Optimal Annual Routines: New Tools for Conservation Biology

Abstract

Abstract. Many applied problems in ecology and conservation require prediction, and population models are important tools for that purpose. Formerly, the majority of predictive population models were based on matrix models. As the limitations of classical matrix models have become clearer, the use of individual-based models has increased. These models use behavioral rules imposed at the level of the individual to establish the emergent consequences of those rules at the population level. Individual behaviors in such models use an array of different rule types, from empirically derived probabilities to long-term fitness considerations. There has been surprisingly little discussion of the strengths and weaknesses of these different rule types. Here, we consider different strategies for modeling individual behaviors, together with some problems associated with individual-based models. We propose a novel approach based on modeling optimal annual routines. Annual routines allow individual behaviors to be predicted over a whole annual cycle within the context of long-term fitness considerations. Temporal trade-offs between different behaviors are automatically included in annual routine models, overcoming some of the primary limitations of other individual-based models. Furthermore, as well as population predictions, individual behaviors and indices of condition are emergent features of annual routine models. We show that these can be more sensitive to environmental change than population size, offering alternative, repeatable metrics for monitoring population status. Annual routine models provide no panacea for the problems of data limitations in predictive population modeling. However, as a result of their ability to deal with life-history trade-offs, as well as their potential for relatively rapid and accurate validation and parameterization, we suggest that annual routine models have strong potential for predictive population modeling in applied conservation settings.

Foraging theory upscaled: the behavioural ecology of herbivore movement

“…As yet few researchers have taken advantage of such opportunities. Fero et al (2008) reviewed the advantages of dynamic state-dependent models projecting optimal annual routines over the seasonal cycle as a class of behaviour-based models (see also ). This approach could be applied to seasonally varying habitat selection, taking into account various trade-offs and carry-over effects, subject to the limitations of the data available.…”

sOAR: a tool for modelling optimal animal life‐history strategies in cyclic environments

“…Such facets, the consequences of suboptimal behaviour or the development of new behavioural strategies, can be easily explored using sOAR. Also, individual variation can be explored within OAR frameworks and be compared to empirically observed movement data, for example by means of telemetry (Feró et al 2008). To illustrate usage and ease application, the software package sOAR includes descriptions and configurations for two illustrative examples as well as two examples from the literature (Fig.…”

“…Feró et al 2008) whereby additional sites and processes such as molt or explicit densitydependent effects (Barta et al 2008) or thermoregulation could be integrated into future versions of sOAR: 1) analysis of life-history under global change, 2) prediction of potential new adaptive behavioral strategies, 3) theoretical studies of carry-over effects at the population level, 4) analysis of phenotypic variation in a population within a life-history context, 5) studies of functional groups of organisms, 6) combining life-history models with large-scale datasets that are becoming increasingly available nowadays.…”

“…Although the OAR framework is suited for a broad range of research questions and has many advantages over other modelling approaches, the number of actual implementations is small (Feró et al 2008). One major reason for this might be the complexity of such models, which require time and expertise for model development and implementation.…”

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

“…The impacts of perturbations of vital rates on the population growth rate can be analyzed using sensitivity and elasticity analyses (Caswell, 2001;Greene and Beechie, 2004;Hunter and Caswell, 2005;Caswell and Shyu, 2012). When the objective involves factors other than the population growth rate (such as population size, age structure, extinction risk or harvest levels), perturbation analyses are commonly applied to estimate the contribution of a particular habitat (Sutherland 1996(Sutherland , 1998Pettifor et al, 2000;Caswell 2001;Hunter and Caswell, 2005;Fero et al, 2008;Taylor and Norris, 2010;Caswell and Shyu, 2012;Mattsson et al, 2012;Strasser et al, 2012;Bauer and Klaassen, 2013;Flockhart et al, 2015). 4.3.3.2.…”