Integrating demographic data: towards a framework for monitoring wildlife populations at large spatial scales

Abstract

Summary1. Landscapes are becoming increasingly intensively managed resulting in greater anthropogenic disturbance of ecosystems. Effective policies for conservation and management of wildlife populations will require a mechanistic understanding of the processes underlying the population responses to these changes. Detailed demographic studies are often of individual populations in relatively stable habitats, whereas there is a need to characterize demographic variation at larger scales in wider landscapes that are subject to environmental change. 2. We use long-term (18-46 years) data sets, gathered by volunteers across Britain, to parameterize Bayesian state-space demographic population models for 17 widely occurring bird species. As some demographic processes were not quantified directly, we introduce a scaling parameter (q) to account for this unmeasured variation, and assess the extent to which this influences our ability to understand the processes driving population change.3. The population models provided a good fit to the population trajectory in all but one species (the nocturnal tawny owl Strix aluco). The scaling parameter generally showed little annual variation and did not make a major contribution (<12%) to population change among passerine species. For five non-passerine species, the contribution was still not large (11-21%), but did indicate the importance of unmeasured demographic variables in these species. 4. We were able to retrieve known demographic signals both within and across species. The importance of the nest failure rates was greater for species that construct nests in open rather than cavity situations. We also confirmed the demographic causes of population decline in two species of conservation concern, song thrush and lapwing, as changes in juvenile survival and reproductive success respectively. Furthermore, we show that population dynamics of declining species are generally driven more by recruitment than increasing species (for which variation in adult survival is more important).5. These analyses demonstrate that volunteer-based monitoring programmes can provide insight into population changes at large spatial scales across a range of species. By facilitating the combination of data sets on different demographic parameters, the integrated approach adopted here allows important demographic parameters to be identified, even if they are not measured directly.

Persistent impacts of West Nile virus on North American bird populations

“…Important to note is that in short-lived bird species that breed in their first year (typical of the species we examined), adult survival is often the largest demographic component of population growth (32,33) and can have a direct influence on the following year's growth rate (34). Thus, a decline in survival of 0.3 can result in a decline in the growth rate of the population of 0.3.…”

“…18) had larger decreases in survival, we compared the average WNV risk score and the estimated WNV effect on survival (Table S3) across all 49 taxa, corrected for phylogenetic signal within residuals. We used the package caper (39) within the R framework (33) to estimate the values of λ, κ, and δ individually (using the maximum-likelihood criteria, "ML"), and then used these values as input in a phylogenetic generalized linear model (pgls with caper).…”

Demographic drivers of decline and recovery in an Afro-Palaearctic migratory bird population

“…For each region, we modelled annual population growth rates ( λ t = N t / N t −1 ) as a function of survival and recruitment using the IPM framework of [2], and count and demographic data collected in UK-wide surveys from 1994 to 2012; the period spanning the recent regional divergence in population trends (details below). Below we outline the modelling process, with full details and R code provided in the electronic supplementary material.…”

“…IPMs simultaneously estimate trajectories of population size and demographic parameters by combining time-series of population abundance and key demographic rates, such as survival, fecundity or dispersal [27]. IPMs can also incorporate the influence of unmeasured demographic processes into population models, allowing their influence on population change to be explored [2,28,29]. …”

An 18-Year Mark–Recapture Study of Wood Turtles (Glyptemys insculpta) in Michigan

“…Our estimate should be interpreted as the product of fecundity and juvenile and adult survival up until first capture. Nevertheless, it represents the only missing vital rate in our balance equation, and provided survival and population estimates are unbiased, our estimate of recruitment properly captures the unmeasured vital rates of the population (Robinson et al, 2014).…”