The role of detectability on bird population trend estimates in an open farmland landscape

Sanz‐Pérez, Ana; Sollmann, Rahel; Sardà‐Palomera, Francesc; Bota, Gérard; Giralt, David

doi:10.1007/s10531-020-01948-0

Cited by 22 publications

(14 citation statements)

References 52 publications

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“…It is important that changes in observers be integrated into most monitoring programmes in order to be incorporated into models able to estimate a probability of detection. Taking into account the differences between observers in the detection of individuals makes it possible to better identify variability sources and assess population trends and the environmental factors that impact them more accurately, in order to correctly design species-specific conservation actions [ 13 , 25 ].…”

Section: Discussionmentioning

confidence: 99%

“…Sources of error such as imperfect detection [ 2 , 3 ], biased abilities to count animals that are detected [ 4 – 7 ], and misidentification of species [ 8 , 9 ] can introduce considerable estimation bias [ 10 ] and reduce the survey’s power to detect trends [ 6 , 11 – 13 ]. Counts may provide reliable information about population trends if detection probability remains constant over time [ 5 , 14 ], yet such a situation is rarely met in practice [ 13 ]. Observers in long-term surveys often change annually or gain experience through time [ 15 ], both of which affect detection [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

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Accounting for detection probability with overestimation by integrating double monitoring programs over 40 years

et al. 2022

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In the context of wildlife population declines, increasing computer power over the last 20 years allowed wildlife managers to apply advanced statistical techniques that has improved population size estimates. However, respecting the assumptions of the models that consider the probability of detection, such as N-mixture models, requires the implementation of a rigorous monitoring protocol with several replicate survey occasions and no double counting that are hardly adaptable to field conditions. When the logistical, economic and ecological constraints are too strong to meet model assumptions, it may be possible to combine data from independent surveys into the modelling framework in order to understand population dynamics more reliably. Here, we present a state-space model with an error process modelled on the log scale to evaluate wintering waterfowl numbers in the Camargue, southern France, while taking a conditional probability of detection into consideration. Conditional probability of detection corresponds to estimation of a detection probability index, which is not a true probability of detection, but rather conditional on the difference to a particular baseline. The large number of sites (wetlands within the Camargue delta) and years monitored (44) provide significant information to combine both terrestrial and aerial surveys (which constituted spatially and temporally replicated counts) to estimate a conditional probability of detection, while accounting for false-positive counting errors and changes in observers over the study period. The model estimates abundance indices of wintering Common Teal, Mallard and Common Coot, all species abundant in the area. We found that raw counts were underestimated compared to the predicted population size. The model-based data integration approach as described here seems like a promising solution that takes advantage of as much as possible of the data collected from several methods when the logistic constraints do not allow the implementation of a permanent monitoring and analysis protocol that takes into account the detectability of individuals.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accounting for detection probability with overestimation by integrating double monitoring programs over 40 years

et al. 2022

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“…The detection probability of the breeding females is limited due to the concealing behavior (Magaña et al 2010). Therefore, in order to avoid a distortion (Sanz-Pérez et al 2020), the results of the censuses after April 30 th , when the majority of the females in our area are already incubating (Faragó 1983, Petrik 1996, were not taken into account. Despite the relatively small size of the study area, during the active spring period of the females, the whole area cannot be patrolled in such a way that double counting of individuals can be definitely excluded due to visual obstacles, thus the censuses of females were performed only in the 'bustard counting area' (Figure 1).…”

Section: Methodsmentioning

confidence: 99%

Impact of agriculture irrigation on the habitat structure and use by Great Bustards (Otis tarda) in a Natura 2000 site

Spakovszky

Raab

2020

Ornis Hungarica

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As the whole Palearctic steppe system, its iconic bird, the Great Bustard has also suffered from the expansion of intensive agriculture. The species now typically has stable or growing populations only in protected areas, but negative processes are still prevalent even there. In this study, we present a recent change in a part of the Natura 2000 site designated for the isolated West Pannonian population. In recent years, a total of 2.3 km Center-pivot and laterally moving linear irrigation systems have been built and 4.7 km of underground pipelines have been laid, with which more than 52% of the 1245,5 ha study area was irrigated by 2020. In comparison to 2009, when the study period has started, the sown area of autumn cereals, one of the main breeding habitats, was roughly halved and the proportion of crops unsuitable for breeding was increased. New crops requiring irrigation have emerged with a rate of 30.6% in the last year. Despite the available support, the area of alfalfa, which is the most significant breeding habitat, and is grown almost exclusively in the agri-environmental scheme, has decreased. As a result of habitat degradation, the number of Great Bustard females observed in the area in spring decreased to a small fraction of the beginning. Irrigation farming is expected to increase, as a response to the climate change, but in order to save agro-steppe habitats and their species, the adverse effects of agricultural intensification need to be urgently addressed at both local and European levels.

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“…However, wildlife counts only provide estimates and not actual population size, because of various sources of errors such as imperfect detection (Dénes et al., 2015), imperfect abilities to count animals that are detected (Seber, 2002; Thompson, 2002; Williams et al., 2002), misidentification of species or nonexhaustive geographical coverage. When unaccounted for, these errors can introduce considerable estimation bias and obscure important ecological patterns (Wenger & Freeman, 2008), which can reduce the power to detect trends and accuracy of any trends that are detected (Sanz‐Pérez et al., 2020). Integration of systematic sources of count errors into population models can help.…”

Section: Introductionmentioning

confidence: 99%

Reliability of animal counts and implications for the interpretation of trends

Vallecillo

Gauthier‐Clerc

Guillemain

et al. 2021

Ecology and Evolution

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Population time series analysis is an integral part of conservation biology in the current context of global changes. To quantify changes in population size, wildlife counts only provide estimates because of various sources of error. When unaccounted for, such errors can obscure important ecological patterns and reduce confidence in the derived trend. In the case of highly gregarious species, which are common in the animal kingdom, the estimation of group size is an important potential bias, which is characterized by high variance among observers. In this context, it is crucial to quantify the impact of observer changes, inherent to population monitoring, on i) the minimum length of population time series required to detect significant trends and ii) the accuracy (bias and precision) of the trend estimate. We acquired group size estimation error data by an experimental protocol where 24 experienced observers conducted counting simulation tests on group sizes. We used this empirical data to simulate observations over 25 years of a declining population distributed over 100 sites. Five scenarios of changes in observer identity over time and sites were tested for each of three simulated trends (true population size evolving according to deterministic models parameterized with declines of 1.1%, 3.9% or 7.4% per year that justify respectively a “declining,” “vulnerable” or “endangered” population under IUCN criteria). We found that under realistic field conditions observers detected the accurate value of the population trend in only 1.3% of the cases. Our results also show that trend estimates are similar if many observers are spatially distributed among the different sites, or if one single observer counts all sites. However, successive changes in observer identity over time lead to a clear decrease in the ability to reliably estimate a given population trend, and an increase in the number of years of monitoring required to adequately detect the trend. Minimizing temporal changes of observers improve the quality of count data and help taking appropriate management decisions and setting conservation priorities. The same occurs when increasing the number of observers spread over 100 sites. If the population surveyed is composed of few sites, then it is preferable to perform the survey by one observer. In this context, it is important to reconsider how we use estimated population trend values and potentially to scale our decisions according to the direction and duration of estimated trends, instead of setting too precise threshold values before action.

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The role of detectability on bird population trend estimates in an open farmland landscape

Cited by 22 publications

References 52 publications

Accounting for detection probability with overestimation by integrating double monitoring programs over 40 years

Accounting for detection probability with overestimation by integrating double monitoring programs over 40 years

Impact of agriculture irrigation on the habitat structure and use by Great Bustards (Otis tarda) in a Natura 2000 site

Reliability of animal counts and implications for the interpretation of trends

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