The formation of red colobus-diana monkey associations under predation pressure from chimpanzees.

It is generally assumed that most primates live in monospecific or polyspecific groups because group living provides protection against predation, but hard evidence is scarce. We tested the antipredation hypothesis with observational and experimental data on mixed-species groups of red colobus (Procolobus badius) and diana monkeys (Cercopithecus diana) in the Taï National Park, Ivory Coast. Red colobus, but not diana monkeys, are frequently killed by cooperatively hunting chimpanzees. Association rates peaked during the chimpanzees'' hunting season, as a result of changes in the behaviour of the red colobus. In addition, playbacks of recordings of chimpanzee sounds induced the formation of new associations and extended the duration of existing associations. No such effects were observed in reaction to control experiments and playbacks of leopard recordings.     

Dyadic associations of red Colobus and diana monkey groups in the Taï National Park, Ivory Coast

Members of the genus Colobus have been observed to associate frequently with Cercopithecus monkeys in several African sites. In the Taï National Park, Ivory Coast, one group of western red colobus was found to be in association with one particular group of diana monkeys more than could be expected by chance (Holenweg et al., 1996). We show that dyadic association is not an idiosyncrasy of these two groups, but rather a pattern that is general for our study site. All five red colobus groups we studied were closely associated with diana monkeys during more than 60% of the time. Four groups had one particular diana partner group, the fifth two different partners. Apart from the red colobus, three more primate species, the olive colobus, Campbell's monkey, and the lesser spot-nosed monkey, were also strongly attracted to diana monkeys.     

Primate population dynamics over 32.9 years at Ngogo, Kibale National Park, Uganda

We present census data for eight primate species spanning 32.9 years along the same transect at Ngogo, Kibale National Park, Uganda, demonstrating major changes in the composition of the primate community. Correlated with an estimated decline of ～89% in the red colobus population was an increase in encounter rates with chimpanzee parties. Our data, along with the unusually high rates of predation by chimpanzees on red colobus at Ngogo and the fact that the chimpanzee community at Ngogo is the largest ever recorded, support the conclusion that the red colobus decline was caused primarily by chimpanzee predation. This seems to be the first documented case of predation by one nonhuman primate causing the population decline in another. We evaluated disease and interspecific competition as other possible causes of the red colobus decline, but judged them to be relatively insignificant compared with predation by chimpanzees. Notable changes in encounter rates with other primate species may have resulted from forest expansion. Those for mangabeys, redtails, and black and white colobus increased significantly. Encounter rates increased for l'Hoest's monkeys too, but the increased sightings may have been an artifact of increased habituation. Sightings of blue monkey and baboon groups declined. There was no significant change in encounter rates for all species combined. The Ngogo primate community seemed to be in a nonequilibrium state, changing from one dominated by two species, a folivore (red colobus) and a frugivorous omnivore (redtails), to one dominated by three species of frugivorous omnivores (redtails, mangabeys, and chimpanzees). This study demonstrates the importance of long-term monitoring in understanding population dynamics and the role of intrinsic variables in shaping the species composition of a community.     

The importance of incorporating imperfect detection in biodiversity assessments: a case study of small mammals in an Australian region

Aim Assessments of biodiversity are an essential requirement of conservation management planning. Species distributional modelling is a popular approach to quantifying biodiversity whereby occurrence data are related to environmental covariates. An important confounding factor that is often overlooked in the development of such models is uncertainty due to imperfect detection. Here, I demonstrate how an analytical approach that accounts for the bias due to imperfect detection can be applied retrospectively to an existing biodiversity survey data set to produce more realistic estimates of species distributions and unbiased covariate relationships. Location Pilbara biogeographic region, Australia. Methods As a component of the Pilbara survey, presence/absence (i.e. undetected) data on small ground‐dwelling mammals were collected. I applied a multiseason occupancy modelling approach to six of the most common species encountered during this survey. Detection and occupancy rates, as well as extinction and colonization probabilities, were determined, and the influence of covariates on these parameters was examined using the multi‐model inference approach. Results Detection probabilities for all six species were considerably lower than 1.0 and varied across time and species. Naïve estimates of occupancy underestimated occupancy rates corrected for species detectability by up to 45%. Seasonal variation in occupancy status was attributed to changes in detection for two of the focal species, while reproductive events explained variation in occupancy in three others. Covariates describing the substrate strongly influenced site occupancy for most of the species modelled. A comparison of the occupancy model with a generalized linear model, assuming perfect detection, showed that the effects of the covariates were underestimated in the latter model. Main conclusions The application of the multiseason occupancy modelling approach to the Pilbara mammal data set demonstrated a powerful framework for examining changes in site occupancy, as well as local colonization and extinction rates of species which are not confounded by variable species detection rates.     

Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.     

Long-term dynamics of wild primate populations across forests with contrasting protection in Tanzania

Anthropogenic activities driving tropical forests' loss imperil global biodiversity and provision of ecosystem services. In this context, systematic monitoring programs evaluating wildlife trends are essential. Non-human primates are relevant conservation targets since they represent vital components of tropical forests by serving as pollinators and seed dispersers. Here, we present primate group counts data collected over 19 years in a primate hotspot in Tanzania. We analyzed data with a hierarchical dynamic model accounting for imperfect detection that estimates local group abundance and temporal rates of change, to assess whether habitat protection explained trends of the arboreal and diurnal Peters' Angola colobus (Colobus angolensis palliatus), Udzungwa red colobus (Piliocolobus gordonorum), and Tanzania Sykes' monkey (Cercopithecus mitis subsp. moloneyi). We targeted populations occurring in two forest blocks with contrasting protection regimes, with one block impacted by targeted poaching of the two Colobus species. We found that these latter species were much less abundant in the more human impacted forest, underwent a rapid decline, and subsequently remained at low abundance and without signs of recovery once this forest was granted greater protection. Instead, Sykes' abundance did not differ between forests, and improved protection was associated with a slight increase in abundance. Age class composition for social groups of both Colobus species differed between forests, indicating altered births and survivorship rates in the impacted forest. Results suggest that targeted hunting can prevent recovery for several years and even after increased habitat protection. Our approach appears valuable to monitor population dynamics over the long term, highlighting species-specific variations in both vulnerability to anthropogenic disturbance and recovery patterns in primate populations.     

Primate population dynamics: variation in abundance over space and time

The rapid disappearance of tropical forests, the potential impacts of climate change, and the increasing threats of bushmeat hunting to wildlife, makes it imperative that we understand wildlife population dynamics. With long-lived animals this requires extensive, long-term data, but such data is often lacking. Here we present longitudinal data documenting changes in primate abundance over 45 years at eight sites in Kibale National Park, Uganda. Complex patterns of change in primate abundance were dependent on site, sampling year, and species, but all species, except blue monkeys, colonized regenerating forest, indicating that park-wide populations are increasing. At two paired sites, we found that while the primate populations in the regenerating forests had increased from nothing to a substantial size, there was little evidence of a decline in the source populations in old-growth forest, with the possible exception of mangabeys at one of the paired sites. Censuses conducted in logged forest since 1970 demonstrated that for all species, except black-and-white colobus, the encounter rate was higher in the old-growth and lightly-logged forest than in heavily-logged forest. Black-and-white colobus generally showed the opposite trend and were most common in the heavily-logged forest in all but the first year of monitoring after logging, when they were most common in the lightly-logged forest. Overall, except for blue monkey populations which are declining, primate populations in Kibale National Park are growing; in fact the endangered red colobus populations have an annual growth rate of 3%. These finding present a positive conservation message and indicate that the Uganda Wildlife Authority is being effective in managing its biodiversity; however, with constant poaching pressure and changes such as the exponential growth of elephant populations that could cause forest degradation, continued monitoring and modification of conservation plans are needed.     

Influence of chimpanzee predation on the red colobus population at Ngogo, Kibale National Park, Uganda

Frequent hunting of red colobus monkeys (Procolobus rufomitratus) takes place at all long-term chimpanzee (Pan troglodytes) study sites where both species are present. Red colobus are the most commonly selected prey of chimpanzees even when other monkey species are more abundant. In particular, the chimpanzee community at Ngogo, Kibale National Park, Uganda, preys heavily on red colobus monkeys: the chimpanzee hunting success rate is extremely high, and chimpanzees kill many individuals per successful hunt. Census data had suggested that the red colobus population is declining and that predation by chimpanzees may be contributing to this decline. In this paper, I address the impact of hunting on the red colobus population at Ngogo. To test the hypothesis that chimpanzee hunting is sustainable, I am using demographic data collected on red colobus monkeys over a period of 3 years, as well as fecundity and mortality data from previous studies of this species. I apply matrix models and vortex analyses using a sensitivity analysis approach to project future population development. Results show that current rates of hunting are not sustainable, but that chimpanzees are neither more “noble”, nor more “savage” than humans are, but that they also hunt to ensure maximum benefit without regard for the consequences for the prey population.     

Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling

Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult‐to‐detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species‐specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses.     

Impact of Commercial Hunting on Monkey Populations in the Taï region,Côte d'Ivoire1

We studied the impact of hunting on monkey species in the Taï National Park and adjacent forests in Côte d'Ivoire. The average wild meat consumption per capita per year was assessed from market surveys and interviews. We determined that the amount of primate wild meat being extracted in the Taï National Park and surrounding forests was 249 t in 1999. Hunting pressure was the highest on the larger primate species such as red colobus, Procolobus badius, black and white colobus, Colobus polykomos, and the sooty mangabey, Cercocebus torquatus atys. Estimates of population densities were based on line transect surveys. The maximum annual production of each species was calculated using the Robinson and Redford model (1991) and assuming unhunted conditions. Comparing current harvest levels with the maximum sustainable yield suggests that harvest of red colobus monkeys (Procolobus badius) is sustainable, whereas current off‐take of the black and white colobus (Colobus polykomos), the sooty mangabey (Cercocebus atys), diana monkeys (Cercopithecus diana), and Campbell's monkeys (Cercopithecus campbelli) exceeds sustainability by up to three times.     

Spatial patch occupancy patterns of the Lower Keys marsh rabbit

Reliable estimates of presence or absence of a species can provide substantial information on management questions related to distribution and habitat use but should incorporate the probability of detection to reduce bias. We surveyed for the endangered Lower Keys marsh rabbit (Sylvilagus palustris hefneri) in habitat patches on 5 Florida Key islands, USA, to estimate occupancy and detection probabilities. We derived detection probabilities using spatial replication of plots and evaluated hypotheses that patch location (coastal or interior) and patch size influence occupancy and detection. Results demonstrate that detection probability, given rabbits were present, was <0.5 and suggest that naïve estimates (i.e., estimates without consideration of imperfect detection) of patch occupancy are negatively biased. We found that patch size and location influenced probability of occupancy but not detection. Our findings will be used by Refuge managers to evaluate population trends of Lower Keys marsh rabbits from historical data and to guide management decisions for species recovery. The sampling and analytical methods we used may be useful for researchers and managers of other endangered lagomorphs and cryptic or fossorial animals occupying diverse habitats. © 2011 The Wildlife Society.     

Linking occupancy surveys with habitat characteristics to estimate abundance and distribution in an endangered cryptic bird

Accurate estimates of the distribution and abundance of endangered species are crucial to determine their status and plan recovery options, but such estimates are often difficult to obtain for species with low detection probabilities or that occur in inaccessible habitats. The Puaiohi (Myadestes palmeri) is a cryptic species endemic to Kaua?i, Hawai‘i, and restricted to high elevation ravines that are largely inaccessible. To improve current population estimates, we developed an approach to model distribution and abundance of Puaiohi across their range by linking occupancy surveys to habitat characteristics, territory density, and landscape attributes. Occupancy per station ranged from 0.17 to 0.82, and was best predicted by the number and vertical extent of cliffs, cliff slope, stream width, and elevation. To link occupancy estimates with abundance, we used territory mapping data to estimate the average number of territories per survey station (0.44 and 0.66 territories per station in low and high occupancy streams, respectively), and the average number of individuals per territory (1.9). We then modeled Puaiohi occupancy as a function of two remote-sensed measures of habitat (stream sinuosity and elevation) to predict occupancy across its entire range. We combined predicted occupancy with estimates of birds per station to produce a global population estimate of 494 (95% CI 414–580) individuals. Our approach is a model for using multiple independent sources of information to accurately track population trends, and we discuss future directions for modeling abundance of this, and other, rare species.     

Inferring wildlife poaching in southeast Asia with multispecies dynamic occupancy models

Determining the ‘space race’ between co-occurring species is crucial to understand the effects of interspecific interactions on the extinction risk of species threatened by poachers and predators. Dynamic two-species occupancy models provide a flexible framework to decompose complex species interaction patterns, while accounting for imperfect detection. These models can describe poachers–wildlife interactions, as they allow estimating occupancy, extinction and colonisation probabilities of wildlife conditional on the occurrence of poachers and vice versa. We applied our model to a case study on wildlife poaching in the eastern plains of Cambodia. We used co-occurrence data extracted from the database of the SMART partnership to study the distribution dynamics between poachers and six ungulate species pooled together into the tiger prey guild. We used four years of survey data reporting the locations of snares and of presence signs of the ungulates recorded by rangers during their monthly multi-patrolling sessions. Our results showed that a substantial proportion of the sites occupied by ungulate species went extinct over the years of the study while the proportion of sites colonised by poachers increased. We also showed, for the first time, that spatio-temporal heterogeneity in the patrolling effort explains a great deal of the variation in the detection of poachers and ungulates. Our approach provides practitioners with a flexible and robust tool to assess conservation status of species and extinction risk of wildlife populations. It can assist managers in better evaluating, learning and adapting the patrolling strategies of rangers.     

Environmental DNA (eDNA) Sampling Improves Occurrence and Detection Estimates of Invasive Burmese Pythons

Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models.     

Recognition of Predator and Competitor Calls in Nonhuman Primates and Birds: a Preliminary Report

Field playback experiments were conducted in the Kibale Forest, Uganda to determine whether three monkeys (redtail monkeys, blue monkeys, and red colobus monkeys) and one bird (great blue turaco) [1] respond with flight and/or increased vigilance to exemplars of calls given by potential predators (crowned eagle, chimpanzee) and [2] respond differently to food competitors vs. noncompetitors (black-and-white casqued hornbill, chimpanzee vs. red colobus). Because the chimpanzee is both a potential predator of all subject species and a food competitor of blue and redtail monkeys and great blue turacos, we also examined whether chimpanzee calls induced responses appropriate to potential predation or competition. Each subject species responded differentially to the calls of potential predators, competitors and noncompetitors. Thus, acoustic cues appeared sufficient for the detection of predators and competitors.     

Primates and Cameras

Field-based primate studies often make population inferences using count-based indices (e.g., individuals/plot) or distance sampling; the first does not account for the probability of detection and thus can be biased, while the second requires large sample sizes to obtain precise estimates, which is difficult for many primate studies. We discuss photographic sampling and occupancy modeling to correct for imperfect detection when estimating system states and dynamics at the landscape level, specifically in relation to primate ecology. We highlight the flexibility of the occupancy framework and its many applications to studying low-density primate populations or species that are difficult to detect. We discuss relevant sampling and estimation procedures with special attention to data collection via photographic sampling. To provide tangible meaning to terminology and clarify subtleties, we use illustrative examples. Photographic sampling can have many advantages over observer-based sampling, especially when studying rare or elusive species. Combining photographic sampling with an occupancy framework allows inference to larger scales than is common in primate studies, addresses uncertainty due to the observation process, and allows researchers to examine questions of how landscape-level anthropogenic changes affect primate distributions.     

Market Hunting in the Taï Region,Côte d’Ivoire and Implications for Monkey Populations

We studied the effect of market hunting on primate species in the Taï National Park and adjacent forests in Côte d’Ivoire. We assessed the impact of hunting by comparing the calculated maximal reproduction rate with the current off-take rate. We assessed the average bushmeat consumption per capita/per year from weekly investigations on bushmeat available in 88 bushmeat restaurants and markets over a 12-mo period in 1999. We derived data on preferences for particular game species from interviews of 162 bushmeat consumers, 25 subsistence hunters and 3 groups of professional hunters. Hunting pressure was highest on the larger primate species such red colobus (Procolobus badius), black- and- white colobus (Colobus polykomos) and sooty mangabeys (Cercocebus atys). The amount of primate bushmeat extracted from the Taï National Park and surrounding forests was 249,229 kg in 1999. We estimated population densities using line transect surveys. By referring to current population densities we calculated the maximum production of each species using the Robinson Redford model (2001) and assuming unhunted conditions. A comparison of current harvest levels with maximum production suggests that harvest of Procolobus badius is sustainable, whereas current off-take of Colobus polykomos, Cercocebus atys, Cercopithecus diana (diana monkey) and C. campbelli (Campbell’s monkeys) exceeds sustainability by ≤3 times. We recommend that wildlife managers promote programs that encourage the production of domestic animals as a substitute for wild meat.     

Modeling the occupancy of sympatric carnivorans in a Mediterranean ecosystem

Site occupancy provides a reasonable estimate of population status and trends, and it also provides an unbiased, cost-effective alternative method for large-scale, multispecies monitoring programs. In this study, we used camera-trapping data to determine carnivoran occupancy and associated environmental factors in Serra da Malcata Nature Reserve, Portugal. The study was intended as a precursor of further long-term multispecies monitoring programs. We estimated carnivoran species occupancy using a likelihood-based method, using the software PRESENCE. The major conclusions of the study were (1) fox occupancy tends to be independent of environmental factors; (2) stone marten occupancy is related with habitat variables, landscape structure, and preys; (3) common genet occupancy is related to broad leaf formations and preys; and (4) mongoose occupancy is higher in extensive areas of shrub habitats. Methodologically, we demonstrated the importance of modeling detection probabilities for species with low or variable detection rates. In the future, monitoring programs could benefit from incorporating estimates of detection probabilities into their design and analysis.     

Primates in Human-Modified and Fragmented Landscapes: The Conservation Relevance of Modelling Habitat and Disturbance Factors in Density Estimation

Accurate density estimations of threatened animal populations is essential for management and conservation. This is particularly critical for species living in patchy and altered landscapes, as is the case for most tropical forest primates. In this study, we used a hierarchical modelling approach that incorporates the effect of environmental covariates on both the detection (i.e. observation) and the state (i.e. abundance) processes of distance sampling. We applied this method to already published data on three arboreal primates of the Udzungwa Mountains of Tanzania, including the endangered and endemic Udzungwa red colobus (Procolobus gordonorum). The area is a primate hotspot at continental level. Compared to previous, ‘canonical’ density estimates, we found that the inclusion of covariates in the modelling makes the inference process more informative, as it takes in full account the contrasting habitat and protection levels among forest blocks. The correction of density estimates for imperfect detection was especially critical where animal detectability was low. Relative to our approach, density was underestimated by the canonical distance sampling, particularly in the less protected forest. Group size had an effect on detectability, determining how the observation process varies depending on the socio-ecology of the target species. Lastly, as the inference on density is spatially-explicit to the scale of the covariates used in the modelling, we could confirm that primate densities are highest in low-to-mid elevations, where human disturbance tend to be greater, indicating a considerable resilience by target monkeys in disturbed habitats. However, the marked trend of lower densities in unprotected forests urgently calls for effective forest protection.     

Primate Community Dynamics in Old Growth Forest over 23.5 Years at Ngogo,Kibale National Park,Uganda: Implications for Conservation and Census Methods

Few data exist regarding long-term changes in primate populations in old-growth, tropical forests. In the absence of this information, it is unclear how to assess population trends efficiently and economically. We addressed these problems by conducting line-transect censuses 23.5 years apart at the Ngogo study area in Kibale National Park, Uganda. We conducted additional censuses over short time intervals to determine the degree to which the temporal distribution of censuses affected estimates of primate numbers. Results indicate that two species, blue monkeys and red colobus, may have experienced significant reductions over the past 23.5 years at Ngogo. In contrast, five other species, baboons, black-and-white colobus, chimpanzees, mangabeys, and red-tailed guenons, have not changed in relative abundance. Additional findings indicate that different observers may vary significantly in their estimates of sighting distances of animals during censuses, thus rendering the use of measures of absolute densities problematic. Moreover, censuses conducted over short periods produce biased estimates of primate numbers. These results provide guidelines for the use of line-transect censuses and underscore the importance of protecting large blocks of forests for primate conservation.