Species co-occurrence networks show reptile community reorganization under agricultural transformation
- Kay, Geoffrey, Tulloch, Ayesha, Barton, Philip, Cunningham, Saul, Driscoll, Don, Lindenmayer, David
- Authors: Kay, Geoffrey , Tulloch, Ayesha , Barton, Philip , Cunningham, Saul , Driscoll, Don , Lindenmayer, David
- Date: 2018
- Type: Text , Journal article
- Relation: Ecography Vol. 41, no. 1 (2018), p. 113-125
- Full Text:
- Reviewed:
- Description: Agricultural transformation represents one of the greatest threats to biodiversity, causing degradation and loss of habitat, leading to changes in the richness and composition of communities. These changes in richness and composition may, in turn, lead to altered species co-occurrence, but our knowledge of this remains limited. We used a novel co-occurrence network approach to examine the impact of agricultural transformation on reptile community structure within two large (> 172 000 km2; 224 sites) agricultural regions in southeastern Australia. We contrasted assemblages from sites surrounded by intact and modified landscapes and tested four key hypotheses that agricultural transformation leads to (H1) declines in species richness, (H2) altered assemblages, (H3) declines in overall co-occurrence, and (H4) complex restructuring of pairwise associations. We found that modified landscapes differed in composition but not richness compared with intact sites. Modified landscapes were also characterized by differences in co-occurrence network structure; with species sharing fewer sites with each other (reduced co-occurrence connectance), fewer highly-connected species (truncation of the frequency distribution of co-occurrence degree) and increased modularity of co-occurrence networks. Critically, overall loss of co-occurrence was underpinned by complex changes to the number and distribution of pair-wise co-occurrence links, with 41–44% of species also gaining associations with other species. Change in co-occurrence was not correlated with changes in occupancy, nor by functional trait membership, allowing a novel classification of species susceptibility to agricultural transformation. Our study reveals the value of using co-occurrence analysis to uncover impacts of agricultural transformation that may be masked in conventional studies of species richness and community composition. © 2017 The Authors
- Authors: Kay, Geoffrey , Tulloch, Ayesha , Barton, Philip , Cunningham, Saul , Driscoll, Don , Lindenmayer, David
- Date: 2018
- Type: Text , Journal article
- Relation: Ecography Vol. 41, no. 1 (2018), p. 113-125
- Full Text:
- Reviewed:
- Description: Agricultural transformation represents one of the greatest threats to biodiversity, causing degradation and loss of habitat, leading to changes in the richness and composition of communities. These changes in richness and composition may, in turn, lead to altered species co-occurrence, but our knowledge of this remains limited. We used a novel co-occurrence network approach to examine the impact of agricultural transformation on reptile community structure within two large (> 172 000 km2; 224 sites) agricultural regions in southeastern Australia. We contrasted assemblages from sites surrounded by intact and modified landscapes and tested four key hypotheses that agricultural transformation leads to (H1) declines in species richness, (H2) altered assemblages, (H3) declines in overall co-occurrence, and (H4) complex restructuring of pairwise associations. We found that modified landscapes differed in composition but not richness compared with intact sites. Modified landscapes were also characterized by differences in co-occurrence network structure; with species sharing fewer sites with each other (reduced co-occurrence connectance), fewer highly-connected species (truncation of the frequency distribution of co-occurrence degree) and increased modularity of co-occurrence networks. Critically, overall loss of co-occurrence was underpinned by complex changes to the number and distribution of pair-wise co-occurrence links, with 41–44% of species also gaining associations with other species. Change in co-occurrence was not correlated with changes in occupancy, nor by functional trait membership, allowing a novel classification of species susceptibility to agricultural transformation. Our study reveals the value of using co-occurrence analysis to uncover impacts of agricultural transformation that may be masked in conventional studies of species richness and community composition. © 2017 The Authors
Optimal taxonomic groups for biodiversity assessment: a meta-analytic approach
- Westgate, Martin, Tulloch, Ayesha, Barton, Philip, Pierson, Jennifer, Lindenmayer, David
- Authors: Westgate, Martin , Tulloch, Ayesha , Barton, Philip , Pierson, Jennifer , Lindenmayer, David
- Date: 2017
- Type: Text , Journal article
- Relation: Ecography Vol. 40, no. 4 (2017), p. 539-548
- Full Text:
- Reviewed:
- Description: A fundamental decision in biodiversity assessment is the selection of one or more study taxa, a choice that is often made using qualitative criteria such as historical precedent, ease of detection, or available technical or taxonomic expertise. A more robust approach would involve selecting taxa based on the a priori expectation that they will provide the best possible information on unmeasured groups, but data to inform such hypotheses are often lacking. Using a global meta-analysis, we quantified the proportion of variability that each of 12 taxonomic groups (at the Order level or above) explained in the richness or composition of other taxa. We then applied optimization to matrices of pairwise congruency to identify the best set of complementary surrogate groups. We found that no single taxon was an optimal surrogate for both the richness and composition of unmeasured taxa if we used simple methods to aggregate congruence data between studies. In contrast, statistical methods that accounted for well-known drivers of cross-taxon congruence (spatial extent, grain size, and latitude) lead to the prioritization of similar surrogates for both species richness and composition. Advanced statistical methods were also more effective at describing known ecological relationships between taxa than simple methods, and show that congruence is typically highest between taxonomically and functionally dissimilar taxa. Birds and vascular plants were most frequently selected by our algorithm as surrogates for other taxonomic groups, but the extent to which any one taxon was the ‘optimal’ choice of surrogate for other biodiversity was highly context-dependent. In the absence of other information – such as in data-poor areas of the globe, and under limited budgets for monitoring or assessment – ecologists can use our results to assess which taxa are most likely to reflect the distribution of the richness or composition of ‘total’ biodiversity. © 2016 The Authors
- Authors: Westgate, Martin , Tulloch, Ayesha , Barton, Philip , Pierson, Jennifer , Lindenmayer, David
- Date: 2017
- Type: Text , Journal article
- Relation: Ecography Vol. 40, no. 4 (2017), p. 539-548
- Full Text:
- Reviewed:
- Description: A fundamental decision in biodiversity assessment is the selection of one or more study taxa, a choice that is often made using qualitative criteria such as historical precedent, ease of detection, or available technical or taxonomic expertise. A more robust approach would involve selecting taxa based on the a priori expectation that they will provide the best possible information on unmeasured groups, but data to inform such hypotheses are often lacking. Using a global meta-analysis, we quantified the proportion of variability that each of 12 taxonomic groups (at the Order level or above) explained in the richness or composition of other taxa. We then applied optimization to matrices of pairwise congruency to identify the best set of complementary surrogate groups. We found that no single taxon was an optimal surrogate for both the richness and composition of unmeasured taxa if we used simple methods to aggregate congruence data between studies. In contrast, statistical methods that accounted for well-known drivers of cross-taxon congruence (spatial extent, grain size, and latitude) lead to the prioritization of similar surrogates for both species richness and composition. Advanced statistical methods were also more effective at describing known ecological relationships between taxa than simple methods, and show that congruence is typically highest between taxonomically and functionally dissimilar taxa. Birds and vascular plants were most frequently selected by our algorithm as surrogates for other taxonomic groups, but the extent to which any one taxon was the ‘optimal’ choice of surrogate for other biodiversity was highly context-dependent. In the absence of other information – such as in data-poor areas of the globe, and under limited budgets for monitoring or assessment – ecologists can use our results to assess which taxa are most likely to reflect the distribution of the richness or composition of ‘total’ biodiversity. © 2016 The Authors
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