Thresholds for adding degraded tropical forest to the conservation estate

Abstract

Logged and disturbed forests are often viewed as degraded and depauperate environments compared with primary forest. However, they are dynamic ecosystems¹ that provide refugia for large amounts of biodiversity^2,3, so we cannot afford to underestimate their conservation value⁴. Here we present empirically defined thresholds for categorizing the conservation value of logged forests, using one of the most comprehensive assessments of taxon responses to habitat degradation in any tropical forest environment. We analysed the impact of logging intensity on the individual occurrence patterns of 1,681 taxa belonging to 86 taxonomic orders and 126 functional groups in Sabah, Malaysia. Our results demonstrate the existence of two conservation-relevant thresholds. First, lightly logged forests (<29% biomass removal) retain high conservation value and a largely intact functional composition, and are therefore likely to recover their pre-logging values if allowed to undergo natural regeneration. Second, the most extreme impacts occur in heavily degraded forests with more than two-thirds (>68%) of their biomass removed, and these are likely to require more expensive measures to recover their biodiversity value. Overall, our data confirm that primary forests are irreplaceable⁵, but they also reinforce the message that logged forests retain considerable conservation value that should not be overlooked.

Fig. 1. Summarized responses of 1,681 taxa and 126 functional groups to forest degradation.

Forest degradation is represented as a percentage reduction in above-ground biomass, for which zero represents the median biomass in unlogged forest. a, Cumulative distribution function of the proportion of taxa or functional groups that have passed a change point along the forest degradation gradient. b, Mean occurrence probabilities along the forest degradation gradient. Thin lines show the fitted lines for all individual taxa and functional groups. Thick lines show the unweighted mean value of all fitted lines. c,d, Probability distribution functions showing the spread of change points (c) and maximum rate points (d) in occurrence for individual taxa and functional groups. Insets present a stylized representation of how change and maximum rate points are identified (see Extended Data Fig. 3 for a more detailed explanation). Open circles represent locations at which the rate of accumulation of taxa accelerates, and are used to estimate thresholds (filled triangles) for conservation action (Methods). Peaks in the distributions represent points along the degradation gradient where the largest number of taxa or functional groups begin to be first affected (c) or have their maximum rate of change in occurrence probability (d).

Fig. 2. Vulnerability of 10 taxonomic groups and 47 functional traits to habitat degradation.

a, Taxonomic vulnerability. b, Functional vulnerability. The magnitude of vulnerability is indicated by the size of the plotted points, and is the product of metrics representing the probability and severity of impact that habitat degradation has on taxa within the groups (Methods). Probability of impact is represented as the proportion of individual taxa within the group that had statistically significant changes in occurrence along the forest degradation gradient. Severity of impact is calculated as one minus the mean proportion of biomass reduction at which individual taxa within the group have change points. Points are plotted at the mean values of probability and severity of impact per group, and whiskers represent the bootstrapped 95% confidence interval. We assigned 1,681 taxa to 1 of 10 taxonomic groups (a), and to all of the 126 functional traits for which those taxa exhibited matching characteristics (b; Methods and Supplementary Table 2). Only functional traits containing ≥5 taxa are shown (n = 47). Functional groups are coloured according to broadly defined functional categories.

Fig. 3. Functional group responses to a forest degradation gradient.

a,b, Data show the impact of biomass reduction on critical thresholds and turnover (a), and vulnerability, probability of impact and severity of impact (b) of functional groups. Analyses were conducted on the 126 functional groups described in Supplementary Table 2, but here we present only functional groups that had statistically significant responses to forest degradation. All other groups not shown had non-significant responses. In a, lines represent a single functional group and connect the change point (symbol) to the maximum rate point (dot) for that group. Line type indicates whether the occurrence probability of that functional group is increasing (solid) or decreasing (dashed) along the forest degradation gradient, and symbols represent different taxa. The ‘Other invertebrate’ grouping contains non-insect invertebrates. In b, vulnerability is shown in bars, with symbols representing the probability and severity of the impact that habitat degradation has on taxa within the groups. These metrics were calculated only for functional groups containing ≥5 taxa and are not shown for groups with fewer than this. In all panels, functional groups are coloured according to broadly defined functional categories.

Extended Data Fig. 1. Phylogenetic super-tree showing the 103 orders represented in the full set of biodiversity surveys.

Of the 103 orders, 86 had at least one taxon with enough occurrence observations to be analysed. Bar length represents the number of taxa per order (light shading), and the number of taxa that were analysed (dark shading). Bars are presented on a log₁₀-scale and are coloured according to taxonomic class.

Extended Data Fig. 2. Distribution of number of surveys per taxon for the 1,681 modelled taxa.

Of the taxa, 731 (44 %) were represented in a single survey, and the remaining 946 (56 %) were represented in multiple surveys.

Extended Data Fig. 3. Visualisation of the data analysis process.

(A) For a given taxon in a given survey, we modelled taxon occurrence using presence (filled circles) and absence (open circles) data collected from individual surveys. Fitted occurrence probabilities were predicted across the forest degradation gradient. Forest degradation is represented as a percentage reduction in aboveground biomass, where zero represents the median biomass in unlogged forest. (B) Some taxa were observed in multiple surveys (represented by semi-transparent lines, here fitted as survey-specific linear models), each of which could have a different occurrence pattern. In these cases, we used a mixed effect model to combine observations across all datasets, generating a single model of that taxon’s occurrence pattern that was used to determine turning and maximum rate points (thick line). (C) The second derivative (black line; y-axis values not shown) of the fitted curve (thick blue line) was used to detect change points (filled triangle), which signify the point at which forest degradation first exerts a discernible impact on taxon occurrence. Similarly, the first derivative (grey line; y-axis values not shown) was used to detect the point along the forest degradation gradient where the rate of change in occurrence of that taxon was the greatest (open triangle). (D) The approach used in panel (C) was applied to all taxa and functional groups. Two rules were used to record change points that fell outside of the survey’s forest degradation range (open triangles): if the change point occurred below or above the range of feasible values it was truncated to 0 % or 100 % respectively (labelled 1 and 2 on the figure).