Foundations of bird surveys and implications for the collection and analysis of data in large-scale monitoring programs

Großräumige Monitoringprogramme stellen eine zweistufige Stichprobe dar: Zuerst wird eine räumliche Stichprobe ausgewählt und danach eine Stichprobe an beobachteten Individuen, besetzten Flächen oder Arten. Damit die in Monitoringprogrammen gewonnenen Zahlen interpretierbar bleiben, muss die räumliche Stichprobe „definiert zufällig“ erfolgen, ansonsten können Verfälschungen auftreten. Außerdem muss beachtet werden, dass Zählungen und Vorkommensbeobachtungen („Präsenz-Absenz-Daten“) binomiale Zufallsgrößen sind, ganz analog zum Wurf einer Münze. Die Binomialverteiltung stellt sozusagen das „Grundgesetz der Bestandserhebung“ dar und besagt, dass Zählungen (Z) erstens auch unter identischen Bedingungen automatisch streuen, und dass sie zweitens im Durchschnitt einem Anteil p der vorhandenen Bestände N entsprechen, wobei p die Antreffwahrscheinlichkeit darstellt. Drittens beinhaltet ein Vergleich zwischen zwei oder mehr Zählungen immer gleichzeitig einen Vergleich der Bestände N und der Antreffwahrscheinlichkeit p. Das bedeutet, dass ein Zeittrend in Zählungen zustande kommen kann durch einen realen Bestandstrend, durch einen Trend in der Antreffwahrscheinlichkeit oder durch eine Kombination von beidem. Eine direkte Interpretation von Zählungen impliziert immer die Annahme, dass p = 1 oder dass p konstant sei. Es ist nützlich, sich die Entstehung von Vogelzählungen hierarchisch, d. H. mehrstufig vorzustellen: In einem ersten Schritt entstehen die wahren Bestände und im zweiten die Zählungen in Abhängigkeit der Bestände und der Antreffwahrscheinlichkeit p. Extrainformation ist nötig, um die wahren Bestände korrigiert für p zu schätzen. Diese Extrainformation besteht in der Regel aus Distanzinformation oder aus wiederholten Beobachtungen, woraus Distance-Sampling- und Fangwiederfang- Methoden die echten Bestände oder das wahre Vorkommen zu schätzen vermögen. In den vergangenen Jahren haben wir im Schweizer Brutvogelmonitoringprogramm MHB mehrere Analyseverfahren vom Fangwiederfang-Typ getestet und stellen diese und unsere Befunde zusammenfassend kurz vor. Diese Methoden korrigieren für den binomialen „Beobachtungsfehler“, der allen Vogelzählungen und Vorkommensbeobachtungen inhärent ist. Wir glauben, dass man an Methoden wie den hier illustrierten eigentlich nicht vorbei kommt, wenn bei Monitoringprogrammen absolute Bestandsgrößen vonnöten sind oder wenn man für „gefährliche Muster“ in der Antreffwahrscheinlichkeit, z. B. Zeittrends in p, korrigieren möchte.Large-scale monitoring programs represent a two-level, nested sampling scheme: first, a spatial sample of quadrats or other study sites is selected, within which a second sample, of individuals, occupied quadrats or species, is chosen. To produce meaningful numbers, a monitoring program ought to be based on a spatial probability sample, otherwise the inferences obtained may be biased with respect to the desired statistical population about which one wants to learn something. Moreover, all bird counts and detection-nondetection records (misleadingly also called “presence-absence data”) are binomial random variables, much like the flip of a coin. The binomial distribution is the theoretical basis of all animal or plant surveys and explains and predicts all of their most salient features: 1. repeated counts C vary automatically, even under identical conditions; 2. on average, a count amounts to a proportion p of true population size N , where p is the detection probability, and 3. any comparison between two or more counts represents the simultaneous comparison of the associated true population size N and of the detection probability p. For instance, a temporal trend in counts may be due to a genuine trend in the underlying population size or to a trend in detection probability or to a combination of the two. Any direct interpretation of counts always implies one of two assumptions, either that of p = 1 or that of p < 1 constant. It is useful to think about the genesis of bird counts in a hierarchical way. In a first random process, the true population sizes are generated. In a second random process, the actual counts are generated conditional on these true population sizes and on detection probability. For inference about the underlying true population size free from distorting effects of the observation process, extra information is required, which usually comes as distance information or as repeated observation of a system within a period of closure. Then, distance sampling and capturerecapture methods can be used to estimate true population size or true distributions, corrected for imperfect detection. During the past few years, we have used data from the Swiss breeding bird survey MHB to experiment with, adapt and develop several such methods of the capture-recapture type. Here, we review these briefly, describe some of our key findings and provide pointers to more specific work. These methods correct counts and detection-nondetection data for the binomial observation error inherent in all bird observations. We believe that use of these methods is hard to avoid in a monitoring program if absolute population size or the absolute extent of distributional ranges, corrected for imperfect detection, are required, or if one needs to correct for “dangerous patterns” in detection probability, for instance time trends in p

Positive effects of cyanogenic glycosides in food plants on larval development of the common blue butterfly

Cyanogenesis is a widespread chemical defence mechanism in plants against herbivory. However, some specialised herbivores overcome this protection by different behavioural or metabolic mechanisms. In the present study, we investigated the effect of presence or absence of cyanogenic glycosides in birdsfoot trefoil (Lotus corniculatus, Fabaceae) on oviposition behaviour, larval preference, larval development, adult weight and nectar preference of the common blue butterfly (Polyommatus icarus, Lycaenidae). For oviposition behaviour there was a female-specific reaction to cyanogenic glycoside content; i.e. some females preferred to oviposit on cyanogenic over acyanogenic plants, while other females behaved in the opposite way. Freshly hatched larvae did not discriminate between the two plant morphs. Since the two plant morphs differed not only in their content of cyanogenic glycoside, but also in N and water content, we expected these differences to affect larval growth. Contrary to our expectations, larvae feeding on cyanogenic plants showed a faster development and stronger weight gain than larvae feeding on acyanogenic plants. Furthermore, female genotype affected development time, larval and pupal weight of the common blue butterfly. However, most effects detected in the larval phase disappeared for adult weight, indicating compensatory feeding of larvae. Adult butterflies reared on the two cyanogenic glycoside plant morphs did not differ in their nectar preference. But a gender-specific effect was found, where females preferred amino acid-rich nectar while males did not discriminate between the two nectar mimics. The presented results indicate that larvae of the common blue butterfly can metabolise the surplus of N in cyanogenic plants for growth. Additionally, the female-specific behaviour to oviposit preferably on cyanogenic or acyanogenic plant morphs and the female-genotype-specific responses in life history traits indicate the genetic flexibility of this butterfly species and its potential for local adaptatio

spOccupancy: An R package for single-species, multi-species, and integrated spatial occupancy models

Occupancy modeling is a common approach to assess spatial and temporal species distribution patterns, while explicitly accounting for measurement errors common in detection-nondetection data. Numerous extensions of the basic single species occupancy model exist to address dynamics, multiple species or states, interactions, false positive errors, autocorrelation, and to integrate multiple data sources. However, development of specialized and computationally efficient software to fit spatial models to large data sets is scarce or absent. We introduce the spOccupancy R package designed to fit single-species, multi-species, and integrated spatially-explicit occupancy models. Using a Bayesian framework, we leverage P\'olya-Gamma data augmentation and Nearest Neighbor Gaussian Processes to ensure models are computationally efficient for potentially massive data sets. spOccupancy provides user-friendly functions for data simulation, model fitting, model validation (by posterior predictive checks), model comparison (using information criteria and k-fold cross-validation), and out-of-sample prediction. We illustrate the package's functionality via a vignette, simulated data analysis, and two bird case studies, in which we estimate occurrence of the Black-throated Green Warbler (Setophaga virens) across the eastern USA and species richness of a foliage-gleaning bird community in the Hubbard Brook Experimental Forest in New Hampshire, USA. The spOccupancy package provides a user-friendly approach to fit a variety of single and multi-species occupancy models, making it straightforward to address detection biases and spatial autocorrelation in species distribution models even for large data sets.Comment: 20 pages, 2 figure

spAbundance: An R package for single-species and multi-species spatially-explicit abundance models

Numerous modeling techniques exist to estimate abundance of plant and wildlife species. These methods seek to estimate abundance while accounting for multiple complexities found in ecological data, such as observational biases, spatial autocorrelation, and species correlations. There is, however, a lack of user-friendly and computationally efficient software to implement the various models, particularly for large data sets. We developed the spAbundance R package for fitting spatially-explicit Bayesian single-species and multi-species hierarchical distance sampling models, N-mixture models, and generalized linear mixed models. The models within the package can account for spatial autocorrelation using Nearest Neighbor Gaussian Processes and accommodate species correlations in multi-species models using a latent factor approach, which enables model fitting for data sets with large numbers of sites and/or species. We provide three vignettes and three case studies that highlight spAbundance functionality. We used spatially-explicit multi-species distance sampling models to estimate density of 16 bird species in Florida, USA, an N-mixture model to estimate Black-throated Blue Warbler (Setophaga caerulescens) abundance in New Hampshire, USA, and a spatial linear mixed model to estimate forest aboveground biomass across the continental USA. spAbundance provides a user-friendly, formula-based interface to fit a variety of univariate and multivariate spatially-explicit abundance models. The package serves as a useful tool for ecologists and conservation practitioners to generate improved inference and predictions on the spatial drivers of populations and communities

The demographic drivers of local population dynamics in two rare migratory birds

The exchange of individuals among populations can have strong effects on the dynamics and persistence of a given population. Yet, estimation of immigration rates remains one of the greatest challenges for animal demographers. Little empirical knowledge exists about the effects of immigration on population dynamics. New integrated population models fitted using Bayesian methods enable simultaneous estimation of fecundity, survival and immigration, as well as the growth rate of a population of interest. We applied this novel analytical framework to the demography of two populations of long-distance migratory birds, hoopoe Upupa epops and wryneck Jynx torquilla, in a study area in south-western Switzerland. During 2002-2010, the hoopoe population increased annually by 11%, while the wryneck population remained fairly stable. Apparent juvenile and adult survival probability was nearly identical in both species, but fecundity and immigration were slightly higher in the hoopoe. Hoopoe population growth rate was strongly correlated with juvenile survival, fecundity and immigration, while that of wrynecks strongly correlated only with immigration. This indicates that demographic components impacting the arrival of new individuals into the populations were more important for their dynamics than demographic components affecting the loss of individuals. The finding that immigration plays a crucial role in the population growth rates of these two rare species emphasizes the need for a broad rather than local perspective for population studies, and the development of wide-scale conservation action

Lessons to be learned by comparing integrated fisheries stock assessment models (SAMs) with integrated population models (IPMs)

AEP was partially funded by the Cooperative Institute for Climate, Ocean, & Ecosystem Studies (CICOES) under NOAA Cooperative Agreement NA15OAR4320063, Contribution No. 2023-1331.Integrated fisheries stock assessment models (SAMs) and integrated population models (IPMs) are used in biological and ecological systems to estimate abundance and demographic rates. The approaches are fundamentally very similar, but historically have been considered as separate endeavors, resulting in a loss of shared vision, practice and progress. We review the two approaches to identify similarities and differences, with a view to identifying key lessons that would benefit more generally the overarching topic of population ecology. We present a case study for each of SAM (snapper from the west coast of New Zealand) and IPM (woodchat shrikes from Germany) to highlight differences and similarities. The key differences between SAMs and IPMs appear to be the objectives and parameter estimates required to meet these objectives, the size and spatial scale of the populations, and the differing availability of various types of data. In addition, up to now, typical SAMs have been applied in aquatic habitats, while most IPMs stem from terrestrial habitats. SAMs generally aim to assess the level of sustainable exploitation of fish populations, so absolute abundance or biomass must be estimated, although some estimate only relative trends. Relative abundance is often sufficient to understand population dynamics and inform conservation actions, which is the main objective of IPMs. IPMs are often applied to small populations of conservation concern, where demographic uncertainty can be important, which is more conveniently implemented using Bayesian approaches. IPMs are typically applied at small to moderate spatial scales (1 to 104 km2), with the possibility of collecting detailed longitudinal individual data, whereas SAMs are typically applied to large, economically valuable fish stocks at very large spatial scales (104 to 106 km2) with limited possibility of collecting detailed individual data. There is a sense in which a SAM is more data- (or information-) hungry than an IPM because of its goal to estimate absolute biomass or abundance, and data at the individual level to inform demographic rates are more difficult to obtain in the (often marine) systems where most SAMs are applied. SAMs therefore require more 'tuning' or assumptions than IPMs, where the 'data speak for themselves', and consequently techniques such as data weighting and model evaluation are more nuanced for SAMs than for IPMs. SAMs would benefit from being fit to more disaggregated data to quantify spatial and individual variation and allow richer inference on demographic processes. IPMs would benefit from more attempts to estimate absolute abundance, for example by using unconditional models for capture-recapture data.Publisher PDFPeer reviewe

Full-annual demography and seasonal cycles in a resident vertebrate

Wildlife demography is typically studied at a single point in time within a year when species, often during the reproductive season, are more active and therefore easier to find. However, this provides only a low-resolution glimpse into demographic temporal patterns over time and may hamper a more complete understanding of the population dynamics of a species over the full annual cycle. The full annual cycle is often influenced by environmental seasonality, which induces a cyclic behavior in many species. However, cycles have rarely been explicitly included in models for demographic parameters, and most information on full annual cycle demography is restricted to migratory species. Here we used a high-resolution capture-recapture study of a resident tropical lizard to assess the full intra-annual demography and within-year periodicity in survival, temporary emigration and recapture probabilities. We found important variation over the annual cycle and up to 92% of the total monthly variation explained by cycles. Fine-scale demographic studies and assessments on the importance of cycles within parameters may be a powerful way to achieve a better understanding of population persistence over time

Life-cycle analysis of an endangered migratory goose to assess the impact ofconservation actions on population recovery

Evaluating the effectiveness of conservation actions is challenging for migratory species because a population can be impacted anywhere along its route. Conservation actions for the critically endangered Fennoscandian lesser white-fronted goose population include culling of red foxes in the breeding area and habitat improvements and reduction of illegal hunting in the non-breeding areas. One goal of the predator control strategy is to prevent adult birds from using an autumn migration route through western Asia, where mortality is believed to be higher than on the migration route through eastern Europe. We used 23 years of count data obtained at different staging areas to parameterize a seasonal state-space model describing the full-annual cycle dynamics of this population and evaluate whether the recent population recovery was linked to these conservation efforts. The results did not provide evidence that predator control influenced population recovery, as survival on the European route did not appear higher than on the allegedly riskier Asian route. However, adult survival at staging areas on both routes and at wintering sites may have improved in the last decade, suggesting a positive effect of the other conser- vation initiatives. These results emphasize the importance of including the non-breeding dynamics in population assessments of migratory species and highlight the challenge of evaluating the efficacy of separate conservation actions when a proper experimental design is unfeasible. Our study, which is a unique case of cross-national, coordinated conservation efforts, exemplifies how to model complex population dynamics to assess the influ- ence of costly conservation initiatives. Goose management State-space model Management evaluation Lesser whitefronted goose Unmarked individuals Non-breeding dynamic

Effect of Recreational Trails on Forest Birds: Human Presence Matters

Outdoor recreational activities are increasing worldwide and occur at high frequency especially close to cities. Forests are a natural environment often used for such activities as jogging, hiking, dog walking, mountain biking, or horse riding. The mere presence of people in forests can disturb wildlife, which may perceive humans as potential predators. Many of these activities rely on trails, which intersect an otherwise contiguous habitat and hence impact wildlife habitat. The aim of this study was to separate the effect of the change in vegetation and habitat structure through trails, from the effect of human presence using these trails, on forest bird communities. Therefore we compared the effects of recreational trails on birds in two forests frequently used by recreationists with that in two rarely visited forests. In each forest, we conducted paired point counts to investigate the differences between the avian community close (50 m) and far (120 m) from trails, while accounting for possible habitat differences, and, for imperfect detection, by applying a multi-species N-mixture model. We found that in the disturbed (i.e., high-recreation-level forests) the density of birds and species richness were both reduced at points close to trails when compared to points further away (−13 and −4% respectively), whereas such an effect was not statistically discernible in the forests with a low-recreation-level. Additionally we found indications that the effects of human presence varied depending on the traits of the species. These findings imply that the mere presence of humans can negatively affect the forest bird community along trails. Visitor guidance is an effective conservation measure to reduce the negative impacts of recreationists. In addition, prevention of trail construction in undeveloped natural habitats would reduce human access, and thus disturbance, most efficiently

Survival rates in the world's southernmost forest bird community

Article asserts that the Magellanic sub-Antarctic Forest is home to the world's southernmost avian community and is the only Southern Hemisphere analogue to Northern Hemisphere temperate forests at this latitude. Authors describe annual survival patterns and their association with climate variables using a 20-year mark–recapture data set of five forest bird species in the Cape Horn Biosphere Reserve