentine Davis 2005), while native trees in the proximities imply Pampas. Survival curves were built by fitting a mixed Cox proportional hazards model with distance to the road as the higher rates of nest predation and parasitism (Flaspohler predictor variable. Predicted survival for nests located at 5, 10, et al. 2001, Patten et al. 2006, Pietz et al. 2009). It is 15 and 20 m from the road are shown. not clear why only native trees, rather than total trees, Table 3. Factors influencing predation of artificial nests in roadside borders of Argentine Pampas, tested by Mixed Cox Logistic Regression models. Regression coefficient and hazard ratio for the predictor variable of each of the univariate models are shown. Significant predictor variables (P < 0.05) are in bold. Univariate model Coefficient P-value Hazard ratio Short grass 0.005 0.57 1.01 Tall grass -0.005 0.41 0.99 Pampa grass 0.014 0.5 1.01 Dicotyledonous -0.036 0.27 0.96 Wetland vegetation 0.007 0.43 1.01 Water -0.005 0.73 0.99 Native trees 0.02· 0.05 1.02 Exotic trees -0.02 0.37 0.97 Total trees 0.006 0.41 1.01 Distance to road 0.102* 0.02 1.11 Modified land < -0.001 0.21 0.99 Native woodland 0.028 0.71 1.02 Exotic woodland 0.105 0.37 1.11 Total woodland < -0.001 0.97 0.99 * P < 0.05 · P < 0.1 Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz were negatively associated with bird abundance. One as Didelphis albiventer, Galictis cuja and Cavia aperea explanation is that native trees attract more predators than (Attademo et al. 2011, Bauni et al. 2017). Therefore, it exotic trees. For example, in the Pampas, insectivorous is possible that mammals do not prefer to forage in road birds usually prefer to forage on native trees than on exotic proximities, but rather move along the road, parallel to it ones (Cueto & Lopez-de-Casenave 2002). Therefore, (Forman & Alexander 1998, Meunier et al. 1999). native trees could attract some insectivorous birds that Nevertheless, the success of real nests may be predate nests opportunistically, and thus represent an influenced by additional factors. Real nests might not additional predation pressure. Another explanation is be exposed to the same predation pressures as artificial that native trees were more abundant than exotic ones nests (Thompson & Burhans 2004), and artificial nests in roadsides (Table 1) and formed continuous lines can underestimate predation by birds due to the lack along field fences, which could provide more shelter of parental activity (Söderström et al. 1998, Flaspohler to predators, and be perceived by sharp edges by birds et al. 2001). Thus we cannot reject based on our results (Fletcher & Koford 2003, Weldon & Haddad 2005). the possibility that nest predation may be causing the Unlike local vegetation of roadsides, the cover of negative relationship between bird abundance and native surrounding fields did not relate with bird abundance. trees, and that native trees may have a significant, rather On the one hand, the lack of associations between bird than marginal, positive effect on nest predation. During abundance and the cover of seminatural grasslands in the bird surveys, we detected avian predators perching on landscape could suggest that during the breeding season trees in roadsides (Appendix I), and trees could offer them birds travel short distances to fulfill t heir requirements, lookouts during the predation of real nests (Flaspohler et and forage within nest proximities rather than using al. 2001). surrounding alternative habitats (Robinson et al. 2004, Another explanation, although not excluding, Vickery et al. 2009). On the other hand, the lack of would be that the negative association between grassland associations between abundance and sources of predation birds and native trees is actually the result of a higher such as woodlands and modified lands could be related to risk of nest parasitism near trees (Patten et al. 2006, the characteristics of our study area. Also in the flooding Pietz et al. 2009). Within the Pampas, nest parasitism Pampa, Pretelli et al. (2018) found no negative effect of by the generalist brood parasite Molothrus bonariensis is agriculture on the abundance of grassland specialist birds one of the major causes of egg losses for nesting birds, inhabiting grassland remnants, probably because in this due to the punctures performed on the host's eggs region agriculture is often mixed with short grasses and during inspection visits (Massoni & Reboreda 2002). pastures. In contrast, they did report a negative effect of However, this icterid might not be able to break the a continuous forest matrix around grassland remnants on thick shell of quail eggs (Svagelj et al. 2003). Likewise, it bird abundance, although our study area did not exhibit might not visit artific ial nests frequently, since parasites' a forest matrix but rather small scattered patches of behavior is usually based on parental activity around woodland, which could be perceived differently b y birds. the nest (Wilson et al. 1998). The monitoring of real Regarding nest predation, most marks left on nests would be necessary in order to test the potential artificial nests belonged to mammals. A high frequency implications of native trees for nest predation and of predation by mammals in our nests is consistent parasitism. In addition, real nest monitoring could with other studies, which compared nest predation at also clarify the effec t of road proximity on ground nest different heights and reported that mammals were the success. Although our artific ial nests were less likely most frequent predators of ground nests (Söderström to be predated in road proximities, chicks of natural et al. 1998, Colombelli-Négrel & Kleindorfer 2009). nests that hatch and fled ge closer to roads may be more As proposed for other habitat strips within modified exposed to collisions (Kociolek et al. 2011). landscapes, these roadsides could serve as corridors for In summary, this paper highlights that roadside mammals, which could predate nests in an opportunistic borders of the flooding Pampas are inhabited by a wide manner as they travel (Meunier et al. 1999, Conover et range of grassland bird species, including several grassland al. 2011). obligates, and their conservation value could be increased Additionally, predation mostly due to mammals with the application of appropriate managements. Such could explain the striking negative relationship between managements should consider the importance of tall grass proximity to the road and the probability of predation. for ground nesting birds, as well as the negative effects These animals are usually affected by the presence of of native trees on their abundance. Future studies that roads (Seiler 2001, Benítez-López et al. 2010). Moreover, involve the monitoring of real nests are necessary in order recent researches about animals killed by collisions in to elucidate the potential effects of native trees, distance Argentine roads found dead individuals of some of the to the road, and other environmental variables on ground mammalian predators we detected during this study such nest success. Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz a los usos de la tierra en la provincia de Buenos Aires, p. 511–526. ACKNOWLEDGEMENTS In: P. Laterra, E.G. Jobbágy & J.M. Paruelo (eds.). Valoración de servicios ecosistémicos: conceptos, herramientas y aplicaciones para el We thank Emilio M. Charnelli, Daniela R. Acosta, ordenamiento territorial. Buenos Aires: INTA. Natalia Mufato, Cecilia Zilli and Víctor Blanco for the Codesido M., González-Fischer C. & Bilenca D. 2011. Distributional assistance in the field, and Pa blo Picca for the assistance changes of landbird species in agroecosystems of central Argentina. Condor 113: 266–273. in the determination of plant species. We appreciate Colombelli-Négrel D. & Kleindorfer S. 2009. Nest height, nest the improvements in English usage made by Nicole concealment, and predator type predict nest predation in Superb Arcilla through the Association of Field Ornithologists' Fairy-wrens (Malurus cyaneus). Ecological Research 24: 921–928. program of editorial assistance. D.M.D. was supported Conover R.R., Dinsmore S.J. & Burger L.W. 2011. Effects of conservation practices on bird nest density and survival in by a Doctoral Fellowship from the Consejo Nacional intensive agriculture. Agriculture, Ecosystems & Environment 141: de Investigaciones Científicas y Técnicas (CONICET). 126–132. M.E.M. is a Research Fellow of CONICET. This work Cox D.R. 1972. Regression models and life-tables. Journal of the Royal was supported by a Neotropical Grassland Conservancy Statistical Society: Series B (Methodological) 34: 187–202. Cozzani N. & Zalba S.M. 2012. Depredadores de nidos en pastizales (NGC) Ritt-Kellogg Grant to M.E.M., and N.G.C. del Parque Provincial Ernesto Tornquist (provincia de Buenos Equipment Grant and Student Grant to D.M.D. Authors Aires, Argentina): importancia relativa bajo distintas intensidades have no conflicts of interest to disclose. de pastoreo. Hornero 27: 137–148. Crawley M.J. 2012. The R book. Chichester: John Wiley & Sons. Cueto V.R. & Lopez-de-Casenave J. 2002. 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Order, Family, Species Total individuals Presence (%) Mean abundance TINAMIFORMES Tinamidae 27 22.22 0.03 Rhynchotus rufescens* ** 7 7.77 0.07 Nothura maculosa* ** ANSERIFORMES Anhimidae 1 1.11 0.01 Chauna torquata Anatidae Dendrocygna viduata 1 1.11 0.01 Callonetta leucophrys 4 2.22 0.04 15 7.77 0.16 Spatula versicolor 2 1.11 0.02 Anas georgica Anas flavirostris 4 3.33 0.04 Netta peposaca 3 2.22 0.03 PODICIPEDIFORMES Podicipedidae Rollandia rolland 4 2.22 0.04 Podilymbus podiceps 2 2.22 0.02 1 1.11 0.01 Podiceps major COLUMBIFORMES Columbidae 10 8.88 0.11 Patagioenas picazuro Zenaida auriculata 63 36.66 0.7 Columbina picui 3 2.22 0.03 CUCULIFORMES Cuculidae Guira guira 25 5.55 0.27 GRUIFORMES Aramidae Aramus guarauna 1 1.11 0.01 Rallidae 1 1.11 0.01 Pardirallus maculatus Pardirallus sanguinolentus 15 13.33 0.16 Porphyriops melanops 2 2.22 0.01 3 2.22 0.03 Fulica rufifrons Fulica armillata 6 2.22 0.06 Fulica leucoptera 4 4.44 0.04 APODIFORMES Trochilidae Chlorostilbon lucidus 8 3.33 0.08 Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Order, Family, Species Total individuals Presence (%) Mean abundance CHARADRIIFORMES Charadriidae 2 1.11 0.02 Vanellus chilensis* ** Recurvirostridae 2 1.11 0.02 Himantopus mexicanus Laridae Chroicocephalus maculipennis 29 5.55 0.32 Gelochelidon nilotica 1 1.11 0.01 SULIFORMES Phalacrocoracidae Phalacrocorax brasilianus 1 1.11 0.01 PELECANIFORMES Ardeidae Ardea alba 2 2.22 0.02 1 1.11 0.01 Egretta thula ACCIPITRIFORMES Accipitridae 1 1.11 0.01 Elanus leucurus Rostrhamus sociabilis 21 14.44 0.23 Circus buffoni 5 3.33 0.05 1 1.11 0.01 Rupornis magnirostris PICIFORMES Picidae 1 1.11 0.01 Colaptes melanochloros Colaptes campestris 2 2.22 0.02 FALCONIFORMES Falconidae Caracara plancus 24 16.66 0.26 Milvago chimango 27 24.44 0.3 PSITTACIFORMES Psittacidae Myiopsitta monachus 62 18.88 0.68 PASSERIFORMES Furnariidae Furnarius rufus 32 25.55 0.35 Phleocryptes melanops 90 37.77 1 2 2.22 0.02 Leptasthenura platensis Phacellodomus striaticollis 23 2.22 0.25 Anumbius annumbi 25 21.11 0.31 35 24.44 0.38 Limnoctites sulphuriferus Synallaxis albescens 3 1.11 0.03 Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Order, Family, Species Total individuals Presence (%) Mean abundance Tyrannidae Serpophaga nigricans 8 7.77 0.08 1 1.11 0.01 Serpophaga subcristata Pseudocolopteryx flaviventris 61 38.88 0.67 Tachuris rubrigastra 8 5.55 0.08 14 10 0.15 Pyrocephalus rubinus Hymenops perspicillatus 144 74.44 1.6 Satrapa icterophrys 7 6.66 0.07 2 2.22 0.02 Machetornis rixosa Pitangus sulphuratus 57 35.55 0.63 Tyrannus melancholicus 17 13.33 0.18 64 37.77 0.71 Tyrannus savana Hirundinidae Progne tapera 9 6.66 0.1 3 3.33 0.03 Progne chalybea Tachycineta leucorrhoa 24 20 0.26 Hirundo rustica 128 28.88 1.42 Troglodytidae Troglodytes aedon 25 22.22 0.27 Cistothorus platensis 1 1.11 0.01 Polioptilidae Polioptila dumicola 5 4.44 0.05 Turdidae 5 5.55 0.05 Turdus rufiventris Mimidae Mimus saturninus 14 10 0.15 Motacillidae 3 3.33 0.03 Anthus correndera* ** Fringillidae Spinus magellanicus 9 6.66 0.1 Passerellidae Zonotrichia capensis* 378 96.66 4.2 Icteridae 1 1.11 0.01 Leistes superciliaris* ** Molothrus bonariensis 219 73.33 2.43 Amblyramphus holosericeus 19 12.22 0.21 58 16.66 0.64 Agelaioides badius Agelasticus thilius 152 56.66 1.68 Pseudoleistes virescens 222 72.22 2.46 Thraupidae Sicalis flaveola 28 15.55 0.31 526 85.55 5.84 Sicalis luteola* ** 8 5.55 0.08 Sporophila caerulescens Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Order, Family, Species Total individuals Presence (%) Mean abundance 111 65.55 1.23 Embernagra platensis* ** 64 45.55 0.71 Poospiza nigrorufa Donacospiza albifrons* 6 5.55 0.06 Paroaria coronata 1 1.11 0.01 5 3.33 0.05 Pipraeidea bonariensis Revista Brasileira de Ornitologia 27(4): 2019 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ornithology Research Springer Journals

Ground nesting birds in roadside borders of the Argentine Pampas: habitat use and predation risk of artificial nests

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Revista Brasileira de Ornitologia 27(4): 261–274. ARTICLE December 2019 Ground nesting birds in roadside borders of the Argentine Pampas: habitat use and predation risk of artificial nests 1,2,3 1 Daniela María Depalma & Myriam Emilia Mermoz Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA-CONICET), Buenos Aires, Argentina. Departamento de Ecología, Genética y Evolución, Universidad de Buenos Aires, Buenos Aires, Argentina. Corresponding author: danieladepalma@ege.fcen.uba.ar Received on 19 February 2019. Accepted on 18 November 2019. ABSTRACT: Habitat loss and fragmentation have led to grassland bird declines, with ground nesters particularly vulnerable. Roadsides could provide habitat, although their suitability depends on several roadside and field characteristics. Vegetation structure determines foraging and nesting site availability. In addition, road delimits sharp edges where the activity of nest predators is usually higher, whereas herbaceous vegetation determines ground nest concealment. Trees could provide lookouts to predators, and modified habitat and woodlands in surrounding fields could offer additional resour ces to predators. Our objective was to assess habitat suitability for ground nester birds in roadsides belonging to one modified grassland of the Argentine Pampas. We surveyed birds (90 plots) and monitored artificial nests (60 plots) in different road types: unpaved, paved of one-lane per side, and paved of two-lanes per side. Within each road type, we evaluated the relationship that ground nesters abundance had with vegetation structure of roadsides and surrounding fields. In addition, we related predation of artificial nests with t he proximity to the road, roadside vegetation, and modified land and woodlands of surrounding fields. We made 2832 recor ds of 84 species using roadsides, including 1083 records of 13 ground nesting species. Abundance of ground nesters increased with tall grass cover of roadsides and decreased with the number of native trees within roadsides. Roughly half (31/60) of the artificial nests were pre dated and 82.6% of the identified egg-marks were of mammal teeth. Nest predation decreased with nest proximity to the road. Our results emphasize the importance of tall grass cover of roadsides for the conservation of ground nesting species, and the necessity of monitoring natural nests in order to clarify the effect of trees, proximity to the road, and other environmental variables on nest success. KEY-WORDS: corridors, field margins, grassland bir ds, habitat remnants, survival analysis. INTRODUCTION determines the availability of shelter, foraging sites and nesting sites (Meunier et al. 1999, Kociolek et al. 2011). Habitat loss and fragmentation have led to the decline of Moreover, habitat availability in the surrounding fields grassland bird populations worldwide (Askins et al. 2007, may also promote bird abundance in roadsides (Huijser Zuckerberg et al. 2009, Azpiroz et al. 2012, Reif 2013). & Clevenger 2006), while woodlands and modified Amongst them, ground nesting birds are particularly land (i.e., crops or human settlements) have exhibited vulnerable due to the greater exposure of eggs, chicks a negative association with the abundance of birds and incubating adults to mammalian and bird predators inhabiting grassland remnants (Leston 2013, Dotta (Pietz et al. 2009, Fletcher et al. 2010), which increases et al. 2016, Pretelli et al. 2018). Some grassland birds with habitat fragmentation due to higher amounts of might avoid these areas since woodlands can increase the habitat edges with which predators are associated (Evans abundance of specialist predators (Vickery et al. 2009, 2004, Huijser & Clevenger 2006). Thus, conservation Ellison et al. 2013) and brood parasites (Patten et al. researchers have become interested in habitat remnants 2006, Pietz et al. 2009), and modified land may offer that could benefit the conservation of these species resources to generalist predators (Evans 2004, Benítez- (Weidman & Litvaitis 2011, Duchardt et al. 2016, Port López et al. 2010). & Schottler 2017). In this context, it has been proposed In addition, roadside characteristics can affect ground that roadside networks can provide habitat (Meunier et nesting bird populations due to their influence on nest al. 1999, Bergin et al. 2000), although their suitability for predation risk. Nest detectability by predators decreases grassland birds depends on several factors affecting bird with greater structural complexity of the vegetation, abundance and nest predation. which contributes to nest concealment (Weidinger 2002, One key factor influencing the abundance of Conover et al. 2011). In contrast, detectability may be grassland birds in roadsides is vegetation structure, which increased by the proximity to trees, which offer lookouts Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz o o to avian predators that use visual cues (Söderström et al. city (37 0'7''S; 57 8'10''W), Buenos Aires province, 1998, Bergin et al. 2000, Flaspohler et al. 2001) as well Argentina, within the flooding Pampa. In the flooding as to brood parasites (Patten et al. 2006). Moreover, roads Pampa, mean temperature varies from 23 C in January lack structural complexity, and nest proximity to the road to 13 C in July with mean annual precipitation of 1000 could imply the proximity to hard habitat edges where mm (Soriano et al. 2001). The area exhibits subtle predator activity is higher (Fletcher & Koford 2003, topographic variations (most lands are less than 4 m Weldon & Haddad 2005, King et al. 2009). Likewise, above sea level), with lowlands remaining flooded for predation can depend on wider scale factors such as the long periods. For this reason, the flooding Pampa is the prevalence of woodlands and modified lands, which offer least cropped portion of the Pampas and the distribution resources to generalist predators and may enhance their of many native bird species is restricted to this area, abundance in the landscape (Hogrefe et al. 1998, Vickery giving it a high conservation value (Codesido et al. 2011). et al. 2009, Ellison et al. 2013). However, since 1990's increasing crop lands and cattle Analyzing factors that affect both abundance and production pose conservation implications (Agra et al. predation risk, therefore, constitutes an appropriate 2015). Vegetation in this area is a mosaic of extensive method to assess roadsides' suitability for birds in grasslands disrupted by wetlands with a high presence of threatened grasslands. In particular, some of the Schoenoplectus californicus (Family Cyperaceae), Solanum most important Neotropical grasslands are those of glaucophyllum (Solanaceae), Senecio spp. (Asteraceae), and southeastern South America, constituted by a part of Typha spp. (Typhaceae), and by smaller patches of native Uruguay, southern Brazil and mainly by the Pampas in woodlands comprised mostly of Celtis ehrenbergiana Argentina (Soriano et al. 2001). The conservation status (Cannabaceae) in the higher areas (Vervoorst 1967). of the Pampas is critical since currently more than 75% of About 70% of the area is used for cattle production, with their extent has been converted into croplands (Viglizzo land crops covering 20% (Codesido & Bilenca 2011) and et al. 2011). Such habitat loss has caused a decrease in the remaining land consisting in deep water bodies, tree the abundance and distribution of many grassland bird plantations, dunes, salt marshes, and urban areas (Baldi species, including a high proportion of ground nesting & Paruelo 2008).We conducted our study in October– birds (Fraga 2003, Di Giacomo & Di Giacomo 2004, November 2015, which comprises the peak of the Filloy & Bellocq 2007, Azpiroz et al. 2012). Roadside breeding season for most bird species (de la Peña 2015). conservation and management practices are still Within an area of approximately 80,000 ha, we sampled uncommon in the region, although it has been reported roads representing the three types of roads present in the that ground nesting birds and many other bird species area. Sampled road types were: unpaved roads of local use use roadsides more frequently than adjacent pastures (three roads), one paved road of one-lane per side that and crops (i.e., soy and maize, Leveau & Leveau 2011), connects General Madariaga city with Las Armas town, and that grassland nesting bird richness increase with the and one paved road of two-lanes per side that connects amount of roadside borders in rural areas (Codesido & General Madariaga city with Pinamar city. All these roads Bilenca 2011). could be considered as transects, being the mean distance Our objective here was to assess breeding habitat among transects' midpoints 20.4 km (range: 6.2–26.5 suitability for ground nesting birds in roadsides belonging km). Road types have different speed limits (two-lanes per to one modified grassland of the Argentine Pampas. side: 110 km/h, one-lane per side: 100 km/h, unpaved: In particular, we analyzed the effects that roadside and 60 km/h). In addition, road types could have different surrounding field characteristics have on bird abundance traffic intensity in terms of vehicles per unit of time. The and nest predation. To achieve that aim, in different two-lanes per side probably has the highest amount of road types, we performed bird surveys and evaluated the vehicles per unit of time since it connects two cities and relationship of bird abundance with vegetation structure leads to one of the most important touristic spots along of roadsides and surrounding fields. A dditionally, we the coast of Buenos Aires province. We further considered conducted an experiment with artificial nests to identify the potential differences among road types from a birds' nest predators, and to evaluate the effects that proximity perspective (see Statistical analysis), since it has been to the road and vegetation structure of roadsides and reported that traffic-related factors such as noise can affect surrounding fields have on ground nest predation. bird distribution and behavior (Seiler 2001, Kociolek et al. 2011). Along each road we selected points at random METHODS distances from the beginning of the sampling section of the road (one-lane per side: n = 30 points, two-lanes Study area and sampling sites per side: n = 30, unpaved: n = 30), being the minimum distance between neighbour points 400 m. Then, in each Field work was carried out near General Madariaga point we established one sampling plot, which was a Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz fragment of roadside borders of 200-m length that was exotic pasture Festuca arundinacea –with low presence of centred in the point and comprised the area between the Bromus catharticus, Dactylis glomerata, Triticum aestivum, edge of the road, either right or left, and the fence of its Nassella neesiana, Avena sativa and Phalaris minor), adjacent field. Since the width of our roadside borders Pampa grass (individuals of the native grass Cortaderia had a range of 6.0–45.6 m, the area of our sampling plots selloana of 0.7–2 m height), dicotyledoneous (grassland varied between 0.12 and 1.08 ha. of 30–80 cm height dominated by exotic flowering plants with non-negligible presence of native flowering plants), Bird sampling wetland vegetation (S. californicus and Typha spp.), water, native trees (C. ehrenbergiana and Scutia buxifolia) and In each sampling plot, we performed bird surveys using exotic trees (mainly Populus spp.). All flowering plants 10-min point counts, during the first 4 h after sunrise and were classified into the finest level possible, and t hus in good weather conditions (Bibby 2000). Sampling plots we determined that exotic flowering plants belonging were divided in two 100-m length subplots, and each of to the family Brassicaceae represented 55% of the total two observers recorded every bird seen or heard in one flowering plants, and p lants belonging to the native subplot, disregarding those birds flying above the plot. species Matricaria chamomila represented 32%. We also We considered that there was minimal need to account counted individual trees within the entire area of each for detection probability given the high visibility in these sampling plot. In all statistical analyses, the number of roadside borders mainly constituted by grassland, and trees was incorporated instead of tree cover, since it may because each observer recorded individuals at a maximum be a more accurate variable to measure in linear fragments distance of 50 m (Smucker et al. 2005). To increase the (McDonald & Johnson 1995; Table 1). The number of accuracy of abundance estimations, we surveyed each trees has been also mentioned as one of the major factors plot twice (one visit during October and the other influencing bird richness and abundance in field borders one during November), and the maximum number of (Hinsley & Bellamy 2000). individuals recorded for each species was considered the In addition, while measuring vegetation cover at species' abundance. Later, we classified species by their plot scale, we described the cover of surrounding fields. nesting sites (de la Peña 2015). We only considered in Later, we estimated the cover of surrounding fields in further analyses the abundance of those grassland birds satellite images of November 2015 (Image 2017 Digital ® TM that build their nests directly on the ground, or very close Globe, source: Google Earth ) with Google Earth Pro to the ground on clumps of grasses (de la Peña 2015), Software (Sullivan 2009). Validating the images with hereafter designated as “ground nesting birds”. We also our observations recorded in the field, we measured t he noted which of these ground nesting bird species are percentage of short grassland, seminatural grassland, considered as grassland obligates (Azpiroz & Blake 2009). native woodland, exotic woodland, and modified land Scientific nomenclature was in accor dance with South within a 200-m radius circular area around each plot American Classification Committee (SACC–American (Table 1). Short grassland consisted in extremely short Ornithologists' Union, Remsen-Jr. et al. 2019). grass intensively grazed or mowed. Seminatural grassland consisted in tall grass often moderately disturbed by Vegetation sampling grazing. Modified land consisted in crops (mainly maize and soy), stubble, and human settlements. Finally, native In each sampling plot, we estimated local vegetation woodland consisted in groups of trees mainly composed cover based on three transects perpendicular to the road, by C. ehrenbergiana and S. buxifolia, and exotic woodland separated by 75 m. One observer (D. Depalma) measured were composed by at least 80% of exotic trees (mostly the length of intersection of each vegetation type (see Eucalyptus spp., Table 1). We considered the percentage below) on each transect, by walking along the transect of seminatural grasslands as available habitat for grassland using a measuring tape (Matteucci & Colma 1982). birds, and the percentage of native and exotic woodlands When there was no accessibility (e.g., wetlands), the length and modified land as potential sour ces of predators. of intersection of vegetation types was measured with a ® TM rangefinder (Redfield Raider 550). Then we expressed Artificial nests experiment the lengths of intersection as percentages. Finally, in every plot, for each vegetation type we used the average of the Artificial nests carry a certain bias since their visual three transects. The perpendicular orientation of transects signals (absence of parental activity) and chemical allowed us to account for the vegetation gradient present signals differ from those of natural nests, and t hus they in roadside borders. may underestimate or overestimate the actual predation Vegetation types consisted of short grass (areas risk, according to nest type and predator community consisting mainly in grasses shorter than 30 cm), tall composition (Thompson & Burhans 2004). However, grass (grassland of 30–80 cm height dominated by the they provided us a possibility to evaluate the relationship Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Table 1. Characteristics of roadside borders of the Argentine Pampas. Frequencies of occurrence and mean value ± standard deviation per sampling plot are shown. Ranges are in parentheses. Vegetation type Frequency of occurrence (%) Value per plot Roadsides     Short grass (%) 86.6 10.8 ± 10.5 (0–39.5) Tall grass (%) 70 32.7 ± 28.5 (0–95.8) Pampa grass (%) 47.7 5.7 ± 10.1 (0–48.5) Dicotyledonous (%) 82.2 5.4 ± 6.9 (0–32.9) Wetland (%) 72.2 21.4 ± 21.8 (0–87) Native trees (n) 55.5 7.4 ± 14.5 (0–71) Exotic trees (n) 5.5 1.4 ± 7.6 (0–50) Total trees (n) 58.8 8.8 ± 17.4 (0–89) Surrounding fields   Seminatural grassland (%) 46.6 12.3 ± 17.2 (0–72.1) Short grass (%) 60  2.7 ± 23.9 (0–81.2) Wetland (%) 76.6 14.4 ± 15.1 (0–52.8) Modified land (%) 44.4 8.6 ± 14.3 (0–55.4) Native woodland (%) 43.3 1.3 ± 2.6 (0–11.5) Exotic woodland (%) 22.2 0.6 ± 1.4 (0–6.5) Total woodland (%) 66.6 2.5 ± 3.8 (0–24.19) between predation risk and environmental variables we observed the natural and the paraffin-filled eggs and through a field experiment, controlling for nest location, looked for marks. We interpreted the marks based on clutch size and differences in parental a ctivity around the criteria used by Cozzani & Zalba (2012) to identify the nest (Thompson & Burhans 2004). In addition, we ground nest predators in Buenos Aires province. Thus, were able to identify types of predators by the marks left we considered incisor marks on the paraffin-filled egg as on artificial eggs (Zanette & Jenkins 2000). Within a predation by small mammals, while bigger and deeper representative subsample of 60 plots (i.e., one-lane per teeth marks, and horseshoe shape marks on the natural side: n = 20, two-lanes per side: n = 20, unpaved: n = 20), egg were considered as predation by medium-sized we placed one artificial nest made of hemp on the ground. mammals. Likewise, unique, deep marks on the paraffin- To resemble the nesting sites of ground nesting birds, all filled egg were considered as predation by birds, and the nests were located beneath a clump of tall grass, therefore presence of two marks separated by a distance of 0.9 cm equally sheltered. Monitoring was performed every four was considered predation by ophidians. days until predation occurred or during 16 days, which encompassed the approximate duration of laying plus Statistical analysis incubation periods of most ground nesting passerines (de la Peña 2015). The artificial nest (10.5 cm diameter All statistical analyses were conducted using the R × 5.5 cm depth) was always placed in the center of the environment (R Core Team 2019). We evaluated the 200 m of the plot, beneath the first clump of tall grass relationship between total abundance of ground nesting encountered by walking from the road into the roadside birds and environmental variables using a Generalized border. We used this method instead of selecting fixed Linear Mixed Model (GLMM) with the “glmadmb” locations because, due to the presence of wetlands within function of the “glmmADMB” package (Bolker et al. most roadsides, many locations were unsuitable for nest 2012). Since overdispersion occurred when adjusting placement (Table 1). In each nest, we put two quail the model to a Poisson distribution, we solved this eggs (Coturnix coturnix): one natural egg and the other problem by using a Negative Binomial distribution. filled with paraffin and tied to the nest b y a nylon thread We accounted for potential interdependencies among (Svagelj et al. 2003). We considered the removal and/ plots belonging to the same road type by incorporating or break of at least one of the eggs as a predation event. “road type” as a random factor. Furthermore, since plots When predation was detected, nests were immediately along unpaved roads were grouped in three different removed and no longer monitored. After monitoring, roads, we incorporated the random factor “road identity” Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz nested within road type. The dependent variable in the the occurrence of predation (0 or 1). The coefficient of model was total abundance of ground nesting birds. an independent variable indicates its relationship with We considered nine candidate independent variables the occurrence of predation: a positive coefficient means measured at plot scale: the percentage (%) of short that the variable is positive associated with the occurrence grass, tall grass, dicotyledonous, Pampa grass, wetland of predation. Coefficients were calculated by the partial vegetation and water, the number of native trees, the maximum likelihood method. Likewise, for every number of exotic trees, and the number of total trees. independent variable the model estimates a Hazard Ratio We also considered five candidate independent variables (HR). A HR > 1 indicates that the variable is positively of surrounding fields (200-m radius): available habitat associated with the probability of predation, while a HR for grassland birds (percentage of seminatural grassland), < 1 indicates the opposite. We considered nine candidate and sources of predators (percentage of native woodland, independent variables measured at plot scale: the percentage of exotic woodland, percentage of total percentage (%) of short grass, tall grass, dicotyledonous, woodland and percentage modified land). Since sampling Pampa grass, wetland vegetation and water, the number plots had different widths, we incorporated p lot area as an of native trees, the number of exotic trees, and the offset, which specifies an a priori known component to be number of total trees. We also considered four candidate included in the linear predictor during fitting (Crawley independent variables of surrounding fields (sources of 2012). predators within the 200-m radius): percentage of native We evaluated the support for predictor variables by woodland, percentage of exotic woodland, percentage of information theoretic procedures (Burham & Anderson total woodland, and percentage of modified land. 2002), using the “MuMIn” package (Bartoń 2013). We To improve the parsimony of a potential global used Akaike's information criterion corrected for small model, we first built one univariate mixed model to sample size (AIC ). In order to improve the parsimony test the effect of each independent variable on survival (in terms of model parameters) of the global model, and separately, in order to further incorporate relevant to avoid generating an excessively large set of models parameters only. The only independent variable that had based on sample size which could lead to spurious results a significant effect on survival was “ distance to road”. We (Grueber et al. 2011), we only incorporated relevant checked the assumptions about the linear functional form parameters. In order to define relevant parameters, we of the independent variables and hazards proportionality first built 14 univariate models, each of them having one (i.e., the ratio of the survival rates remaining constant candidate independent variable as the only predictor. We through time; Santabárbara et al. 2016). To accomplish incorporated to the global model only those variables that this, we deleted two nests belonging to the two-lanes per lowered the AICc in more than 2 units relative to the null side road that impeded the linear functional form of the model. Those variables were the per centage of tall grass variable “distance to road”. These nests (i.e., outliers) were within roadsides and the number of native trees within removed from all the analyses. roadsides (the correlation between these two variables was not significant). In addition, we also included t he interaction between both variables. We considered RESULTS models with all possible combinations of the three final predictor variables and ranked them by their AIC . Finally, Bird abundance we obtained parameter estimates by averaging models with a ΔAIC < 4 from the best model, and calculated We made 2832 records of 84 species using roadside 95% confidence interval limits of parameter estimates borders. Amongst them, 1083 individuals (38.2%) (Grueber et al. 2011). belonging to 13 species (15.5%) were ground nesting To test the effects of environmental variables on species (Appendix I). Seven of these species are considered artificial nests' survival we used a mixed Cox proportional grassland obligates (Leistes superciliaris, Anthus correndera, hazards model (Cox 1972) with the “coxme” package Sicalis luteola, Embernagra platensis, Vanellus chilensis, (Therneau & Therneau 2018). This model is an extension Nothura maculosa and Rynchotus rufescens; Appendix I). As of survival analysis similar to a logistic regression, and is shown by the GLMM, ground nesting birds' abundance able to evaluate the relationship between independent was positively associated with the percentage of tall grass variables and the rate of occurrence of predation within roadsides, and negatively associated with the (Santabárbara et al. 2016). As with the model of bird number of native trees within roadsides (Table 2). abundance, we accounted for potential interdependencies among plots belonging to the same road and road type by Survival of artificial ground nests incorporating the random factor “road identity” nested within the random factor “road type”. The dependent Of the 60 artificial nests we set out, 31 were predated variable was composed of the survival time (days) and within the 16-day period (one-lane per side: n = 10, two- Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz lanes per side: n = 10, unpaved: n = 11). Thus, artificial Moreover, during field work we detected potential nest survival was 48.3%. According to the criteria used mammalian predators: Galictis cuja (Order Carnivora), by Cozzani & Zalba (2012), 43.7% of predated nests (14 Conepatus chinga (Order Carnivora), Cavia aperea nests) exhibited small mammal marks, 15.6% (5 nests) (Order Rodentia) and Didelphis albiventer (Order were predated by medium sized-mammals, 9.4% (3 nests) Didelphimorphia). We also detected potential ophidian were predated by birds and 3.1% (1 nest), by ophidians predators: Liophis poecilogyrus and Liophis anomalus (Fig. 1). In 25% of nests (8 nests), we could not identify (Order Squamata). Likewise, we recorded potential avian the predator, since in five cases the artificial egg had non predators during bird surveys: Caracara plancus, Milvago identifiable marks (Fig. 1), and in three cases it had been chimango, Chroicocephalus maculipennis, Circus buffoni removed. In such situations, we could not identify the and Guira guira (Appendix I). predator using the natural egg either, since it had been As shown by the results of mixed univariate Cox removed in four nests, and it exhibited unidentifiable regressions, only distance to road had a significant effect marks in the remaining nests. on nest survival. The probability of nest predation was Table 2. Candidate Generalized Linear Mixed Models with factors influencing the abundance of grassland ground nesting bird species in roadside borders of the Argentine Pampas, listed in decreasing order of importance. Only those models with a ΔAIC < 4 from the best model and the null model are included. Averaged estimates of parameters are shown in the second part of the table. Those parameters whose 95% Confidence Intervals ex cluded 0 are in bold. K: number of parameters. TGR: tall grass of roadsides; NTR: native trees of roadsides; TGR*NTR: interaction term. SE: unconditional Standard Error. CI: 95% Confidence Interval. Candidate models K Log-likelihood AIC ΔAIC Weight c c TGR + NTR 6 -262.22 537.5 0 0.58 TGR 5 -264.39 539.5 2.04 0.21 TGR + NTR + TGR*NTR (Global model) 7 -262.1 539.6 2.13 0.2 Null model 4 -268.91 546.3 8.83 0.01  Model averaging Estimate SE CI Relative importance TGR 0.247 0.07 0.097, 0.397 1 NTR -0.092 0.07 -0.229, -0.005 0.79 TGR*NTR 0.001 0.02 -0.073, 0.119 0.2 Figure 1. Predated natural and paraffin-filled Coturnix coturnix eggs on roadside borders of the Argentine Pampas. Examples of marks produced by small-sized mammals' incisors (A), medium-sized mammals' teeth marks (B), a horseshoe-shaped mark produced by a medium-sized mammal (C), one unique bird's beak mark (D), two marks produced by an ophidian predator (E) and one unidentifiable mark (F). Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz positively associated with the distance to road (P < 0.05; DISCUSSION Table 3, Fig. 2). Nevertheless, the probability of nest predation also exhibited a marginal positive association In order to assess the suitability of roadsides for ground with the number of native trees within roadsides (P = nesting birds in one modified grassland of the Argentine 0.05, Table 3). Pampas, we evaluated the influence of roadside factors and surrounding field factors on bir d abundance, and on the predation of artificial nests. We found t hat bird abundance was positively associated with tall grass cover of roadsides and negatively associated with the number of native trees of roadsides, while evidence of predation decreased with proximity of nests to the road. Regarding bird abundance, our results indicate that tall grass cover of roadsides favors their use by ground nesting birds, while the number of native trees reduces it. Similarly, it has been previously reported that ground nesting birds of the Pampas such as Sicalis luteola use grassy field margins more frequently than margins with trees (Leveau & Leveau 2011). In another study of birds inhabiting field margins of the Argentine Espinal region, authors found that while total bird density increased with the number of trees, the density of some ground nesters decreased (Di Giacomo & Lopez-de-Casenave 2010). In this sense, it is possible that tall grass increase the amount of escape cover and nest concealment for most ground Figure 2. Expected survival curves for artificial nests located at nesters considered in our study (Isacch & Martínez 2001, different distances to the road in roadside borders of Argentine Davis 2005), while native trees in the proximities imply Pampas. Survival curves were built by fitting a mixed Cox proportional hazards model with distance to the road as the higher rates of nest predation and parasitism (Flaspohler predictor variable. Predicted survival for nests located at 5, 10, et al. 2001, Patten et al. 2006, Pietz et al. 2009). It is 15 and 20 m from the road are shown. not clear why only native trees, rather than total trees, Table 3. Factors influencing predation of artificial nests in roadside borders of Argentine Pampas, tested by Mixed Cox Logistic Regression models. Regression coefficient and hazard ratio for the predictor variable of each of the univariate models are shown. Significant predictor variables (P < 0.05) are in bold. Univariate model Coefficient P-value Hazard ratio Short grass 0.005 0.57 1.01 Tall grass -0.005 0.41 0.99 Pampa grass 0.014 0.5 1.01 Dicotyledonous -0.036 0.27 0.96 Wetland vegetation 0.007 0.43 1.01 Water -0.005 0.73 0.99 Native trees 0.02· 0.05 1.02 Exotic trees -0.02 0.37 0.97 Total trees 0.006 0.41 1.01 Distance to road 0.102* 0.02 1.11 Modified land < -0.001 0.21 0.99 Native woodland 0.028 0.71 1.02 Exotic woodland 0.105 0.37 1.11 Total woodland < -0.001 0.97 0.99 * P < 0.05 · P < 0.1 Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz were negatively associated with bird abundance. One as Didelphis albiventer, Galictis cuja and Cavia aperea explanation is that native trees attract more predators than (Attademo et al. 2011, Bauni et al. 2017). Therefore, it exotic trees. For example, in the Pampas, insectivorous is possible that mammals do not prefer to forage in road birds usually prefer to forage on native trees than on exotic proximities, but rather move along the road, parallel to it ones (Cueto & Lopez-de-Casenave 2002). Therefore, (Forman & Alexander 1998, Meunier et al. 1999). native trees could attract some insectivorous birds that Nevertheless, the success of real nests may be predate nests opportunistically, and thus represent an influenced by additional factors. Real nests might not additional predation pressure. Another explanation is be exposed to the same predation pressures as artificial that native trees were more abundant than exotic ones nests (Thompson & Burhans 2004), and artificial nests in roadsides (Table 1) and formed continuous lines can underestimate predation by birds due to the lack along field fences, which could provide more shelter of parental activity (Söderström et al. 1998, Flaspohler to predators, and be perceived by sharp edges by birds et al. 2001). Thus we cannot reject based on our results (Fletcher & Koford 2003, Weldon & Haddad 2005). the possibility that nest predation may be causing the Unlike local vegetation of roadsides, the cover of negative relationship between bird abundance and native surrounding fields did not relate with bird abundance. trees, and that native trees may have a significant, rather On the one hand, the lack of associations between bird than marginal, positive effect on nest predation. During abundance and the cover of seminatural grasslands in the bird surveys, we detected avian predators perching on landscape could suggest that during the breeding season trees in roadsides (Appendix I), and trees could offer them birds travel short distances to fulfill t heir requirements, lookouts during the predation of real nests (Flaspohler et and forage within nest proximities rather than using al. 2001). surrounding alternative habitats (Robinson et al. 2004, Another explanation, although not excluding, Vickery et al. 2009). On the other hand, the lack of would be that the negative association between grassland associations between abundance and sources of predation birds and native trees is actually the result of a higher such as woodlands and modified lands could be related to risk of nest parasitism near trees (Patten et al. 2006, the characteristics of our study area. Also in the flooding Pietz et al. 2009). Within the Pampas, nest parasitism Pampa, Pretelli et al. (2018) found no negative effect of by the generalist brood parasite Molothrus bonariensis is agriculture on the abundance of grassland specialist birds one of the major causes of egg losses for nesting birds, inhabiting grassland remnants, probably because in this due to the punctures performed on the host's eggs region agriculture is often mixed with short grasses and during inspection visits (Massoni & Reboreda 2002). pastures. In contrast, they did report a negative effect of However, this icterid might not be able to break the a continuous forest matrix around grassland remnants on thick shell of quail eggs (Svagelj et al. 2003). Likewise, it bird abundance, although our study area did not exhibit might not visit artific ial nests frequently, since parasites' a forest matrix but rather small scattered patches of behavior is usually based on parental activity around woodland, which could be perceived differently b y birds. the nest (Wilson et al. 1998). The monitoring of real Regarding nest predation, most marks left on nests would be necessary in order to test the potential artificial nests belonged to mammals. A high frequency implications of native trees for nest predation and of predation by mammals in our nests is consistent parasitism. In addition, real nest monitoring could with other studies, which compared nest predation at also clarify the effec t of road proximity on ground nest different heights and reported that mammals were the success. Although our artific ial nests were less likely most frequent predators of ground nests (Söderström to be predated in road proximities, chicks of natural et al. 1998, Colombelli-Négrel & Kleindorfer 2009). nests that hatch and fled ge closer to roads may be more As proposed for other habitat strips within modified exposed to collisions (Kociolek et al. 2011). landscapes, these roadsides could serve as corridors for In summary, this paper highlights that roadside mammals, which could predate nests in an opportunistic borders of the flooding Pampas are inhabited by a wide manner as they travel (Meunier et al. 1999, Conover et range of grassland bird species, including several grassland al. 2011). obligates, and their conservation value could be increased Additionally, predation mostly due to mammals with the application of appropriate managements. Such could explain the striking negative relationship between managements should consider the importance of tall grass proximity to the road and the probability of predation. for ground nesting birds, as well as the negative effects These animals are usually affected by the presence of of native trees on their abundance. Future studies that roads (Seiler 2001, Benítez-López et al. 2010). Moreover, involve the monitoring of real nests are necessary in order recent researches about animals killed by collisions in to elucidate the potential effects of native trees, distance Argentine roads found dead individuals of some of the to the road, and other environmental variables on ground mammalian predators we detected during this study such nest success. Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz a los usos de la tierra en la provincia de Buenos Aires, p. 511–526. ACKNOWLEDGEMENTS In: P. Laterra, E.G. Jobbágy & J.M. Paruelo (eds.). Valoración de servicios ecosistémicos: conceptos, herramientas y aplicaciones para el We thank Emilio M. Charnelli, Daniela R. Acosta, ordenamiento territorial. Buenos Aires: INTA. Natalia Mufato, Cecilia Zilli and Víctor Blanco for the Codesido M., González-Fischer C. & Bilenca D. 2011. Distributional assistance in the field, and Pa blo Picca for the assistance changes of landbird species in agroecosystems of central Argentina. Condor 113: 266–273. in the determination of plant species. We appreciate Colombelli-Négrel D. & Kleindorfer S. 2009. Nest height, nest the improvements in English usage made by Nicole concealment, and predator type predict nest predation in Superb Arcilla through the Association of Field Ornithologists' Fairy-wrens (Malurus cyaneus). Ecological Research 24: 921–928. program of editorial assistance. D.M.D. was supported Conover R.R., Dinsmore S.J. & Burger L.W. 2011. Effects of conservation practices on bird nest density and survival in by a Doctoral Fellowship from the Consejo Nacional intensive agriculture. Agriculture, Ecosystems & Environment 141: de Investigaciones Científicas y Técnicas (CONICET). 126–132. M.E.M. is a Research Fellow of CONICET. This work Cox D.R. 1972. Regression models and life-tables. Journal of the Royal was supported by a Neotropical Grassland Conservancy Statistical Society: Series B (Methodological) 34: 187–202. Cozzani N. & Zalba S.M. 2012. Depredadores de nidos en pastizales (NGC) Ritt-Kellogg Grant to M.E.M., and N.G.C. del Parque Provincial Ernesto Tornquist (provincia de Buenos Equipment Grant and Student Grant to D.M.D. Authors Aires, Argentina): importancia relativa bajo distintas intensidades have no conflicts of interest to disclose. de pastoreo. Hornero 27: 137–148. Crawley M.J. 2012. The R book. Chichester: John Wiley & Sons. Cueto V.R. & Lopez-de-Casenave J. 2002. 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Order, Family, Species Total individuals Presence (%) Mean abundance TINAMIFORMES Tinamidae 27 22.22 0.03 Rhynchotus rufescens* ** 7 7.77 0.07 Nothura maculosa* ** ANSERIFORMES Anhimidae 1 1.11 0.01 Chauna torquata Anatidae Dendrocygna viduata 1 1.11 0.01 Callonetta leucophrys 4 2.22 0.04 15 7.77 0.16 Spatula versicolor 2 1.11 0.02 Anas georgica Anas flavirostris 4 3.33 0.04 Netta peposaca 3 2.22 0.03 PODICIPEDIFORMES Podicipedidae Rollandia rolland 4 2.22 0.04 Podilymbus podiceps 2 2.22 0.02 1 1.11 0.01 Podiceps major COLUMBIFORMES Columbidae 10 8.88 0.11 Patagioenas picazuro Zenaida auriculata 63 36.66 0.7 Columbina picui 3 2.22 0.03 CUCULIFORMES Cuculidae Guira guira 25 5.55 0.27 GRUIFORMES Aramidae Aramus guarauna 1 1.11 0.01 Rallidae 1 1.11 0.01 Pardirallus maculatus Pardirallus sanguinolentus 15 13.33 0.16 Porphyriops melanops 2 2.22 0.01 3 2.22 0.03 Fulica rufifrons Fulica armillata 6 2.22 0.06 Fulica leucoptera 4 4.44 0.04 APODIFORMES Trochilidae Chlorostilbon lucidus 8 3.33 0.08 Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Order, Family, Species Total individuals Presence (%) Mean abundance CHARADRIIFORMES Charadriidae 2 1.11 0.02 Vanellus chilensis* ** Recurvirostridae 2 1.11 0.02 Himantopus mexicanus Laridae Chroicocephalus maculipennis 29 5.55 0.32 Gelochelidon nilotica 1 1.11 0.01 SULIFORMES Phalacrocoracidae Phalacrocorax brasilianus 1 1.11 0.01 PELECANIFORMES Ardeidae Ardea alba 2 2.22 0.02 1 1.11 0.01 Egretta thula ACCIPITRIFORMES Accipitridae 1 1.11 0.01 Elanus leucurus Rostrhamus sociabilis 21 14.44 0.23 Circus buffoni 5 3.33 0.05 1 1.11 0.01 Rupornis magnirostris PICIFORMES Picidae 1 1.11 0.01 Colaptes melanochloros Colaptes campestris 2 2.22 0.02 FALCONIFORMES Falconidae Caracara plancus 24 16.66 0.26 Milvago chimango 27 24.44 0.3 PSITTACIFORMES Psittacidae Myiopsitta monachus 62 18.88 0.68 PASSERIFORMES Furnariidae Furnarius rufus 32 25.55 0.35 Phleocryptes melanops 90 37.77 1 2 2.22 0.02 Leptasthenura platensis Phacellodomus striaticollis 23 2.22 0.25 Anumbius annumbi 25 21.11 0.31 35 24.44 0.38 Limnoctites sulphuriferus Synallaxis albescens 3 1.11 0.03 Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Order, Family, Species Total individuals Presence (%) Mean abundance Tyrannidae Serpophaga nigricans 8 7.77 0.08 1 1.11 0.01 Serpophaga subcristata Pseudocolopteryx flaviventris 61 38.88 0.67 Tachuris rubrigastra 8 5.55 0.08 14 10 0.15 Pyrocephalus rubinus Hymenops perspicillatus 144 74.44 1.6 Satrapa icterophrys 7 6.66 0.07 2 2.22 0.02 Machetornis rixosa Pitangus sulphuratus 57 35.55 0.63 Tyrannus melancholicus 17 13.33 0.18 64 37.77 0.71 Tyrannus savana Hirundinidae Progne tapera 9 6.66 0.1 3 3.33 0.03 Progne chalybea Tachycineta leucorrhoa 24 20 0.26 Hirundo rustica 128 28.88 1.42 Troglodytidae Troglodytes aedon 25 22.22 0.27 Cistothorus platensis 1 1.11 0.01 Polioptilidae Polioptila dumicola 5 4.44 0.05 Turdidae 5 5.55 0.05 Turdus rufiventris Mimidae Mimus saturninus 14 10 0.15 Motacillidae 3 3.33 0.03 Anthus correndera* ** Fringillidae Spinus magellanicus 9 6.66 0.1 Passerellidae Zonotrichia capensis* 378 96.66 4.2 Icteridae 1 1.11 0.01 Leistes superciliaris* ** Molothrus bonariensis 219 73.33 2.43 Amblyramphus holosericeus 19 12.22 0.21 58 16.66 0.64 Agelaioides badius Agelasticus thilius 152 56.66 1.68 Pseudoleistes virescens 222 72.22 2.46 Thraupidae Sicalis flaveola 28 15.55 0.31 526 85.55 5.84 Sicalis luteola* ** 8 5.55 0.08 Sporophila caerulescens Revista Brasileira de Ornitologia 27(4): 2019 Ground nesting birds in roadsides of Argentine Pampas Depalma & Mermoz Order, Family, Species Total individuals Presence (%) Mean abundance 111 65.55 1.23 Embernagra platensis* ** 64 45.55 0.71 Poospiza nigrorufa Donacospiza albifrons* 6 5.55 0.06 Paroaria coronata 1 1.11 0.01 5 3.33 0.05 Pipraeidea bonariensis Revista Brasileira de Ornitologia 27(4): 2019

Journal

Ornithology Research – Springer Journals

Published: Dec 1, 2019

Keywords: corridors; field margins; grassland birds; habitat remnants; survival analysis

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