Madagascar Forest Conservation Programme

Nosy Be, Madagascar

Phase 191 Science ReportJanuary - March 2019

George Syder Research Officer (RO)

Contents

1 Introduction 21.1 Madagascar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.1.1 Geologic Origins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.1.2 Modern Biogeography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Measuring Biodiversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Study Area 32.1 ’Big Island’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.1.1 Sambirano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.2 Phase 191 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.3 Survey Routes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.4 Habitat Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

3 Projects 53.1 Lemur Abundance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.1.1 Lemurs on Nosy Be . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.1.2 Nocturnal Lemur Survey Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.1.3 Nocturnal Lemur Survey Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3.2 Black Lemur Survey Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.3 Black Lemur Survey Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.3.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93.4 Herpetofauna abundance and species richness . . . . . . . . . . . . . . . . . . . . . . . . . 10

3.4.1 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103.4.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103.4.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4 Avifauna diversity and abundance 13

5 Methods 13

6 Results 14

7 Discussion 15

8 Invertebrate Inventories 158.1 Butterflies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168.2 Spiders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168.3 Beetles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

9 Summary 17

10 Future Work 17

11 References 18

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1 Introduction

1.1 Madagascar

”Continental Island of the first rank”— (Wallace1892). Most animals and plants on Madagascar arefound nowhere else on earth (Goodman2005, Hobbes2008, Phillipson2006). The island’s unique speciesare nested in ancient clades that host endemism up to the family level (e.g. Callmander2011). This hasled some to claim that higher taxa distinctness leaves Madagascar peerless in global biological uniqueness(Ganzhorn2014).Modern estimates hold that over 90% of Madagascar’s endemic animals live in, or rely on forests (Du-fils2003). Although our understanding of the historic relationship between Madagascar’s human popu-lation and the island’s forests is mired in conflicting interpretations and innuendo (Kline2002), humanshave undoubtedly shaped significant aspects of Madagascar’s modern vegetative cover (Randrianja2009).Forest clearance for agriculture using methods such as ‘tavy’ (slash and burn) and oxen grazing are cen-tral to Malagasy culture, widely practiced, and thought to reduce biodiversity (Clark2012, Gade1996,Marcus2001). The tavy system consists of primary or secondary forests being cut and burnt for eithercropland rice and root crops to be cultivated, it is Eastern Madagascar’s predominant land use prac-tise and is the major cause for upland deforestation in the region (Styger2007). In addition to this,international natural resource extraction and its associated politics has also undoubtedly contributed toMadagascar’s decline in woodland cover (Scales2015), with a loss of over 70% of its primary vegetationcover (Myers2000). The above factors, exacerbated by stochastic socioeconomic climes across Madagas-car have largely contributed to the island being classified as a biodiversity ’hotspot’ (Myers2000) andbeing considered a global conservation priority (Goodman2005, Mittermeier2005).

1.1.1 Geologic Origins

Much of Madagascar’s extraordinary biological distinctness is thought to have arisen due to its isolationfrom other landmasses, which has lasted at least 90 million years (Storey1995). Compounded by theCretaceous–Tertiary extinction event (K–T) ∼ 65 million years ago (mya) (Alvarez1980), geographicisolation has allowed Madagascar’s taxa to radiate into previously impoverished niche space (Ali2011,Fortey1999, Renne2013).Throughout the latter half of the 20th century, the role of dispersal in the post-Mesozoic faunal coloni-sation of Madagascar was largely ignored in favour of a vicariance dominated narrative (Yoder2006).The first years of the 21st century have seen this status quo reversed; current thinking is that mostof Madagascar’s basal fauna stocks originated from Cenozoic colonisation events from 65 million yearsago onwards (Salmonds2012, Salmonds2013). Fossil records buttress this model by revealing that mostextant Malagasy vertebrate taxa were not present during the Cretaceous (Krause1997, Krause1998,Krause1999) hence their arrival must have been later. However, some clades are known to have survivedfrom Madagascar’s shared plate tectonic history with Gondwanaland (Gaffney2003, Noonan2006).Stochastic dispersal post-K–T has given rise to peculiar taxonomic assemblages on Madagascar (e.g.Poux2005, Reinthal1991), where a handful of speciose radiations make up most of the fauna (Bossuyt2001,Nagy2003, Vences2004) and entire animal groups, such as large mammals, are absent. However, humandriven extinctions of certain taxa during the Holocene may compound our ability to assess ’natural’patterns of Madagascan biodiversity (Crowley2010). Nevertheless, modern biological communities onMadagascar are widely thought to be unique in structure and composition (Ganzhorn2014, Horvath2008,Reddy2012, Salmonds2012, Salmonds2013).

1.1.2 Modern Biogeography

Often cited as a pseudo-continent (Wit2003), Madagascar is the world’s fourth largest island (587, 000km2),lying ∼ 400km east of mainland Africa in the Indian Ocean. Madagascar’s topography is dominated byan eastern massif running north-south, dividing the island into two slopes: a steep eastern escarpmentand a gentler western slope (27% and 73% of land cover respectively: Ganzhorn2014). This topographydetermines large aspects of moisture deposition across Madagascar. Humid prevailing winds rolling in offthe Indian Ocean are forced upward by eastern mountains and unload precipitation on the east coast andcentral highlands; western Madagascar is left in a seasonal rain shadow and experiences pseudo-monsoonconditions (Jury2003). What results is a fine-grain diversity of microclimes: discrete abiotic pockets ofdifferent weather conditions (Dewar2007, Rakoto2009). These heterogeneous moisture patterns shapemuch of Madagascar’s local landscape diversity. Although ∼ 65% of the island’s land cover is savannah

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(Moat2007), habitat mosaics of scrub, wetland, and forests typify most regions (Mayaux2004). Thecentrepieces of these landscapes are scattered woodland blocks; forest archipelagos that support most ofMadagascar’s species (Dufils2003).The unique structure, composition, and history of Madagascar’s biological communities leaves them asexquisite examples of radiation in isolation (Glaw2007, Herrera2017), and bolster calls for conservationof these ecosystems.

1.2 Measuring Biodiversity

More biodiverse communities are considered to be ecologically healthier; generally having greater stabil-ity, productivity, and resistance to disturbance (Levin2013, Purvis2000). Thus, measuring biodiversitycan provide insights into the condition of biological communities, track changes over space and time, andinform practical management and conservation (Casey1999, Gotteli2013).Estimating biodiversity provides a snapshot in biological time but regular and consistent repeat measurescan provide a window onto the trends and trajectories of species in an area with reference to externalfactors, such as human driven reordering of biological communities (Magurran2010). Ergo, at the begin-ning of this, our project’s new five-year research plan, we build surveys around a framework of measuringthe abundance and proportions of various taxa in our research area over time; various estimates thatdenote richness and evenness will be made at least once per dry and wet season for core animal clades(lemurs, reptiles and amphibians). In exploring finer-grained aspects of ecological dynamics we hope toexpand our repertoire of surveys to include habitat descriptions, more complete inventories of terrestrialinvertebrates, and ecomorphological investigations of certain reptiles. Further, we aim to measure dif-ferent aspects of human disturbance in our study area and to pair this data with that of our ecologicalinvestigations. It is hoped that elucidating these relationships, and others, will not only develop a morecomplete understanding of these ecosystems but also spread awareness of these forests and support futureconservation management in the area if required.

2 Study Area

2.1 ’Big Island’

The Madagascar Frontier project (MGF) is currently located on Nosy Be, Madagascar’s largest offshoreisland (25,000 ha), Nosy Be lies ∼ 8km from the mainland and is itself part of an offshore archipelagoof several islands and many more small islets (figure 1).

Within Madagascar, Nosy Be is a relatively developed area. The island’s thriving tourist industryhas fuelled the development of several large holiday resort areas that provide a large proportion of theislands 75,000 inhabitants a sustainable income. Ecotourism on Nosy Be takes the form of guided toursof the island’s forests or seas; these are very popular as Nosy Be has a large area of pristine woodlandand has several coral reefs in its coastal waters.The MGF study area is located at the southeast tip of Nosy Be, on a peninsula bordered by LokobeNational Park. The small adjacent village of Ambalahonko has a population of ∼ 100 people that arelargely a subsistence community. No road access exists for this area; hence, small local boats are theonly method of reaching our study area.

2.1.1 Sambirano

Named after a mainland watershed, the Sambirano region is a semi-distinct biogeographic domain ofwhich Nosy Be occupies the northern extreme locality. This region is a transitional zone between thedry deciduous forests of western Madagascar and the humid eastern rainforests. As such, characteristicsof both habitats are found on Nosy Be. This transitional arrangement defines much of the ecology inour research area.

2.2 Phase 191

Phase 191 runs for the first quarter of 2019, from January – March. In Madagascar this is in the middleof the rainy season (Glaw2007, Behrens2016), and despite an uneven start in precipitation to 2019, withnotably extending drier periods (NOAA2019), rains, cyclones, and a reduction in personnel have impededdata collection. Unless otherwise stated, data analysed in this report has been collected between 17thDecember 2018 – 15th March 2019.

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Figure 1: Map showing Nosy Be, its surrounding islands, and MGF’s camp

2.3 Survey Routes

MGF has 13 terrestrial survey routes that run through forests in our research area, representing eitherPrimary (four routes), Secondary (5), and Degraded (4) habitat types. Each route is 400m in lengthand present on pre-existing forest trails, many are used extensively by local populations to access theforest or other human populations. Routes run as straight as possible, to (a) reduce variation in visualoverlap between observers, i.e. over/under-surveying on bends (b) simplify routes to flatten the learningcurve for new researchers attempting to memorise the complex network of forest trails in our study area.Routes run along a gradient of human disturbance where many see a significant and regular amount offootfall, yet on others, people are rarely, if ever, encountered. We measure the human use of routes to pairwith data from ecological surveying. Routes are predominantly used to maintain long-term biodiversitymonitoring projects on herpetiles and lemuriforms.

2.4 Habitat Types

Currently, MGF separates the research area into three broad habitat types:Primary: Mostly native forest with little anthropogenic disturbance, characterised by a high canopy,often with little understory (Fig. 2a).Secondary: A mixture of native and planted trees, medium canopy height with thicker understory (Fig.2b).Degraded: Mostly open forest with high anthropogenic disturbance, canopy height varies with a mixtureof planted trees and new growth shrubs, forest cover highly variable throughout the year (Fig. 2c).

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Figure 2: Examples of different habitat types found throughout the research area. From left toright: a. Primary, b. Secondary, c. Degraded.

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3.1 Lemur Abundance

Lemuriforms are old world prosimians endemic to Madagascar, and perhaps the most famous of theisland’s fauna. Placing their date of divergence from the other primates is still the subject of robustscientific debate; some studies argue this is around 60 million years ago (Yoder2006, Horvath2008), whileothers have suggested dates tens of millions of years later (Godinot2006, Sussman2003). Nevertheless,most authors on the subject agree that this date was after Madagascar split from India. Hence, lemurs arethought to have colonised the island sometime later, most likely their ancestors being carried across frommainland Africa on vegetation rafts (Tattersall2006). Once on mainland Madagascar, lemurs underwentseveral million years of adaptive innovation and radiated into diverse niche space provided by the island’sunique landscape and climatic conditions (Herrera2017). Today there are over 100 species of lemur onMadagascar (Behrens2016).Modern lemurs are near exclusively arboreal and are commonly found in all layers of the Malagasycanopy (Behrens2016). From the world’s smallest primate, the mouse lemur, to the largest extantlemur, the Indri, these animals occupy a broad range of ecological roles within their respective habitats(Herrera2017). While lemurs are generally predominantly frugivores, some species commonly feed onleaves, nectar, and opportunistically predate smaller animals such as small lizards (Garbutt2007).

3.1.1 Lemurs on Nosy Be

Three lemur species are found on Nosy be: the black lemur (Eulemur macaco macaco), Hawk’s sportivelemur (Lepilemur tymerlachsonorum), and Clair’s mouse lemur (Microcebus mamiratra). These specieshave different niches and life histories and may use their habitat in different ways. For instance, bothL. tymerlachsonorum and M. mamiratra are nocturnal and are found in relatively small groups (of-ten solitary) (Harcourt1990, Seiler2015); this is not true for diurnal, group-living E. macaco macaco(Behrens2016). Thus, impacts from external stimuli such as human disturbance or environmental catas-trophe may be different among these species.We aim to address this question.

Aims

• Determine if lemuriform abundance varies in our research area as a function of habitat type.

• Determine if lemuriform abundance varies in our research area as a function of human disturbance.

3.1.2 Nocturnal Lemur Survey Method

During phase 191, lemur surveys were walked along thirteen pre-existing 400 m routes that run throughour study area. Teams of trained research staff walked these routes at a regular pace (roughly 500 m/perhour) and visually scanned the path and surrounding area for lemurs. Observers left at least 2 m betweeneach other. When an individual was spotted the survey leader—a member of research staff—identifiedthe species and confirmed the group size and measurements. A distance from the path was measuredby an estimate to the nearest metre. Height of individuals was estimated by eye as most lemurs were

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well above a height that could be recorded using a tape measure. During Phase 191, only night surveyswere conducted, starting at between 1900 to 1930 hours, roughly one hour after sunset; electric light wasused to assist observations during night routes. As estimates are given for height and distance, accuracymay be reduced, however, as a trained member of staff is present on all surveys, it is assumed precisionwill be maintained. Data was then analysed using R studio (R Core Team2015) with packages plyr(Wickham2011), vegan (Oksanen2019), and stats.

3.1.3 Nocturnal Lemur Survey Results

During Phase 191, MGF performed 18 nocturnal lemur transects. With eight surveys being carried outon degraded forest routes, five on secondary, and five on primary routes. This surveying identified 107individuals; 98 sportive and nine mouse lemurs. Sportive lemurs were observed far more frequently thanmouse lemurs, with an average of 5.44 ± 3.80 per survey compared 0.50 ± 0.96 per survey. Sportivelemurs were observed with the highest average number of individuals on degraded routes (7.63 ± 3.71per survey), whereas mouse lemurs were most often observed on primary routes (0.80±1.17 per survey).Based on Shapiro-Wilks test for normality, the number mouse lemurs recorded per survey is not normallydistributed (W = 0.567, P < 0.01), whereas the number of sportive lemurs recorded per survey is (W =0.933, P = 0.22).As stated, degraded routes had the highest average number of individuals on degraded routes. Secondaryroutes had the second highest (5.00±3.39), followed by primary routes (2.40±2.19; Fig. 3). A parametricOne-way ANOVA showed that the difference between this groups was not significant (F = 3.657, df =2, P = 0.05).

Figure 3: Barplot showing average and standard deviation of number of sportive lemurs persurvey for each forest type.

For mouse lemurs (Fig. 4), primary routes had a greater number of individuals per survey (0.80±1.31)than degraded routes (0.63± 1.06), whilst secondary routes had no individuals on any survey. The non-parametric test, Kruskal-Wallis one-way ANOVA on ranks, showed no significant difference in the numberof mouse lemurs per habitat type (X2 = 2.478, df = 2, P = 0.29).

3.2 Black Lemur Survey Method

For Phase 191, the method for measuring the abundance of black lemurs has been altered slightly. Inphases 184 and earlier, methodology followed that of the nocturnal lemur survey, however based on theresults of 184, where data was possibly skewed by the presence of two large groups, methodology hasresponded accordingly. Phase 191 began a foray into shifting methodology from sample transects to

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Figure 4: Barplot showing average and standard deviation of number of mouse lemurs persurvey for each forest type.

a census of the survey area. Rather than following the 400 metre transects, all available paths withinthe survey area were utilised, with a trained-member of staff looking for lemur sign and listening forcommunication and alarm calls. Once a troop was encountered, the survey team take GPS coordinates,and the local habitat classified. Coupled with distance and height estimates, and bearing from point,using a compass. As well as this, a trained staff member would begin assigning each individual an age,gender, and fur and body condition score, adapted from Millette et al. (2015). Using QGIS, an overlayof GPS data of troop encounters, with information about troop composition and local habitat was com-bined with a base map of the region. Each troop encounter was analysed and given a troop ID based ontroop composition, location, and identified individuals. Also, as each troop is capable of moving betweenhabitat types, the survey area was split into three distinct areas:

Ambalahonko/Antafondro Region: taking up the central and eastern portion of the survey area,characterised by a mosaic of open areas with degraded and secondary forests, high amounts of anthro-pogenic disturbance from agriculture and villages.Ampasipohy Community Forest: a secondary forest encompassing the northern part of the surveyarea, receives some disturbance for tourism, with potential issues including feeding of lemurs.Lokobe Adjacent Forest: a mixture of primary and secondary forest with relatively low disturbance.

An 85-metre buffer was created around the paths (the greatest distance from the path a troop wasidentified from), from this, the area surveyed was calculated. Troop density and average troop sizes werethen calculated and analysed using Microsoft Excel, and R studio (R Core Team2015) with packagesplyr (Wickham2011), vegan (Oksanen2019), and stats.

3.3 Black Lemur Survey Results

During Phase 191, data was collected using the described methodology between 15th January-15thMarch. Over that period, 23 troop encounters, of 13 different troops occurred. Ten in the Ambala-honko/Antafondro Region (AAR), six in the Ampasipohy Community Forest (AFC), and seven in theLokobe Adjacent Forest (LAF) (Fig. 5). Encounters of each troop ranged from four (one troop) to one(five troops).

Four troops were identified in the AAR, four in AFC, and five in LAF. With the area surveyed being0.757 km2 for AAR, 0.143 km2 for AFC, and 0.457 km2 for LAF. The calculated troop densities forthese areas are 5.28/km2 for AAR, 27.97/km2 for AFC, and 10.94/km2 for LAF (Fig. 6). Using troopdensity for the entire area (9.57/km2) as the expected values, pairwise chi-squared testing was carried

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Figure 5: Map of troop encounters, with north arrow and scale bar. Each region is representedby a different shape: Ambalahonko/Antafondro Region (squares), Ampasipohy Community For-est (circles), and Lokobe Adjacent Forest (triangles). Each troop within the region is assigneda different colour. Black lines indicate routes. Created in QGIS, OpenStreetMap base map.

out to determine if there was a significant variation from the expected values between areas. The resultsof the chi-square test showed there was no significant variation in troop density between AAR and LAF(X2 = 2.123, df = 1, P = 0.15), but significant variations between AFC and both AAR (X2 = 37.232,df = 1, P < 0.01), and LAF (X2 = 35.495, df = 1, P < 0.01).

Figure 6: Barplot showing black lemur troop density for each forest area (AAR: Ambala-honko/Antafondro Region, ACF: Ampasipohy Community Forest, LAF: Lokobe Adjacent For-est) and the overall troop density with significance between groups indicated.

The maximum size for each troop ranged from three to 16 with and an average of 7.46 ± 3.20. AAR

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had the largest average troop size (10.50± 3.84), followed by LAF (6.20± 1.94), then ACF (6.00± 0.714;Fig. 7). Based on Shapiro-Wilks test for normality, troop size is not normally distributed (W = 0.849,P = 0.02). The non-parametric test, Kruskal-Wallis One-way ANOVA on ranks, showed that there wasno significant difference in troop size based on area (X2 = 3.742, df = 2, P = 0.15).

Figure 7: Barplot showing the average and standard deviation of troop sizes for each forest area(AAR: Ambalahonko/Antafondro Region, ACF: Ampasipohy Community Forest, LAF: LokobeAdjacent Forest).

3.3.1 Discussion

In Phase 191, sportive lemurs showed greater abundance in degraded transects, however this result wasnot significant, which differs from previous phases. This is an unexpected result due to the results ofprevious phases and similar studies (Seiler2014), however this is most likely due to a lower survey output,reducing the strength of statistical tests.Once again, mouse lemur occurrences are very low, this can be attributed to their cryptic nature and sta-tus as a critically endangered animal. Encouragingly, however, they have been located in both degradedand primary forests, which may suggest they have some resilience to habitat degradation. However,Ganzhorn and Schmid (1998) identified that non-primary habitats result in lower densities, body mass,and fitness.Due to the changes in methodology over phase 191, the dataset for black lemurs may not be as ro-bust which may have contributed to the results differing from previous phases, such as phase 184 whichshowed a significantly greater occurrence of black lemurs on primary routes (best represented by LAF).Furthermore, the addition of two new secondary routes mid-way through 184, which are within the areaof the ACF, may not have been sufficiently surveyed to portray the true density that they have indicatedduring phase 191. Overall, a change in results is encouraging for the new methodology, which suggeststhe old methodology was not accurate enough to truly represent black lemur distribution and populationwithin the research area. Continuing surveying of this method can build upon the current dataset, pro-ducing data on ranging habitats; in addition to this, observations of the use of different tree species maypossibly be incorporated. Furthermore, the current region separation and their descriptions are basedon personal observations and experience, collection of data regarding disturbance will be required tocompound this separation. As the study continues, and the dataset increases, it would be expected thatmore individuals, in lower troop densities, would be found in primary regions (LAF) when comparedto fragmented areas (AAR, Bayart2005, Schwitzer2007). In conclusion, the change in methodology hasallowed for more in-depth observations to be carried out, which can produce more important informationfor the future of black lemur conservation in the region.

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3.4 Herpetofauna abundance and species richness

Reptiles and amphibians are by far the most diverse groups of vertebrates on Madagascar (Glaw2007).These hold such enigmatic clades as the leaf-nosed snakes and several chameleons—one of a handful oftaxa thought to have dispersed across continents from a Madagascan epicentre. Shaped by Madagascar’sgeographic isolation and unique ecological pressures, herpetofauna on the island has taken on a uniqueform, full of peculiarities not found anywhere else on earth with 100% of amphibians and 92% of terres-trial retiles endemic to the island (Glaw2007).All wild amphibians on Madagascar are frogs. These species are near exclusively restricted to wood-land habitat, not being able to withstand long periods in direct sunlight and needing humid conditionsand access to water bodies for reproduction. As such, amphibian diversity is heavily concentrated inthe island’s eastern rainforests (Glaw2007). The heterogeneity of these habitats has helped catalysemicroendemism of frogs along Madagascar’s eastern coast. These amphibians fill broad niche ranges intheir respective habitats, from leaf litter dwelling Stumpfia, to Boophids capable of bounding betweenhigh tree tops, Madagascar’s frogs can be very locally abundant and occupy many key positions in theirtrophic webs (Glaw2007).Reptiles on Madagascar are generally less restricted to the island’s forests, their scaled dermis allowsthem to thrive in areas of intense ultraviolet exposure and to store water so as to go much longer betweenhydrating. Therefore, Madagascar’s reptiles can occupy areas of scrub and savannah—the most commonhabitat type on the island. These reptiles include a number of charismatic and well-known species, suchas the chameleons; Madagascar holds ∼ 50% of the globes chameleon species (Glaw2007).Most reptiles and amphibians on Madagascar are found nowhere else on earth (Glaw2007). Owingpredominantly to a unique pattern of stochastic transoceanic dispersal to the island after biological im-poverishment ∼ 65 million years ago (Ali2011, Alvarez1980), peculiar assemblages have taken hold; forinstance, Madagascar is the global hub for chameleon species diversity, yet hosts no salamander species(Glaw2007). These disharmonic biological communities came about due to a few speciose taxa radiatinginto unoccupied niche space on Madagascar—they now typify the ecology of the island (Goodman2005,Poux2005, Salmonds2013). Investigating the ecology of these strange communities can provide uniquelenses onto evolutionary biology, consequences of environmental change, and practical conservation po-tential.

Aims

• Determine if herpetile abundance and species diversity varies in our research area as a function ofhabitat type

• Determine if herpetile abundance and species diversity varies in our research area as a function ofhuman disturbance level

3.4.1 Methods

During phase 191 herpetofauna surveys were walked along thirteen pre-existing 400 m routes that runthrough our study area. Teams of trained research staff walked these routes at a regular pace and visuallyscanned the path and surrounding area for reptiles and amphibians. Observers left at least 2 m betweeneach other. When an individual was spotted the survey leader—a member of research staff—identifiedthe species and confirmed the group size and measurements. A tape measure was used to measurethe distance from path and height above ground, if individuals were too high the height above groundwas estimated by eye. Both day and night surveys were conducted; electric light was used to assistobservations during night routes. Casual observations were also recorded to understand the presence ofdifferent species in the area.

3.4.2 Results

During Phase 191, 19 herpetofauna surveys (10 diurnal and 9 nocturnal) were walked, represented byseven surveys on degraded routes, seven on secondary routes, and 5 on primary routes. Over the course ofthese surveys, 161 individuals from 22 species were recorded. The most recorded species was Zonosaurusrufipes, with 32 individuals (20% of total) recorded across six surveys, representing all three forest types.Six species were recorded a single time, including the locally rare Trachylepis elegans and the inconspic-uous Uroplatus ebenaui and Lygodactylus madagascariensis. Despite Phase 191 encompassing the heightof the rainy season, only three species of frog were recorded (Boophis tephraeomystax, Mantella ebenaui,

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and Ptchyadena mascareniensis), however this equated to 17% of all records, compared with only 2%for Phase 184. In total, 32 species of herpetofauna were observed in January, February, and March.Included in the nine species observed, but not recorded on surveys, was one species of frog (Gephroman-tis pseudoasper), one chameleon (Calumma boettgeri), one gecko (Hemidactylus mercatorius) and sevensnakes (including both Boas, Acrantophis madagascariensis and Sanzinia madagascariensis).Shapiro-Wilks test for normality was performed on species richness, total abundance and species diver-sity for each survey. Species richness (W = 0.926, P = 0.14) and total abundance (W = 0.967, P = 0.72)were normally distributed, whereas species diversity (W = 0.873, P = 0.02) was not. Based on this, aparametric One-Way ANOVA was performed to investigate if there was a significant difference betweenspecies richness and total abundance based on forest type, whilst species diversity was tested using thenon-parametric Kruskal-Wallis One-Way ANOVA.Species richness was highest along degraded transects with an average 4.001.63 species per survey. Pri-mary routes showed the second highest species richness (3.80 ± 0.84), with secondary routes having thelowest (3.43 ± 1.72). Based on the results of the One-way ANOVA (F = 0.256, df = 2, P = 0.78), nosignificant difference was found between the average species richness of each forest type (Fig. 8).

Figure 8: Barplot showing average and standard deviation of herpetile species richness persurvey for each forest type.

Total abundance was highest in primary routes (9.60±4.83), followed by secondary routes (8.29±6.78),with degraded routes having the lowest abundance (7.86 ± 4.06; Fig. 9). Similar to species richness,parametric One-way ANOVA testing showed no significant difference between average total abundancesper survey based on forest type (F = 0.159, df = 2, P = 0.855).

Degraded routes had the highest average species diversity (1.19±0.30). This was followed by primaryroutes which had an average diversity of 1.00 ± 0.21. Secondary routes had the lowest average diversity(0.88 ± 0.64). The result of a non-parametric Kruskal-Wallis One-way ANOVA on ranks (X2 = 1.5099,df = 2, P = 0.47), showed there was no significant difference in species diversity based on forest type(Fig. 10).

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Figure 9: Barplot showing average and standard deviation for total abundance of herpetilesper survey for each forest type.

Figure 10: Barplot showing average and standard deviation of herpetile species diversity (asShannon-Weiner’s Diversity Index) per survey for each forest type.

3.4.3 Discussion

Phase 191 produced a different result from previous reports. In previous reports, primary routes haveshown a significantly greater species richness than degraded routes. Therefore, having no significant

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result is unexpected and conflicts with studies both throughout Madagascar (Glaw2007) and worldwide(Gibbon2000). However, it has been observed that the local distributions of both amphibians and reptileschange between wet and dry seasons, with more open and degraded (and subsequently drier areas duringdry season; Saha2013) areas being more readily utilised (Seebacher1999, Berezowski2015). As such,the results of this phase may be due to those species usually found in primary and secondary forests,exploiting the wetter degraded forests.Secondary transect data may have been skewed by two surveys producing only one individual of onespecies each, however, as these surveys were conducted under normal conditions, it can be assumed theyreflect the habitat. It should be noted that these two surveys were conducted at night, the only othernight survey for secondary routes recorded five individuals from four species; based on data from thisphase, it may be suggested (but by no means concluded) that secondary transects support a more diversecommunity of diurnal herpetile than nocturnal ones.Despite eight species of snakes being observed during phase 191, but only one recorded during surveys,shows that they do have a noticeable presence throughout the research area, but may exist in lowerdensities or are generally more cryptic in their nature when compared to other reptile groups. Theabsence of a record for the hog-nose snake (Leioheterodon madagascariensis) during surveys is a particularsurprise as it is frequently encountered throughout the research area and is generally unresponsive tofootfall.

4 Avifauna diversity and abundance

Avifauna is notably the taxonomic group with the lowest endemism in Madagascar, with only 52% of theisland’s 209 breeding species being endemic to the island (Goodman2005), compared to an average of 84%for terrestrial vertebrates. Due to the ability of flight, migration across the Mozambique Channel, andacross the Indian Ocean Islands, is less inhibited, a trait also seen in the bats of Madagascar (Goodman2005), with these two groups having the highest number of colonisation events of terrestrial vertebrates(Samonds2012). Nevertheless, four entirely endemic families, and two further families also found on theComoros, are found in Madagascar (Sinclair2013, Behrens2016). Due to Madagascar’s isolation, manyprimitive species have been able to persist where they would have been otherwise outcompeted. One ex-ample of this are Mesites (Mesitornithformes), and entire order of ground birds endemic to Madagascarthat have existed since before the K-T extinction event (Samonds2013). Madagascar has a relatively lowspecies richness (313 species total, including migrants; Ganzhorn 2014), when compared to the similarlysized New Guinea (760 species; WWF2019). However, the pseudo-continent does possess one of thehighest proportion of birds of prey, as total number of birds of any country in the world (9%; Good-man2003), with the region around Nosy Be being touted as being one of the best places to find thecritically endangered Madagascar Fish Eagle (Haliaeetus vociferoides, Behrens2016). It has been regularly stated that the avifauna of malagasy forests are less vocal than other foreststhroughout the world (Goodman2003, Sinclair2013, Behrens2016), and as such much of the ambientnoise of the forest is dominated by frogs (Glaw2007).

Aims:

Determine if avifauna abundance and species diversity varies in our research area as a function of habitattype

Determine if avifauna abundance and species diversity varies in our research area as a function of humandisturbance level

5 Methods

Point counts were used to measure diversity and abundance. Eighteen points spread at least 200 metresapart represented Primary, Secondary, and Degraded forest habitats. Points were generally placed at thestart and end of transect to allow for easier access. Surveys were carried out between 0600 and 0800, withobservers having a five-minute wait period, before a ten-minute survey period. During the survey period,time, species, group size, state, and distance were recorded. State indicated whether an individual orgroup were seen, heard, or seen flying on first contact; Distance was recorded in bands as either 0-25metres (Band 1), 25-50 metres (2), or 50+ metres (3). During analysis, records in distance band 3were removed, this was carried out in Microsoft Excel. For each survey, values for Species Richness,

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Total Abundance, and Shannon-Weiner’s Diversity Index (hereafter Species Diversity) were calculated.Shapiro-Wilk’s test for normality and analysis of variance based on forest type was performed usingRstudio (R Core Team2015) with packages dplyr (Wickham2018), plyr (Wickham2011), vegan (Oksanen2019), and stats.

6 Results

During Phase 191, 48 surveys were conducted, 19 at degraded points, 18 at secondary points, and 11 atprimary points. In total, 26 species were recorded, 22 at degraded points, 17 at secondary, and 10 atprimary. The most abundantly surveyed species was the Souimanga Sunbird (Nectarinia souimanga),recording 79 individuals across 32 surveys (67% of surveys). A total of seven species (Buteo brachypterus,Cisticola cherina, Coracina cinerea, Leptopterus chabert, Merops supercilliosus, Treron australis, Upupamarginata) were only recorded on a single survey, with all but the Chabert Vanga (Leptopterus chabert)having but a single individual recorded. During the phase, casual observations were also recorded, with44 species observed between January and March. Of the 18 species observed, but not recorded duringsurveys, eight are considered seabirds, shorebirds, or occupy wetlands, and would not be expected duringforest transects. The following ten species mostly consisted of less common species, such as the Broad-billed Roller (Eurystomus glaucurus), Hook-billed Vanga (Vanga curvirostris), and Madagascar BluePigeon (Alectroenas madagascariensis).Shapiro-Wilks test for normality was performed on species richness, total abundance and species diversityfor each survey. Species richness (W = 0.939, P = 0.01) and diversity (W = 0.897, P < 0.01) werenot normally distributed, whereas total abundance (W = 0.977, P = 0.47) was. Based on this, thenon-parametric Kruskal-Wallis One-Way ANOVA on ranks was performed to investigate if there was asignificant difference in species richness and diversity based on forest type, whilst total abundance wastested using a parametric One-Way ANOVA.Degraded points showed a greater species richness (4.95 ± 1.13) than either secondary (4.17 ± 1.42),or primary points (3.45 ± 2.16; Fig. 11). The results of the Kruskal-Wallis test showed there was nosignificant difference between these groups (X2 = 5.240, df = 2, P = 0.07).

Figure 11: Barplot showing average and standard deviation of avifauna species richness persurvey for each forest type.

Similarly, total abundance of avifauna followed the same trend, with degraded points having thegreatest abundance (10.80±4.08), followed by secondary (7.94±2.96), then primary points (6.27±4.43).

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However, unlike species richness, the results of the One-way ANOVA produced a significant result (F =5.519, df = 2, P < 0.01). Tukey HSD Post-Hoc analysis showed that degraded points had a significantlygreater total abundance than primary points (P < 0.01; Fig. 12)

Figure 12: Barplot showing average and standard deviation of total avifauna abundance persurvey for each forest type; with significance between groups indicated.

Again, species diversity followed the trend of richness and abundance, with degraded points havingthe highest average (1.43 ± 0.25), followed by secondary (1.26 ± 0.37), and subsequently, primary points(1.03 ± 0.62). Shown in Fig. 13, there was no significant difference found between the species diversityof different forest types, based on Kruskal-Wallis test results (X2 = 2.786, df = 2, P = 0.25).

7 Discussion

The results of the Kruskal-Wallis test show that there is no significant difference in species richnessand species diversity of avifauna per survey based on forest type. Data was analysed per survey dueto an uneven sample size. There was, however, a significantly greater total abundance of avifauna persurvey in degraded points compared to primary points. However, it is unknown at this point whetherthis is due to (a) greater abundance across species, (b) greater representation of flocking species, or(c) greater number of observations due to more open habitats found at degraded points. As stated inthe introduction, malagasy birds are often less vocal, as such, in more obscured habitats (primary andsecondary), the actual diversity may be far greater than the surveyed diversity. This report is MGF’sfirst attempt at measuring avifauna diversity since phase 173 (July – September 2017), with the resultbeing similar, in that there was no significant difference in bird species diversity dependant on habitattype.

8 Invertebrate Inventories

During phase 191, invertebrate inventories of butterflies, spiders, and beetles continued, however to alesser degree than previous phases. Butterfly inventories were carried out during the day, using sweepnets, butterflies were caught and placed in a larger housing net (modified mosquito net) where new specieswere photographed. Spider and beetle inventories were carried out opportunistically at night, by walking

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Figure 13: Barplot showing average and standard deviation of avifauna species diversity (asShannon-Weiner’s Diversity Index) per survey for each forest type.

along forest routes, and using electrical light to look for individuals, again these were photographed.Photographs were separated into morpho-species, and where possible grouped into families, and genera.

8.1 Butterflies

At present, our butterfly inventory consists of 29 species across five families. One species of skipper (Hes-periidae), five species of blue (Lycaenidae), twelve species of nymphalid (Nymphalidae), four swallowtails(Papillonidae), and seven orange and whites (Pieridae). Every species has been identified to at leastfamily level. There are also a number of species absent from our inventory but well known and observedto be common in the area. This includes the African Monarch (Danaus chrysippus) and MadagascarForest Nymph (Aterica rabena).

8.2 Spiders

Spider diversity in Madagascar is vastly understudied, this reflects the difficulty that MGF has expe-rienced in identifying different species, even to higher taxonomic groups. In this instance, focus hasbeen given to orb-weaving spiders due to their comparatively conspicuous nature, and position as abioindicator (Maelfait1998, Nogueira2016). MGF currently has 13 orb-weaving spiders on record, tenof which can be described as armoured orb-weavers or spiny orb-weavers (Gasteracanthinii; Araneidae),two of which belong to the golden orb-weaver group (Nephilidae), and one currently unknown. Of thespiny orb-weavers, the genera Isoxya, Poltys, and Gasteracantha have been identified. It should be notedthat this does not reflect the species richness of the region, with many more species being observed, butnot included (by either due to lack of equipment or accessibility at the time of observation). However,the proportions of each group do reflect diversity of orb-weavers more accurately, with the spiny andarmoured orb-weavers being by far the most abundant. Other non-orb weaving species encountered reg-ularly include wolf spider (Lycosidae), huntsman (Sparassidae), and Ogre-face webcasters (Dinopidae).

8.3 Beetles

Beetle inventories is still in early stages, with focus on research and identification of different families.As a result, MGF is not the stage to report on the richness of species found in the area. It can be noted

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that there are noticeable numbers of tiger beetles (Cicindelinae; Carabidae), longhorns (Cerambycidae),leaf-beetles (Chryomelidae), and weevils (Curculiondae).

9 Summary

Overall during Phase 191, much of the data analysed differed from previous phases. This is due toa variety of potential reasons. The first possible reason may be due to the rainy season, changingconditions may increase or decrease suitability of habitats for different organisms, thus altering theirdistribution abundance and behaviour. A second possible reason is a change to methodology and dataanalyses; changing methods will mean the data being analysed is slightly different in nature, even if theoverall object of the data is the same (i.e. abundance), and by using different data analysis, the waythe trends and relationships are investigated is altered. In this case, MGF maintains that any changesthat have been made are more suitable for the data collected for this phase. The final reason is due tothe comparatively small datasets when compared with previous reports (48 herpetofauna surveys in 184compared to 19 in 191). The result of this is that although the data collected may be similar to previousphases, any statistical test applied will be less powerful and less likely to return a significant result.

10 Future Work

Phase 192 will see a re-adjustment of habitat classifications, with the addition of a ‘Corridor’ forest type.This is to address some disparity in species communities seen between secondary forest transects, allowingindividual analysis of small secondary and planted forests that are surrounded by degraded and openagricultural areas. Furthermore, some current transects will be adjusted to more accurately encompassthis classification and the number of transects will change from thirteen (Four primary, five secondary,and four degraded) to twelve (three for each forest type, including the new corridor forest type). Havingequal numbers of transects, surveyed an equal number of times, will allow for more robust analysis oftotal species richness and gross total abundance. Phase 192 will also see the continuation of the blacklemur census, by identifying new paths to increase the survey area. With inventories of butterflies andspiders becoming larger, it is hoped that butterfly point counts will begin, and orb-weaving spider web-morphology will resume, after being delayed in 191, due to unforeseen circumstances. The coming phasewill also see the implementation of a variety of habitat surveys, utilising botany experience in new staffmembers; this will allow for qualitative data to be collected on route degradation.

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