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The continuing circulation and reassortment with low-pathogenicity avian influenza Gs/Gd (goose/Guangdong/1996)-like avian influenza viruses (AIVs) has caused huge economic losses and raised public health concerns over the zoonotic potential. Virologic surveillance of wild birds has been suggested as part of a global AIV surveillance system. However, underreporting and biased selection of sampling sites has rendered gaining information about the transmission and evolution of highly pathogenic AIV problematic. We explored the use of the Citizen Scientist eBird database to elucidate the dynamic distribution of wild birds in Taiwan and their potential for AIV exchange with domestic poultry. Through the 2-stage analytical framework, we associated nonignorable risk with 10 species of wild birds with100 significant positive results. We generated a risk map, which served as the guide for highly pathogenic AIV surveillance. Our methodologic blueprint has the potential to be incorporated into the global AIV surveillance system of wild birds.

Accurate data describing the geographic distribution of specific species form the basis for effective conservation management policies. However, for most species the freely available distributional information is usually confined to either expert maps or purely theoretical maps constructed by using a variety of modeling frameworks. These maps usually do not provide enough resolution for conservation applications or do not accurately describe the current distribution status. In this study, we constructed a novel workflow designed to integrate data from various species distribution models and expert knowledge into a single unified modeling process. Under this workflow, we systematically constructed current distribution maps for a selection of terrestrial vertebrates found across Taiwan. We used species distribution modeling as the base and then aggregated multiple open datasets describing species occurrence and environmental factors as data sources. Thereafter, we estimated the primary broad-scale and high spatial resolution species range maps using the MaxEnt modeling algorithm, and then consulted experts on each taxa to refine these maps. This dataset provides up-to-date species distribution maps for 379 terrestrial vertebrates in Taiwan, with members from across four taxa (27 amphibians, 52 reptiles, 264 birds, and 36 mammals). This dataset helps to fill the spatial knowledge gaps for conservation concerns and improves our understanding of the geographic distribution of more than half (61%) of the vertebrate species of Taiwan. Furthermore, by stacking the range maps of multiple species, we can identify vertebrate diversity hotspots and identify priority areas for conservation.

Species traits affect how a species interacts with the environment and other species and thus determine the role of the species in an ecosystem. They affect not only population dynamics of a species across space and over time, but also community structure and function through their key role in the community assembly processes. Information on species traits is also highly relevant for conservation planning as they determine the adaptive ability of a species in the face of environmental changes. However, information on species traits is usually scarce and sparsely distributed amongst diverse types of literature and sources. Difficulty in accessing comprehensive information on species traits has formed an essential knowledge gap, limiting our understanding of biodiversity patterns and ecosystem functioning and preventing effective conservation. Even for birds, a well-studied taxon, comprehensive trait information is still unavailable or distributed across different sources for many species. In this study, we compiled information from a variety of sources on 23 traits for all breeding birds, including 157 resident and 14 summer visiting species, in Taiwan and surrounding islands. The 23 traits include those related to the movement patterns, morphology, geographic distributions, activity patterns, feeding behaviour, habitat use, and breeding behaviour and strategies of the species. The trait information was obtained, not only from published literature and datasets, but also from unpublished banding records and specimen measurements. The dataset also contains derived traits, including the elevation and temperature boundaries of species distribution ranges in Taiwan. In addition, structured information on nest characters, which is seldom compiled in trait datasets, has been made available, for the first time, for the breeding birds in Taiwan. Therefore, the most comprehensive trait dataset to date on breeding birds in Taiwan will allow trait-based research and applications in diverse topics and thus enhance our understanding of the patterns and dynamics of breeding bird diversity and its functions in Taiwan.

The importance of a data exchanging culture accompanied by a supporting bioinformatic system is widely praised as an aid to sustainable development. Yet this is not always implemented as a top-down procedure in every governing environment. Common obstacles include lack of resources, lack of support from decision-makers, and lack of recognition from data-providers. Using citizen science (hereafter CS), which assumes a spirit of public information sharing, we demonstrate how CS can be a critical tool to help database managers overcome this difficulty. CS data contributes to impressively over 70% of the currently 4.5 million openly distributed occurrence data in Taiwan. Although CS projects emerged much earlier in a few taxa, such as Aves and Anura, CS was unknown to the wider public and politicians in the region until 2009. This was probably due to the combination of the popularity of social media and improvements to wifi connections, which brought discoveries and impacts of CS data to the news spotlight. Such cases include roadkill projects that aided rabies-outbreak control, and amateur bird records that helped downscale the conflict between solar energy deployment and migratory wetland bird conservation. These cases also created feedback on the call for more data to be open, an effect that was prominent from project managers in other CS communities, the previously reluctant expert researcher communities, and even placed pressure on data policy of several conservation agencies which previously were not supportive of open data. The inclusion of CS programs is also critical in forming alliances between agencies that were responsible for promoting and building the biodiversity informatics system. Previously, financial and human resources for such systems are split across agencies. However, in terms of building up a cutting edge biodiversity information service platform, or empowerment of human resources to handle the rapidly growing amount of data, joint partnerships across government agencies is then necessary. CS brings the spotlight of government efforts to the people, which is an important strategy to maintain support from top decision-makers and politicians, who mostly rely on public votes in a democratic society. Currently, the national node of the Global Biodiversity Information Facility in Taiwan, the administration for conservation in Taiwan, and the main biodiversity consultancy in Taiwan have teamed up, answering the call for sharing data for a better future. As a tribute to the CS projects, a biodiversity informatics system named Taiwan Biodiversity Network, is now enhancing its ability as a platform to promote data usage and provide technical aid to CS programs. Data visualization projects such as “Coldspots” pointed out regions that lack data, which can be used to decide where to focus efforts for the next field surveys. Online CS data platforms, such as Taiwan Reptile Report Program, are also working to ease the previously intensive efforts that project managers needed to contribute to run event-based monitoring. Combined, these developments form a cultural and technical basis for the implementation of multi-taxa atlas projects, which was made possible by the mainstreaming of open data culture and biodiversity awareness through citizen science projects.

Dominance hierarchies usually form quickly among avian foraging groups because they are beneficial to most individuals by reducing conflict. Several characteristics that correlate with dominance rank have been identified in birds, but most of these conclusions rely on studies of temperate species. Hence, we studied whether captive group members of a subtropical species, grey-cheeked fulvetta Alcippe morrisonia, form social dominance hierarchies when competing for food during the non-breeding season. We also investigated whether sex, age, body condition and fat score were related to an individual's dominance rank which was established by counting aggressive interactions in six captive groups of nine individuals each. In all groups, linear dominance hierarchies were formed whereby yearlings dominated over adult birds, and individuals with a better body condition were also more dominant, while sex and fat score had no discernable effect. Male yearlings had significantly higher body masses and body condition indices than male adults, while female yearlings had significantly higher body masses, body condition indices and fat scores than female adults. However, there were no significant differences between male and female yearlings or adults for any of these variables. We suggest possible reasons for the dominance of yearlings, such as captive conditions or the higher body weight of yearlings.

SummaryTaiwan has 145 breeding bird species, but so far no comprehensive attempt has been made to model their distributions. For the first time, we bring together various datasets to model the distributions of the 116 bird species with sufficient sampling coverage. We improved on previous limited modelling efforts by using ensemble modelling, based on five well-performing modelling approaches: multiple discriminant analysis, logistic regression, genetic algorithm for rule-set production, ecological niche factor analysis and maximum-entropy. We then used these ensemble models to improve our knowledge of the status of each bird species by (1) calculating each species’s coverage of Taiwan, (2) calculating each species’s coverage by Taiwan’s protected area network, and (3) comparing these two conservation-relevant measures with already established measures to highlight those species whose status may need to be reassessed. We categorised each species’s coverage of the entire study area as measured by their modelled distributions into four quartiles, thus establishing a new measure of rarity called ‘range quartile’ which we used to highlight the 22 species with a limited distribution on mainland Taiwan. We also calculated that overall, 29.8% of the distribution ranges of the 116 modelled species are covered by Taiwanese protected areas. We then identified those species whose status may need to be reassessed because of possible conflicts between the respective conservation-relevant measures. Thus we identified 10 species which are first-quartile species < 5% of whose distributions are protected, of which only five are considered threatened. We also identified another 12 species with limited distributions, 30 species with limited protection and 19 species whose status may need to be reassessed for various reasons. We recommend that range quartile and protected area coverage be incorporated into future assessments of the conservation status and protected area coverage of Taiwanese birds.

Modelling species distributions has been widely used to understand present and future potential distributions of species, and can provide adaptation and mitigation information as references for conservation and management under climate change. However, various methods of data splitting to develop and validate functions of the models do not get enough attention, which may mislead the interpretation of predicted results. We used the Taiwanese endemic birds to test the influences of temporal independence of datasets on model performance and prediction. Training and testing data were considered to be independent if they were collected during different survey periods (1993–2004 and 2009–2010). The results indicated no significant differences of six model performance measures (AUC, kappa, TSS, accuracy, sensitivity, and specificity) among the combinations of training and testing datasets. Both species- and grid cell-based assessments differed significantly between predictions by the annual and pooled training data. We also found an average of 85.8% similarity for species presences and absences in different survey periods. The remaining dissimilarity was mostly caused by species observed in the late survey period but not in the early one. The method of data splitting, yielding training and testing data, is critical for resulting model species distributions. Even if similar model performance exists, different methods can lead to different species distributional maps. More attention needs to be given to this issue, especially when amplifying these models to project species distributions in a changing world.

For the study of the macroecology and conservation of Taiwan’s birds, there was an urgent need to develop distribution models of bird species whose distribution had never before been modeled. Therefore, we here model the distributions of 27 mostly rare and cryptic breeding bird species using a statistical approach which has been shown to be especially reliable for modeling species with a low sample size of presence localities, namely the maximum entropy (Maxent) modeling technique. For this purpose, we began with a dedicated attempt to collate as much high-quality distributional data as possible, assembling databases from several scientific reports, contacting individual data recorders and searching publicly accessible database, the internet and the available literature. This effort resulted in 2022 grid cells of 1 × 1 km size being associated with a presence record for one of the 27 species. These records and 10 pre-selected environmental variables were then used to model each species’ probability distribution which we show here with all grid cells below the lowest presence threshold being converted to zeros. We then in detail discuss the interpretation and applicability of these distributions, whereby we pay close attention to habitat requirements, the intactness and fragmentation of their habitat, the general detectability of the species and data reliability. This study is another one in an ongoing series of studies which highlight the usefulness of using large electronic databases and modern analytical methods to help with the monitoring and assessment of Taiwan’s bird species.

Male white-rumped munias sing syntactically simpler songs than their domestic counterparts, Bengalese finches. The differences in song structure may reflect differences in natural selection pressures between wild and domestic environments. Deacon (2010) proposed song simplicity of the wild strain could be subject to natural selection. We hypothesized the selection pressure may be species identification. Thus, we compared song variations in relation to ecological factors and dispersal history of white-rumped munias to understand song evolutionary processes. We found geographic variations of song syntactical complexity. The difference of song syntactical complexity did not corresponded to genetic distance, but did to that of the proportion of mixed flocks with sympatric related species. Birds that inhabited the areas with more mixed flocks sang simpler songs. The song complexity might be constrained to intensify distinct conspecific signals from related species. Our field work provided empirical evidence supporting a proposal made by Deacon (2010). Keywords: birdsong; evolution; masking hypothesis; Bengalese finches; song geographic variation; genetic variation

Understanding species distributions is essential for developing biodiversity conservation strategies. We combined two bird inventories conducted from 1993 to 2004 and identified specific features of 17 endemic bird species in Taiwan. We used eight environmental variables, including elevation, annual total precipitation, annual mean temperature, warmth index, percentage of forest cover, mean Normalized Difference Vegetation Index (NDVI), percentage of building area, and road density, to define macrohabitat characteristics of each species. All the data were in a 1 × 1 km gird system. The 17 species were classified as common (being present in more than 200 grids), uncommon (100–200 grids) or rare (less than 100 grids). The Mikado Pheasant (Syrmaticus mikado), as a rare species, had the lowest occurrence records, while the Taiwan Barbet (Megalaima nuchalis), as a common species, had the highest. Each species had a specific distribution range and habitat preference. These 17 species occupied heterogeneous elevation and climatic conditions. In general, they favored habitats with high vegetation cover, at almost full forest cover and median to high NDVI. Canonical correspondence analysis (CCA) indicated that elevation had the highest correlations with species distributions, with axis 1 accounting for 57.5% of the variation and axis 2 for 9.8%. The endemic species in Taiwan could be classified into three groups mainly separated by elevation based on the CCA. Potential biodiversity hotspots, in the elevation range of 300 and 1500 m with 45%-100% forest cover, included 33.2% areas of Taiwan. Only 35% of actual hotspots (grid with the number of endemic species ≧7) were located in the potential hotspots. Most of the actual hotspots (65%) occur at higher elevation than the potential hotspots. These data demonstrated the distribution patterns of the endemic bird species in Taiwan, and topography and vegetation are the most important macrohabitat factors associated with these species.

The White-rumped Shama (Copsychus malabaricus) is an alien invasive species in Taiwan. The distribution and abundance of this species was estimated based on recorded observation of active birders, the database of 1988-2007 provided by the Chinese Wild Bird Federation, literature citation, a field survey conducted from 2006 to 2008 and an eradication project conducted from 2007 to 2008. This species was found primarily in the western hilly areas of Taiwan at elevations below 400 m. Since it was first recorded in the wild in 1988, it has bred in recent years resulting in confirmed sustainable feral populations in Taiwan. The population sizes of the species in Huben Village, Linnei Township, in Yunlin County remained low originally but the rate of increase steadily increased after 2005. However, the areas where this invasive feral population has established itself are still confined to southern and central-western Taiwan. Unlike earlier avian invaders in Taiwan, the White-rumped Shama has the ability to invade lowland natural forest areas. Therefore, it is recommended that proactive control management is executed at a time when their population is still limited in number and localized.

A fundamental step in biodiversity conservation is to identify potential distribution and quality habitat for a desired species, especially when the target is rare and difficult to detect. We demonstrated a GIS application in developing a quick predictive model to study the globally vulnerable Fairy Pitta (Pitta nympha) in Taiwan. We compiled sighting data between 1982 and 2000, established a rule-based model to predict its distribution, and applied the predictive map to design a sampling protocol, conduced field surveys to evaluate the accuracy of the model and to obtain hotspots. The results showed that most known distribution of the Fairy Pitta occurred in low elevation, hilly and forested areas. The map predicted 21.6% areas of Taiwan suitable for the Fairy Pitta and 78% of them occurred in western Taiwan. A total of 511 pittas were detected during the 2001 survey that covered 4% areas of Taiwan or 14.3% of predictive areas, with a mean of 30.2% detection probability per grid cell (2 × 2 km in resolution). The adjusted data indicated that the overall accuracy of our model was increased to 40.3% with 290 qualified cells. Most of the new sightings of the Fairy Pitta arising from the 2001 field survey fell in our predictive areas with most of them occurring in western Taiwan. The probability of detecting pitta was highest in the active selection cells within predictive areas. Based on mean number of pitta detected per cell, the hotspots of the Fairy Pitta in Taiwan included three regions: the watershed of Shimen Reservoir within Hsinchu and Taoyuan County, Linnei of Yulin County and the watershed of Wusanto Reservoir in Tainan County. We concluded that the model provides quick and effective predictions for planning conservation strategies and is particularly useful for rare species.

Energy, climate, habitat heterogeneity, and human activity are important correlates of spatial variation in species richness. We examined the correlation between species richness and these variables using the birds that breed in northern Taiwan. We conducted general linear models (GLMs) and spatial correlation models to examine the relationship between bird species richness (BSR) and environmental variables. We found that normalized difference vegetation index (NDVI) was the most important predictor of BSR. We suggest productivity is the primary process of BSR. Additionally, we hypothesized that scale dependency might exist in the relationship between BSR and NDVI in Taiwan. Human population density, the second most important factor, was inversely correlated with BSR. The factor and BSR did not have similar response to NDVI, which contradicted observations in most of the previous studies on human population vs. species richness. We proposed that the human population density had an effect on NDVI, which in turn had an effect on BSR. Moreover, we hypothesized that the contradiction between our study and the previous studies might arise from a higher level of human disturbance in Taiwan than in other areas. The necessity of conserving native species in intensively developed lowlands of Taiwan cannot be overemphasized. Number of land cover type was another significant predictor of BSR. Habitat heterogeneity may have an effect on BSR in Taiwan.

Based on the database of 1986-2000 provided by the Wild Bird Federation Taiwan and a field assessment survey conducted between 1998 and 2000, four exotic species of cockatoos, belonging to the genus Cacatua (Psittacidae), were found in Taiwan. The Goffin’s Cockatoo (C. Goffini) and the Sulphur-crested Cockatoo (C. galerita) are more common than the White Cockatoo (C. Alba) and the Lesser Sulphur-crested Cockatoo (C. sulphurea). Most of the sightings were in single or small flocks occurring in or near metropolitan areas of western Taiwan. The birds built permanent roosting sites that were occupied by one to three species. The feral populations of the cockatoos in Taiwan have remained low but fairly stable, since they were introduced more than 20 years ago. Overall, they are not successful invaders.

Methods of sexing the White-rumped Munia Lonchura striata phaethontoptila were investigated in eastern Taiwan. Twenty-six individuals were captured and their physical parameters were measured in the hand. Distance calls emitted when the birds were released were also recorded. The sex of each bird was confirmed using a DNA sexing method in the laboratory. Among the morphological traits measured, the tails and wings of males were significantly longer than those of females. An increasing stepwise discriminant analysis was performed to determine sex on the basis of morphological characters, however, only 84.0% of individuals were sexed correctly by such analysis. Distance calls of the White-rumped Munia were very similar to those of the Bengalese Finch, Lonchura striata var. domestica, the domesticated strain of the White-rumped Munia. Two distinct distance calls were recorded from birds on release, corresponding to the sexual difference confirmed by DNA testing. It is concluded, therefore, that the difference in distance calls is a useful trait that facilitates separation of the sexes in the field.

The Taiwan Breeding Bird Survey (BBS Taiwan) is a national monitoring project with the aim of establishing a breeding bird population index for conservation. It was established as a citizen science project with the working group operating on a cross-organizational cooperation basis. From 2009 to 2012, BBS Taiwan has obtained data from more than 300 sampling sites and has reported on national population trends for more than 60 % of the diurnal breeding bird species in Taiwan. Descriptions of sampling design, survey methods, and current results are given in this chapter. With ongoing monitoring projects covering other taxa such as anurans, butterflies, bats, and reptiles, biodiversity observation networks in Taiwan are expected to provide critical information to aid conservation and climate change adaptation strategies, and also to increase public awareness of the importance of biodiversity.

Background Although Taiwan is an important hotspot of avian endemism, efforts to use available distributional information for conservation analyses are so far incomplete. For the first time, we present a hotspot analysis of Taiwanese breeding birds with sufficient sampling coverage for distribution modeling. Furthermore, we improved previous modeling efforts by combining several of the most reliable modeling techniques to build an ensemble model for each species. These species maps were added together to generate hotspot maps using the following criteria: total species richness, endemic species richness, threatened species richness, and rare species richness. We then proceeded to use these hotspot maps to determine the 5% most species-rich grid cells (1) within the entire island of Taiwan and (2) within the entire island of Taiwan but outside of protected areas. Results Almost all of the species richness and hotspot analyses revealed that mountainous regions of Taiwan hold most of Taiwan's avian biodiversity. The only substantial unprotected region which was consistently highlighted as an important avian hotspot is a large area of unprotected mountains in Taiwan's northeast (mountain regions around Nan-ao) which should become a high priority for future fieldwork and conservation efforts. In contrast, other unprotected areas of high conservation value were just spatial extensions of areas already protected in the central and southern mountains. To combine the results of our four hotspot criteria, we assessed which grid cells were the most valuable according to all four criteria. Again, we found the Nan-ao mountain regions to be important. We also showed that different hotspot criteria only partially overlapped and sometimes barely at all. Conclusions Therefore, to protect areas based on only one hotspot criterion (total species richness) would not protect areas based on other hotspot criteria (endemic species richness, threatened species richness, or rare species richness) in Taiwan.