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opencc-zeroNov 2022View details →

Monitoring small mammal abundance using NEON data: Are calibrated indices useful?

Small mammals are important to the functioning of ecological communities with changes to their abundances used to track impacts of environmental change. While capture-recapture estimates of absolute abundance are preferred, indices of abundance continue to be used in cases of limited sampling, rare species with little data, or unmarked individuals. Improvement to indices can be achieved by calibrating them to absolute abundance but their reliability across years, sites, or species is unclear. To evaluate this, we used the US National Ecological Observatory Network (NEON) capture-recapture data for 63 small mammal species over 46 sites from 2013–2019. We generated 17,155 absolute abundance estimates using capture-recapture analyses and compared these to two standard abundance indices, and three types of calibrated indices. We found that neither raw abundance indices nor index calibrations were reliable approximations of absolute abundance, with raw indices less correlated with absolute abundance than index calibrations (raw indices overall R2 < 0.5, index calibration overall R2 > 0.6). Performance of indices and index calibrations varied by species, with those having higher and less variable capture probabilities performing best. We conclude that indices and index calibration methods should be used with caution with a count of individuals being the best index to use, especially if it can be calibrated with capture probability. None of the indices we tested should be used for comparing different species due to high variation in capture probabilities. Hierarchical models that allow for sharing of capture probabilities over species or plots (i.e., joint likelihood models) may offer a better solution to mitigate the cost and effort of large-scale small mammal sampling while still providing robust estimates of abundance.

opencc-zeroJul 2023View details →

Data from: Long term monitoring reveals the importance of large, long unburnt areas and smaller fires in moderating mammal declines in fire-prone savanna of northern Australia

Biodiversity loss is often attributable to multiple interacting pressures that are moderated across environmental gradients. These processes contribute to complex responses that are challenging to interpret and understand. Well-designed and well-implemented monitoring can play a vital role in this but is rarely undertaken. Mounting evidence suggests that current fire regimes across savanna ecosystems have contributed to the decline of a range of biota. Hence, contemporary fire regimes are at odds with conservation goals. Using an extensive spatio-temporal monitoring dataset from three large National Parks in northern Australia, we applied generalised linear mixed models to examine: 1) trends in mammal richness and abundance through time and how these vary across environmental gradients such as productivity or landscape position (e.g., terrain ruggedness); and 2) how fire, a potential driver, is moderated by environmental gradients. Across 24-years, major declines in mammal richness and abundance were observed with greater reductions in less rugged and less mesic habitats. Patterns of decline were related to multiple aspects of fire regimes, but not changes in vegetation structure and composition, or the arrival of Cane Toads Rhinella marina and concomitant poisoning of predatory animals during consumption. More pronounced declines occurred in sites that were exposed to larger fires, had less long unburnt (5 years without fire) vegetation, and were more distant from large, long unburnt patches. Relationships between mammal persistence and fire varied among vegetation communities, with the strongest fire effects observed in lowland woodland – relatively drier with few barriers to fire spread – where the availability of long unburnt areas moderated declines more than in other vegetation communities. Synthesis and applications. Current fire regimes are contributing to mammal declines in northern Australian savanna. Collectively, our results highlight: 1) the value of long term monitoring, and importance of considering landscape position when assessing faunal responses to landscape-level perturbations like fire; 2) that significant improvements in fire regimes are required to ameliorate mammal declines; and 3) the need to shift management focus from retaining small, short-lived unburnt patches towards preserving relatively large contiguous areas of long unburnt habitat, particularly in less rugged lowland and sandstone woodlands.

publicJul 2023View details →

Data from: Long term monitoring reveals the importance of large, long unburnt areas and smaller fires in moderating mammal declines in fire-prone savanna of northern Australia

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publicApr 2016View details →

Data from: Random versus game trail-based camera trap placement strategy for monitoring terrestrial mammal communities

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publicJan 2022View details →

Data from: Scat DNA provides important data for effective monitoring of mammal and bird biodiversity

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publicNov 2022View details →

Monitoring small mammal abundance using NEON data: Are calibrated indices useful?

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Figure 5 from: Jung J, Alfonsi E, Méheust E, Fuchs S, Carpentier F, Quillivic Y, Viricel A, Hassani S (2013) The use of DNA barcoding to monitor the marine mammal biodiversity along the French Atlantic coast. ZooKeys 365: 5-24. https://doi.org/10.3897/zookeys.365.5873

Figure 5 - Non-metric Multidimensional Scaling plot of K2P-distance between MCR sequences of Stenella coeruleoalba (in blue), Delphinus delphis (in red) and Stenella frontalis (in green). Individuals of each species are clearly clustered together, and unidentified samples (in black) stranded along the coasts of Brittany group with one of the three species. Dd280211A (Ds1), Ds130210 (Ds3), Ds230409 (Ds4), Ds250412 (Ds5) and Sc210910 (Ds6) are putatively identified as Delphinus delphis, whereas Ds080410 (Ds2) would more likely belong to Stenella coeruloalba.

Figure 2 from: Jung J, Alfonsi E, Méheust E, Fuchs S, Carpentier F, Quillivic Y, Viricel A, Hassani S (2013) The use of DNA barcoding to monitor the marine mammal biodiversity along the French Atlantic coast. ZooKeys 365: 5-24. https://doi.org/10.3897/zookeys.365.5873

Figure 2 - Organization of the stranding network in Brittany (North West of France) and localization of the stranded specimens used in this study. Numbers indicate the 18 geographic sections of the stranding network in this area. The map was drawn using ArcGIS Desktop: Release 9.3.1 (Environmental Systems Research Institute, Redlands, CA, USA) with WGS 84 coordinates.

Figure 1 from: Jung J, Alfonsi E, Méheust E, Fuchs S, Carpentier F, Quillivic Y, Viricel A, Hassani S (2013) The use of DNA barcoding to monitor the marine mammal biodiversity along the French Atlantic coast. ZooKeys 365: 5-24. https://doi.org/10.3897/zookeys.365.5873

Figure 1 - Numbers of different species of marine mammals stranded along the coasts of Brittany (North West of France) in the period 2003–2012.

Figure 4 from: Jung J, Alfonsi E, Méheust E, Fuchs S, Carpentier F, Quillivic Y, Viricel A, Hassani S (2013) The use of DNA barcoding to monitor the marine mammal biodiversity along the French Atlantic coast. ZooKeys 365: 5-24. https://doi.org/10.3897/zookeys.365.5873

Figure 4 - Examples of marine mammals stranded along the coasts of Brittany and the species-level identifications of which were determined or confirmed thanks to DNA barcoding. A Sample Ms250511, stranded on the "Île de Sein" during May 2011, and identified as a Balaenoptera physalus B Sample Ds160111, stranded on the Ushant Island during January 2011, and identified as a Grampus griseus C Sample Ds130211, stranded on the Ushant Island in February 2011, and identified as belonging to the Delphininae subfamily (putatively identified as a Delphinus delphis on the nMDS plot in Figure 5) D Sample Ds080410 stranded on the Ushant Island during April 2010, and identified as belonging to the Delphininae (putatively identified as a Stenella coeruleoalba on the nMDS plot in Figure 5).

Figure 3 from: Jung J, Alfonsi E, Méheust E, Fuchs S, Carpentier F, Quillivic Y, Viricel A, Hassani S (2013) The use of DNA barcoding to monitor the marine mammal biodiversity along the French Atlantic coast. ZooKeys 365: 5-24. https://doi.org/10.3897/zookeys.365.5873

Figure 3 - Neighbour-Joining tree of major species of marine mammals, based on K2P-distances calculated from 507 bp of COI. All sequences come from the IMMB project on BOLD, and only 5 harbour porpoise and 5 grey seal samples among those of the IMMB project have been included in the analysis.

Figure 6 from: Jung J, Alfonsi E, Méheust E, Fuchs S, Carpentier F, Quillivic Y, Viricel A, Hassani S (2013) The use of DNA barcoding to monitor the marine mammal biodiversity along the French Atlantic coast. ZooKeys 365: 5-24. https://doi.org/10.3897/zookeys.365.5873

Figure 6 - Haplotype network established from the COI sequences of 45 harbour porpoises stranded along the Atlantic coast of France (Appendix 1). Numbers on a line connecting two haplotypes correspond to the sequence position of the mutation differentiating these haplotypes. Two mitochondrial haplogroups appear (black circles - grey circles), that group the same individuals as the haplogroups alpha and beta determined using MCR polymorphisms and described in Alfonsi et al. (2012).