Livestock grazing is an important management tool of agri-environment schemes initiated within the European Union to maintain and restore biodiversity of grassland birds. However, grazing can affect bird populations negatively by depressing reproduction through nest trampling and increasing nest predation. These effects are, however, considered low when using recommended stocking rates. By simulating wader nests, we experimentally quantify and examine the causes of variation in trampling rates on managed Baltic coastal meadows. Secondly, we examine whether livestock presence increases nest predation of one management target, the critically endangered southern dunlin (Calidris alpina schinzii). Trampling rates of experimental nests were high. Only 21% of nests would have survived a three week incubating period early in the grazing season. Trampling rates were most severe at the onset of grazing and decreased with time. Thus, timing of grazing plays a crucial role in determining breeding success on managed meadows. Predation rates of dunlin nests were moderate and did not depend on livestock presence suggesting that incubating dunlin are not disturbed by cattle. While grazing is vital in habitat restoration and in conserving grassland biodiversity, our results suggest that grazing may also threaten the viability of populations if negative effects are underestimated. Therefore, management plans, especially for endangered species, should not only rely on general recommendations on stocking rates but instead planners need to evaluate the significance of negative effects in terms of local conditions (timing of breeding and grazing, space use of cattle and birds, measured trampling rates) and adjust grazing practises accordingly.
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A standard measurement unit that allows the aggregation of the various categories of livestock in order to enable them to be compared. Livestock units are defined on the basis of the feed requirements. They are not related to the number of feet, i.e. one dairy cow with a calf constitutes one unit of LSU.
Global positioning system
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We are grateful for Riku Halmeenpää, Juhani Karvonen, Antti Rönkä and Ville Suorsa for help in the field, and Petri Kärkkäinen and Matti Rauman for providing equipment. Robert L. Thomson, Laura Kvist, Antti Rönkä, Eduardo J. Belda and two anonymous referees made valuable comments on the manuscript. We thank Jorma Pessa (for providing altitude data), Sami Timonen, Johanna Helkimo and the cattle owners for co-operation in this study. This study was supported by the Finnish Cultural Foundation (VMP), the Kone Foundation (VMP), the Emil Aaltonen Foundation (VMP), the Tauno Tönning Foudation (VMP), the Finnish Environment Centre, the Academy of Finland (project 128384 KK) and the Thule Institute at the University of Oulu.
Examples of encounter histories used in the input files in MARK. First five entry points refer to k is the day the nest was found, l the last day the nest was checked alive, m the last day the nest was checked, information on the fate of the nest and the frequency of such nests (1 in all cases).
Modelling effect of nest size on survival from trampling
1 9 9 0 1 19.63 385.53;
Individual covariates: nest size in cm2, nest size2
Modelling survival from trampling for 8 cm diameter nests
1 1 9 1 1 1 0 0.2 443 1;
Individual covariates: 1st week, 2nd week, altitude (meters), distance to shore (meters), nest cover
Modelling nest survival from predation
24 40 40 0 1 1 0 1 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
Individual covariates: Site1, Site2, Year1, Year2, Year3, Year4, Year5, Year6, Initiation date, following 60 day specific covariates for age of the nest starting from the encounter occasion it was found and continuing to hatching. Site effect had two parameters because the small sites were pooled into the larger sites due to small sample size.
Modelling the effect of cattle’s presence on nest survival
9 9 20 1 1 0 1 1 0 0 0 0 0 12 0 0 0 0 0 0 0 0 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
Individual covariates: Same as in part 3 but the first two covariates differ. The first denotes the cattle effect. There were two larger sites with cattle, thus only one covariate for site effect was needed.
Modelling researcher effects on nest survival
24 40 40 0 1 1 0 1 0 0 0 0 0 21 −13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
Individual covariates: Same as in part 3 but age is modelled as a function of age at the first encounter occasion, i.e. 8th of May (−13 in the example) and the 60 day specific covariates denote whether or not an incubating bird was caught at that day or the previous day.
See Table 1.
Few studies report daily trampling rate estimates that can be compared between studies. Trampling rates are mostly reported as a proportion of nests trampled without any reference to exposure to cattle. Furthermore, stocking rates are rarely reported explicitly. For the above reasons many studies reporting trampling cannot be compared to our study. Table 2 includes studies that give stocking rates and DTR or sufficient information to calculate them.
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Pakanen, VM., Luukkonen, A. & Koivula, K. Nest predation and trampling as management risks in grazed coastal meadows. Biodivers Conserv 20, 2057–2073 (2011). https://doi.org/10.1007/s10531-011-0075-3
- Agri-environment scheme
- Coastal meadows
- Conservation management
- Ecological trap
- Livestock grazing