Evaluation of a Multiple-Species Approach to Monitoring Species at the Ecoregional Scale

Abstract

Monitoring is required of land managers and conservation practitioners to assess the success of management actions. “Shortcuts” are sought to reduce monitoring costs, most often consisting of the selection of a small number of species that are closely monitored to represent the status of many associated species and environmental correlates. Assumptions associated with such shortcuts have been challenged, yet alternative approaches remain scant. We evaluated an approach that departs significantly from the approach of selecting a few representative species. We explored two primary assertions: (1) that a coordinated multiple‐species monitoring effort that collects presence–absence data on a broad range of species is a robust alternative to a few intensive single‐species efforts, and (2) that the vertebrate species expected to be detected using this approach are numerous and diverse enough to represent all vertebrate species. We simulated monitoring the vertebrate species pool on an existing sample grid across the 7 million ha of public lands in the Sierra Nevada (USA) ecoregion. Based on the use of eight standard presence–absence protocols, we estimated the number of vertebrate species (excluding fish) with an adequate number of sample points within their range to detect ≥20% relative change in the proportion of points with detections between two points in time. We estimated that adequate detections would be obtained for 76% of the 465 vertebrate species, including 83% of all birds, 76% of all mammals, 65% of all reptiles, and 44% of all amphibians. Detection adequacy varied among life‐history and ecological groups, but >50% of the species were adequately detected in every group with the exception of three groups: rare species, endemic species, and species of concern (33%, 24%, and 47% of associated species adequately detected, respectively). A multiple‐species monitoring approach represents an effective and feasible alternative to the challenges of large‐scale monitoring needs by targeting the most basic of population data for a large number and breadth of species.

Temporal dynamics of fish assemblages of natural and artificial tropical estuaries

“…presences per net, rather than CPUE. This approach has proved robust for cast net samples from tropical estuaries (Sheaves & Johnston 2009) because it treats species with a diversity of behaviours and patterns of spatial distribution in a more equivalent way than fully quantitative techniques (Manley et al 2004 Trip and Reach. Assemblage structure was analysed using multivariate classification and regression trees (mCARTs).…”

Genetic monitoring as a promising tool for conservation and management

“…Site occupancy and geographical range Changes in the proportion and distribution of sites where a species is observed is commonly monitored to elucidate effects of environmental change [19,20]. These occupancy statistics can be hindered by low probability of detection owing to the elusive nature of some species, and by false positives that occur when visual identification is cryptic or a species leaves signs that are easily confused with signs of other species.…”

Pinus albicaulis Engelm. (Whitebark Pine) in Mixed-Species Stands throughout Its US Range: Broad-Scale Indicators of Extent and Recent Decline

“…Finally, this study opportunistically utilized a national forest inventory dataset to assess a species of concern at a scale that is not possible via purposive sampling due to logistical and cost constraints [15]. This approach contrasts with purposive sampling or experimentation-or even probabilistic sampling within a more constrained region-that enhances our understanding of finer-scale ecological relationships and drivers of demographic changes [3].…”

“…National forest inventories offer an opportunity to use strategic, probabilistic sampling to assess multiple species of concern throughout a wide range of environments [15,16]. The purpose of this study was to quantify four indicators of whitebark pine viability using the US national forest inventory, which represents a spatially representative, broad-scale forest monitoring dataset.…”