The potential impact of tourism development on habitat availability and productivity of Malaysian plovers <i>Charadrius peronii</i>
Bibliographic record
Abstract
Summary Increased human pressure on coastal habitats has contributed to the global population decline in waders. Although coastal development can be particularly rapid and poorly regulated in tropical countries, very little research has been conducted to assess the extent of these impacts in the tropics. We examined the potential effects of human disturbance and tourism‐related habitat changes on Malaysian plovers breeding on sandy tropical beaches. In 2004 and 2005, we monitored 54 and 79 pairs of Malaysian plovers in the Gulf of Thailand, and used logistic habitat models to identify factors influencing habitat selection and breeding success. These models included variables affected by anthropogenic changes such as human disturbance and vegetation structure, as well as other natural factors such as prey availability and predator densities. We also assessed causes of nest failure and conducted 372 h of behavioural observations to identify mechanisms that relate important habitat variables to plover productivity. Plovers selected wide beaches with low levels of human disturbance that had a low percentage cover of tall trees backing the beach. The likelihood of hatching clutches and fledging chicks was greater in territories with low levels of human disturbance, low conspecific density and high percentage cover of 0·5–5 m tall vegetation backing the beach. Nest monitoring and behavioural observations suggested that heightened vulnerability to tidal inundation, trampling, heat stress, predators and territorial conflicts may have contributed to the results from the habitat models. We conclude that tourism development on Thai beaches affects both habitat availability and productivity of Malaysian plovers by enhancing beach erosion rates, converting medium vegetation into tall monocultures and intensifying human disturbance. These direct effects of habitat loss may be exacerbated by density‐dependent reductions in productivity. Synthesis and application. This study demonstrates the value of combining three approaches: habitat modelling, nest monitoring and behavioural observations, for identifying impacts of anthropogenic changes on breeding birds and assigning ultimate causes. In understudied regions where there are pressing threats to wildlife, this approach may focus research efforts so that the necessary data can be obtained rapidly in order to assess and predict human impacts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".