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Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management.

Wood KA, Stillman RA, Daunt F, O'Hare MT - PLoS ONE (2014)

Bottom Line: However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement.New methods which address these issues and offer effective wildlife management are required.The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems.

View Article: PubMed Central - PubMed

Affiliation: Centre for Ecology and Hydrology, Edinburgh, United Kingdom; Faculty of Science & Technology, Bournemouth University, Dorset, United Kingdom.

ABSTRACT
Effective wildlife management is needed for conservation, economic and human well-being objectives. However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement. New methods which address these issues and offer effective wildlife management are required. We used an individual-based model to predict the efficacy of a sacrificial feeding area in preventing grazing damage by mute swans (Cygnus olor) to adjacent river vegetation of high conservation and economic value. The accuracy of model predictions was assessed by a comparison with observed field data, whilst prediction robustness was evaluated using a sensitivity analysis. We used repeated simulations to evaluate how the efficacy of the sacrificial feeding area was regulated by (i) food quantity, (ii) food quality, and (iii) the functional response of the forager. Our model gave accurate predictions of aquatic plant biomass, carrying capacity, swan mortality, swan foraging effort, and river use. Our model predicted that increased sacrificial feeding area food quantity and quality would prevent the depletion of aquatic plant biomass by swans. When the functional response for vegetation in the sacrificial feeding area was increased, the food quantity and quality in the sacrificial feeding area required to protect adjacent aquatic plants were reduced. Our study demonstrates how the insights of behavioural ecology can be used to inform wildlife management. The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems.

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The influence of plant biomass and metabolisable energy content in the sacrificial feeding area (SFA) on aquatic plant biomass in the adjacent river.The dark grey region above the dashed line represents conditions under which aquatic plant biomass was not depleted and thus the SFA was effective. The functional response (FR; food intake rate, g DM hr−1) for swans feeding on plants in the SFA was set at (a) ×1.0, (b) ×2.0 and (c) × 3.0 of that previously reported for pasture grass. The symbol * indicates the mean energy and biomass values for SFA pasture grass.
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pone-0104034-g004: The influence of plant biomass and metabolisable energy content in the sacrificial feeding area (SFA) on aquatic plant biomass in the adjacent river.The dark grey region above the dashed line represents conditions under which aquatic plant biomass was not depleted and thus the SFA was effective. The functional response (FR; food intake rate, g DM hr−1) for swans feeding on plants in the SFA was set at (a) ×1.0, (b) ×2.0 and (c) × 3.0 of that previously reported for pasture grass. The symbol * indicates the mean energy and biomass values for SFA pasture grass.

Mentions: For each level of functional response, given a threshold SFA plant biomass and energy content, our model predicted that SFAs could prevent the depletion of aquatic plant biomass (Figure 4). Where the SFA was effective at preventing grazing of aquatic plants, aquatic plant biomass was predicted to be 185 g DM m−2. Where the SFA was ineffective, aquatic plant biomass was depleted to 169 g DM m−2 before the swans emigrated from the model area. Increasing the functional response for the SFA vegetation resulted in lower biomass and energy values required to prevent the depletion of aquatic plant biomass. Where the intake rate for SFA vegetation was set to equal the pasture grass functional response, our model predicted that the SFA would only prevent the aquatic plant depletion at relatively high SFA plant biomass and energy content (Figure 4a). To be effective the SFA energy content could be as low as 9 kJ g−1 DM given a biomass of 550 g DM m−2. Alternatively, an energy content of 15 kJ g−1 DM and biomass of 300 g DM m−2 was also predicted to be effective. Where the intake rate for SFA vegetation was set to two-times the pasture grass functional response, our model predicted that the SFA would prevent the aquatic plant depletion at lower SFA plant biomass and energy content (Figure 4b). To be effective the SFA energy content could be as low as 5 kJ g−1 DM given a biomass of 475 g DM m−2. Alternatively, an energy content of 10 kJ g−1 DM and biomass of 225 g DM m−2 was also predicted to be effective. Where the intake rate for SFA vegetation was set to three-times the pasture grass functional response, our model predicted that the SFA would prevent the aquatic plant depletion at lower SFA plant biomass and energy content (Figure 4c). To be effective the SFA vegetation energy content could be as low as 3 kJ g−1 DM given a biomass of 550 g DM m−2. Alternatively, an energy content of 7 kJ g−1 DM and biomass of 200 g DM m−2 was also predicted to be effective. However, given the known values for grass metabolisable energy (3.3 kJ g−1 DM) and biomass (406.0 g DM m−2), swans were predicted to always use river habitat whilst in the study area, even when the intake rate for SFA vegetation was set to three-times the pasture grass functional response (Figure 5).


Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management.

Wood KA, Stillman RA, Daunt F, O'Hare MT - PLoS ONE (2014)

The influence of plant biomass and metabolisable energy content in the sacrificial feeding area (SFA) on aquatic plant biomass in the adjacent river.The dark grey region above the dashed line represents conditions under which aquatic plant biomass was not depleted and thus the SFA was effective. The functional response (FR; food intake rate, g DM hr−1) for swans feeding on plants in the SFA was set at (a) ×1.0, (b) ×2.0 and (c) × 3.0 of that previously reported for pasture grass. The symbol * indicates the mean energy and biomass values for SFA pasture grass.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4117538&req=5

pone-0104034-g004: The influence of plant biomass and metabolisable energy content in the sacrificial feeding area (SFA) on aquatic plant biomass in the adjacent river.The dark grey region above the dashed line represents conditions under which aquatic plant biomass was not depleted and thus the SFA was effective. The functional response (FR; food intake rate, g DM hr−1) for swans feeding on plants in the SFA was set at (a) ×1.0, (b) ×2.0 and (c) × 3.0 of that previously reported for pasture grass. The symbol * indicates the mean energy and biomass values for SFA pasture grass.
Mentions: For each level of functional response, given a threshold SFA plant biomass and energy content, our model predicted that SFAs could prevent the depletion of aquatic plant biomass (Figure 4). Where the SFA was effective at preventing grazing of aquatic plants, aquatic plant biomass was predicted to be 185 g DM m−2. Where the SFA was ineffective, aquatic plant biomass was depleted to 169 g DM m−2 before the swans emigrated from the model area. Increasing the functional response for the SFA vegetation resulted in lower biomass and energy values required to prevent the depletion of aquatic plant biomass. Where the intake rate for SFA vegetation was set to equal the pasture grass functional response, our model predicted that the SFA would only prevent the aquatic plant depletion at relatively high SFA plant biomass and energy content (Figure 4a). To be effective the SFA energy content could be as low as 9 kJ g−1 DM given a biomass of 550 g DM m−2. Alternatively, an energy content of 15 kJ g−1 DM and biomass of 300 g DM m−2 was also predicted to be effective. Where the intake rate for SFA vegetation was set to two-times the pasture grass functional response, our model predicted that the SFA would prevent the aquatic plant depletion at lower SFA plant biomass and energy content (Figure 4b). To be effective the SFA energy content could be as low as 5 kJ g−1 DM given a biomass of 475 g DM m−2. Alternatively, an energy content of 10 kJ g−1 DM and biomass of 225 g DM m−2 was also predicted to be effective. Where the intake rate for SFA vegetation was set to three-times the pasture grass functional response, our model predicted that the SFA would prevent the aquatic plant depletion at lower SFA plant biomass and energy content (Figure 4c). To be effective the SFA vegetation energy content could be as low as 3 kJ g−1 DM given a biomass of 550 g DM m−2. Alternatively, an energy content of 7 kJ g−1 DM and biomass of 200 g DM m−2 was also predicted to be effective. However, given the known values for grass metabolisable energy (3.3 kJ g−1 DM) and biomass (406.0 g DM m−2), swans were predicted to always use river habitat whilst in the study area, even when the intake rate for SFA vegetation was set to three-times the pasture grass functional response (Figure 5).

Bottom Line: However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement.New methods which address these issues and offer effective wildlife management are required.The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems.

View Article: PubMed Central - PubMed

Affiliation: Centre for Ecology and Hydrology, Edinburgh, United Kingdom; Faculty of Science & Technology, Bournemouth University, Dorset, United Kingdom.

ABSTRACT
Effective wildlife management is needed for conservation, economic and human well-being objectives. However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement. New methods which address these issues and offer effective wildlife management are required. We used an individual-based model to predict the efficacy of a sacrificial feeding area in preventing grazing damage by mute swans (Cygnus olor) to adjacent river vegetation of high conservation and economic value. The accuracy of model predictions was assessed by a comparison with observed field data, whilst prediction robustness was evaluated using a sensitivity analysis. We used repeated simulations to evaluate how the efficacy of the sacrificial feeding area was regulated by (i) food quantity, (ii) food quality, and (iii) the functional response of the forager. Our model gave accurate predictions of aquatic plant biomass, carrying capacity, swan mortality, swan foraging effort, and river use. Our model predicted that increased sacrificial feeding area food quantity and quality would prevent the depletion of aquatic plant biomass by swans. When the functional response for vegetation in the sacrificial feeding area was increased, the food quantity and quality in the sacrificial feeding area required to protect adjacent aquatic plants were reduced. Our study demonstrates how the insights of behavioural ecology can be used to inform wildlife management. The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems.

Show MeSH
Related in: MedlinePlus