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Table 2 Critical appraisal criteria to assess studies in the full text stage

From: Are small protected habitat patches within boreal production forests effective in conserving species richness, abundance and community composition? A systematic review

Factor Low risk Medium risk High risk
Study design Experimental studies (includes also quasi-experimental studies) Observational studies Case studies (descriptive studies)
Sampling  Large sample size relative to outcome measure and species in question (high confidence that replication is appropriate and representative)
 Sampling method suitable for the population of interesta
 Randomisation accounting for spatial heterogeneity
Control and intervention areas matched based on their ecological characteristics
 Small to medium sample size relative to outcome measure and species in question (medium level of confidence that replication is appropriate and representative).
 Sampling method suitable for the population of interesta
 Control and intervention areas comparable based on their ecological characteristics
Sampling method not suitable for collecting data on the population of interesta
Accounting for heterogeneity and potential effect modifiers Potential biologically important effect modifiers that could influence the study findings identified, and data collected on them. The context in which the study took place clear Potential biologically important effect modifiers that could influence the study findings identified, and considered in relation to the results. The context in which the study took place clear even when there was no direct data Effect modifiers not identified or considered. The context of the study is unclear
Data analysis methods Methods appropriateb Methods appropriateb Methods not appropriateb
  1. aSuitable sampling method refers to the use of methods that are known to work for the population in question based on published studies, e.g. flying insects are sampled by trapping or fogging, not by cutting branches
  2. bAppropriate methods refer to the use of statistical methods that consider data characteristics such as sample size and distribution. For example, non-parametric statistical tests are used for data that does not follow normal distribution