AimThe spatial extent (scale) at which landscape attributes are measured has a strong impact on inferred species-landscape relationships. Consequently, researchers commonly measure landscape variables at multiple scales to select one scale (the 'scale of effect') that yields the strongest species-landscape relationship. Scales of effect observed in multiscale studies may not be true scales of effect if scales are arbitrarily selected and/or are too narrow in range. Miscalculation of the scale of effect may explain why the theoretical relationship between scale of effect and species traits, e.g. dispersal distance, is not empirically well supported.Location World-wide.Methods Using data from 583 species in 71 studies we conducted a quantitative review of multiscale studies to evaluate whether research has been conducted at the true scale of effect.Results Multiple lines of evidence indicated that multiscale studies are often conducted at suboptimal scales. We did not find convincing evidence of a relationship between observed scale of effect and any of 29 species traits. Instead, observed scales of effect were strongly positively predicted by the smallest and largest scales evaluated by researchers. Only 29% of studies reported biological reasons for the scales evaluated. Scales tended to be narrow in range (the mean range is 0.9 orders of magnitude) and few (the mean number of scales evaluated is four). Many species (44%) had observed scales of effect equal to the smallest or largest scale evaluated, suggesting a better scale was outside that range. Increasing the range of scales evaluated decreased the proportion of species with scales of effect equal to the smallest or largest scale evaluated. Main conclusionsTo ensure that species-landscape relationships are well estimated, we recommend that the scales at which landscape variables are measured range widely, from the size of a single territory to well above the average dispersal distance.

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Past studies with spatially structured herbivore populations have emphasized the primacy of intrinsic factors (e.g., patch quality), patch geometry (e.g., patch size and isolation), and more recently landscape context (e.g., matrix composition) in affecting local population abundance and dispersal rate. However, few studies have examined the relative importance of each factor, or how they might interact to affect herbivore abundance or dispersal. Here, we performed a factorial field experiment to examine the independent and interactive effects of patch quality (plant biomass, leaf protein, leaf phenolics) and matrix composition [mudflat or non-host grass (Bromus inermis)] on planthopper (Prokelisia crocea) emigration from host-plant patches (prairie cordgrass, Spartina pectinata). In addition, a field survey was conducted to examine the relative importance of patch quality, geography, and matrix composition on planthopper occupancy and density. In the experiment, we found that rates of emigration from low and intermediate quality patches were, on average, 21% percent higher for patches embedded in brome than mudflat. In contrast, the emigration rate was unaffected by matrix composition in nutrient-rich patches. Within matrix types, plant quality had little effect on emigration. In the survey, planthopper density and the patch occupancy rate of planthoppers increased nonadditively with increasing patch size and the percentage of the surrounding matrix composed of mudflat. This study suggests that landscape-level factors, such as the matrix, may be more important than factors intrinsic to the patches.

Conservation organizations must redouble efforts to protect habitat given continuing biodiversity declines. Prioritization of future areas for protection is hampered by disagreements over what the ecological targets of conservation should be. Here we test the claim that such disagreements will become less important as conservation moves away from prioritizing areas for protection based only on ecological considerations and accounts for varying costs of protection using return-on-investment (ROI) methods. We combine a simulation approach with a case study of forests in the eastern United States, paying particular attention to how covariation between ecological benefits and economic costs influences agreement levels. For many conservation goals, agreement over spatial priorities improves with ROI methods. However, we also show that a reliance on ROI-based prioritization can sometimes exacerbate disagreements over priorities. As such, accounting for costs in conservation planning does not enable society to sidestep careful consideration of the ecological goals of conservation.