Predator vs prey graph software#

For example, depending on the type of interaction, systems where the phenotypic variance of traits is largely determined by genetic variance tend to be more (e.g., competition-Maynard et al. Theory predicts that the effect of intraspecific variation upon the outcome of ecological interactions depends on the relative strength of environmental vs genetic variation (Schreiber et al.

Understanding the potential impact of phenotypic variation on predator–prey interactions and its evolutionary potential thus requires identifying the origin of such variation (Bolnick et al. This is the case when phenotypic variation affects ecological interactions, such as predation (e.g., Moya-Laraño 2011 Bolnick et al. Indeed, different sources of trait variation may indirectly affect evolutionary responses by inducing environmental changes that subsequently act as new selective pressures. This is particularly important in traits that evolve at fast rates. Changes in the latter will in turn set the stage for new selection pressures to operate on individual traits (Bolnick et al. In addition, from an ecological perspective, all sources of trait variation may in principle impact ecosystem functioning. Indeed, responses to selection mostly rely on the additive genetic variation, but other sources of variation may affect some of the characteristics of this response. Therefore, PPSR max, a central trait in ecosystems, can vary widely and this variation is due to different sources, with important consequences for changes in this trait in the short and long terms.ĭifferent sources of phenotypic variation have different implications for ecology and evolution. Finally, a maternal correlation between body size early in life and PPSR max indicated that offspring born larger were less predisposed to feed on larger prey later in life. PPSR max was also partially explained by body condition (during trial) but there was no effect of the rearing food environment. We found low, but significant heritability ( h 2 = 0.069) and dominance and common environmental variance ( d 2 + 4 c 2 = 0.056). We also measured body size and body condition of spiders upon emergence and just before the trial. Each juvenile spider was then sequentially offered crickets of decreasing size and the maximum prey size killed was determined.

We filled this gap by measuring the genetic, maternal and environmental variation of the maximum prey-to-predator size ratio (PPSR max) in juveniles of the wolf spider Lycosa fasciiventris using a paternal half-sib split-brood design, in which each male was paired with two females and the offspring reared in two food environments: poor and rich. Still, these sources of variation remain largely unknown. Identifying the range and origin of such variation is key to understanding the strength and constraints on selection in both predators and prey. However, this ratio can vary widely among individuals or populations. Click to download.The relative body size at which predators are willing to attack prey, a key trait for predator-prey interactions, is usually considered invariant. Suitable for projection or presentation while teaching these activities. Presentation Graphics Used in this ModuleĪll graphics presented in the Teacher Pages/Activity Instructions.The worksheets are made available as printable HTML pages.Īll the Next Generation Science Standards - Disciplinary Core Ideas, Cross Cutting Concepts, and Science & Engineering Principles - aligned to this module’s activities and linked to the NGSS Website. Worksheets needed by students to carry out the module activities. (This tutorial is the same as Activity I in each of the three modules.) The worksheets are made available as printable HTML pages.

Predator vs prey graph software#

This tutorial introduces students to the capabilities and navigation of the VES-V software through a virtual dive. All instructions are made available as printable HTML pages. The following are all the resources for implementing this module:ĭetailed instructions to the eight activities making up this module.

They will gather biomass data for predators and their prey in complex marine food webs and compare changes over time to the behaviors of the simpler systems with just a single predator and its lone prey. Then, students will collect data on “virtual dives” in simulated marine habitats. They will compare the population graphs produced by the model with actual historical data from a similar, simple predator-prey system. Students will analyze a simple predator-prey system, optionally building and “running” a simple, spreadsheet based model. This module introduces students to models used to predict populations of organisms within an ecosystem.