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Background: Modern biologging technologies allow researchers to gain a better understanding of animal movements, offering opportunities to measure survival and remotely study the breeding success of wild birds, i.e., by locating nests. This is particularly useful for species whose nests are difficult to find or access, or when disturbances can impact the breeding outcome. We developed and validated, with field data, a framework to detect nesting events by two sandgrouse species, the black-bellied (Pterocles orientalis) and pin-tailed sandgrouse (Pterocles alchata), using GPS and Overall Dynamic Body Acceleration (ODBA) data. Sandgrouses are ground-nesting, cryptic, and elusive birds with biparental incubation efforts. Because both sexes take turns to incubate, a novel framework considering when tagged individuals are on incubation duty or not needs to be designed to detect nests. Results: We tagged 52 birds with high-resolution GPS devices to monitor their breeding during 2021–24. Using remote tracking and field data from the first 2 years (2021–22), we first determined sex-specific time windows for incubation to maximise differentiation between incubation and non-incubation behaviours. We then used a threshold-based classification to identify incubation days and inferred the minimum number of successive incubation days needed to correctly identify a nesting event. We show how ODBA and GPS data can be used to successfully detect nests incubated for only 2 or 3 days. GPS-only data or combined GPS-ODBA data had a success rate of around 95%, whereas ODBA-only data had a success rate of 100%. Cross-validation using data from 2023 to 2024 confirmed the model's performance, showing an overall success > 90% for GPS-only and ODBA-only data and of 85% for combined GPS–ODBA data. Conclusions: By accurately identifying nesting events, our framework offers new opportunities to study the breeding of conservation-dependent species. Besides its applicability to ground-nesting species with biparental care and sex-specific incubation schedules, the framework can be adapted to other bird species sensitive to disturbances or with inaccessible nesting sites. By doing so, it reduces the need for nest visits and associated disturbances, as well as the carbon footprint and expenses associated with fieldwork. [ABSTRACT FROM AUTHOR]

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Habitat selection is an inherently scale-sensitive process in which detected selection patterns frequently depend on the scale of analysis employed. We used a multi-scale modelling approach to identify how the distributions of two sympatric birds are shaped by differential selection at the landscape, land use and microhabitat scales and by human infrastructures as possible sources of disturbance. We studied two threatened steppe birds, the pin-tailed sandgrouse (PTS) and black-bellied sandgrouse (BBS) in central Spain. Land use gradients explained most of the variation in PTS and BBS occurrence, but there was cross-scale interdependence between the lower (microhabitat) and upper (landscape) spatial scales for the PTS. Synergies between the three scales highlighted the importance of integrating habitat scales in a single modelling framework. The process of habitat selection was also modulated by human disturbance. Both species selected ploughs of large size distant from houses, tracks and other infrastructures, although BBS exhibited broader habitat tolerance than the PTS, and was more sensitive to human disturbance. At microhabitat scale, PTS selected ploughs with greater green vegetation cover and insect abundance and fallows with lower dry vegetation cover and height but greater stone cover. This might reflect a trade-off between camouflage (vegetation and stone cover for concealment) and visibility for predator detection and escape. Ploughs and fallows should be maintained by means of traditional 2-year rotations and low management during the breeding season. Ongoing urbanization trends and infrastructure development inside protected areas should be limited. Multi-scale models were key to identify scale-specific factors that determine sandgrouse habitat preferences and conservation requirements at appropriate levels, and are recommended to better guide regional and local conservation efforts of threatened species. [ABSTRACT FROM AUTHOR]

Predictive species' distribution models may answer ecological questions about habitat selection, co-occurrence of species and competition between them. We studied the habitat preferences and segregation of two sympatric species of declining sandgrouse, the black-bellied sandgrouse ( Pterocles orientalis) and the pin-tailed sandgrouse ( Pterocles alchata), during the breeding season. We developed predictive models that related sandgrouse presence to environmental variables at three different spatial levels: large geographical, landscape and microhabitat scales. At the large geographical scale, differences between sandgrouse distributions, in the Iberian Peninsula, seem to be explained mainly in terms of bioclimatology: pin-tailed sandgrouse appear to be a more thermophilous species and occupy warmer sites usually located in flatter areas. At the landscape spatial level, in those areas that exhibit environmental conditions allowing for both species' co-existence at a large geographical scale, black-bellied sandgrouse appear to be more tolerant to environmental variation than pin-tailed sandgrouse. At the microhabitat level, however, differences between species could be related to different flocking behaviour as a consequence of different sensitivities to vegetation structure and predators. Thus, the observed spatial distribution patterns are the result of different ecological factors that operate at different spatial levels. Conservation guidelines for these species should therefore consider their habitat preferences at large geographical, landscape and microhabitat scales. [ABSTRACT FROM AUTHOR]

Knowledge of the factors determining species distributions is essential for developing conservation strategies. Sandgrouse Pterocles alchata and P. orientalis are threatened in Spain, the stronghold of European populations. Spatial modelling was used to: (1) assess the relative importance of abiotic, anthropogenic and geographical factors in the distribution of both sandgrouse species, (2) determine the most important anthropogenic predictors for each species occurrence, and (3) identify areas where conservation efforts should be prioritized. Abiotic and anthropogenic factors explained most of the variation in sandgrouse distributions. Both species were associated with arid flatlands, arable land cover being the most important anthropogenic variable determining their distribution. The Common Agricultural Policy (CAP) is the main driver of agricultural management in Europe, and may thus have a direct effect on sandgrouse distributions. P. orientalis exhibited broader habitat tolerance than P. alchata; the latter species tolerates warmer climates. Consequently, the network of core and marginally suitable areas identified for each species differs, and connectivity between the populations of these areas seems unlikely. Potential future changes in sandgrouse distribution will probably be directed principally by the synergistic effects of climate change and expected land-use transformations resulting from the new CAP and ongoing population growth, urbanization and infrastructure development. [ABSTRACT FROM PUBLISHER]