Flyway trend analyses based on data from the African-

Eurasian Waterbird Census from the period of 1967-2015

Compiled by

Szabolcs Nagy and Tom Langendoen

Wetlands International

Ede, The Netherlands

August 2017

The data analysis was supported by

the UNEP/AEWA Secretariat,

the Association of the Members of Wetlands International,

the Swiss Federal Office for the Environment,

the Norwegian Environmental Agency

and the European Union LIFE+ NGO Operational Grant

The collection of data was also supported by several other international and national

initiatves and funding.

Recommended citation:

Wetlands International (2017) Flyway trend analyses based on data from the African-

Eurasian Waterbird Census from the period of 1967-2015. Online publication. Wetlands

International, Wageningen, The Netherlands. http://iwc.wetlands.org/static/files/0-IWC-trend-

analysis-report-2017-final.pdf

Table of contents

Introduction 4

The Waterbird Fund 4

Materials and methods 5

Monitoring of waterbirds 5

The African-Eurasian Waterbird Census 5

Selection of species and populations for analysis 6

Allocation of count data to populations 7

Estimating population size 7

Trend analyses 8

Trend classification 9

References 12

Introduction

Waterbirds are shared resources and a shared responsibility. Their conservation and

sustainable management and the sites they use are therefore the subject of various

international treaties, such as the Ramsar Convention on Wetlands, the Convention on

Migratory Species (CMS), the African Eurasian Migratory Waterbird Agreement (AEWA), the

Bern Convention on European Wildlife and Natural Habitats and the EU Birds Directive, as

well as national conservation and hunting legislation.

Flyway-level trend and population size analyses are needed to inform international and

national decisions. Population size and trend estimates are used in the global and regional

Red List assessments, they inform the classification of waterbird populations on Table 1 of the

AEWA Action Plan and guide the subsequent application of its provisions, as well as providing

the basis for the so-called 1% thresholds to select internationally important sites under the

framework of the Ramsar Convention, the Bern Convention’s EMERALD Network, the

European Union’s Natura 2000 Network and the identification of Important Bird Areas.

The flyway-level trend analyses also provide contextual information to national level decisions

concerning the management of waterbird populations, such as regulating harvest or evaluating

the effectiveness of conservation actions including actions at site level.

In 2016, we celebrated the 50th anniversary of the International Waterbird Census (IWC). This

report presents results of half a century of biodiversity monitoring carried out by dedicated

professionals and more than 10,000 volunteers across the African-Eurasian flyways.

Wetlands International and the authors are indebted to the national IWC coordinators, their

networks, the Strategic Working Group of the African-Eurasian Waterbird Monitoring

Partnership and the donors who contributed to this work. We are also grateful to Arco van

Strien and Leo Soldaat of the Dutch Central Bureau for Statistics for their advise concerning

the new statistical analyses.

The Waterbird Fund

This report will illustrate that we can assess the trends of waterbirds only if our national

partners are able to conduct the surveys in their countries. Unfortunately, funding for waterbird

monitoring is not available everywhere across the flyway as national governments also need

to attend to other pressing social needs, especially in low- and medium-income countries.

Recognising the need for regular and predictable support to waterbird monitoring, the

organisations participating in the Waterbird Monitoring Partnership established the Waterbird

Fund in 2016, which is managed by Wetlands International. If you find the information

presented in this report useful and want to help improve monitoring across the flyway, please

support the Waterbird Fund. For further information, visit: https://waterbird.fund/.

Materials and methods

Monitoring of waterbirds

The AEWA Table 1 includes a wide range of water- and seabird populations which require

different survey and monitoring techniques to estimate their population size and trends. In

general, populations can be monitored during the breeding season, during the wintering

season or on migration. Monitoring during the breeding season is most suitable for colonial

breeding species or for those dispersed ones that can be relatively easily found during the

breeding season. Monitoring during the winter season is most suitable to monitor the

populations of species that congregate at certain sites or those dispersed species that breed

in otherwise inaccessible or difficult to observe areas during the breeding season. Migration

counts are particularly useful for those species that are not easy to monitor during the

breeding or non-breeding season, but concentrate on a few sites during migration. The

suitable techniques depend on the species distribution, behaviour, accessibility of their

breeding and non-breeding areas, overlap between the different populations in the given

season and practical considerations such as available capacity and costs.

The African-Eurasian Waterbird Census

This report is based on waterbird count data collected during the African and Western

Palearctic regional schemes of the International Waterbird Census (IWC) which were joined

into a flyway monitoring scheme in 2011. The IWC is a long-term site-based monitoring

scheme that started in parts of the Western Palearctic in 1967 and gradually extended

throughout the rest of the flyway, with the African programme starting in 1990. The IWC has

grown into one of the world’s largest global biodiversity monitoring schemes.

Originally, the IWC was organised to estimate numbers and monitor changes in (the Northern)

wintering waterbirds. Therefore, the core IWC counts are carried out in January across the

entire African-Eurasian Flyway. The IWC is also commonly referred to as the mid-winter

counts, particularly in Europe. In Africa, over-wintering populations of the Palearctic may mix

with local African populations during the mid-winter counts and some species do not

congregate during this period. Some African countries also conduct counts in July as part of

the IWC to better monitor these populations.

The IWC count methods can also be extended to monitor the importance of stop-over sites

during migration. Consequently, additional counts also take place in some or all other months

during the non-breeding season in several countries.

The IWC operates through national schemes in each country. These schemes are organised

by national coordinators (see www.wetlands.org/our-network/iwc-coordinators/) who are

affiliated with government agencies, scientific institutes or non-governmental organisations. In

turn, the national coordinators work with a large network of professional and volunteer

observers. The national IWC schemes contribute to the monitoring obligations of governments

under international treaties such as the Ramsar Convention on Wetlands, the African-Eurasian

Migratory Waterbird Agreement and the Birds Directive of the European Union and are often

supported by respective governments. However, in some countries, particularly in low- and

medium income ones, the counts are implemented only when financial and technical

assistance is available, often from external sources. This dependency on funding results in

significant variability in coverage, presenting challenges for using the count results to produce

population estimates and trend assessments.

Selection of species and populations for analysis

For this report, only the 553 migratory waterbird populations listed on Table 1 of the AEWA

Action Plan were considered for inclusion. For each population, we considered whether the

size and/or the trend of the population can be estimated reliably based on IWC counts and, if

not, whether there is any other alternative monitoring scheme in place. It is not possible to

produce estimates for populations that are mixed with other populations at the time of the IWC

counts because allocation of individuals to the different populations would be speculative. For

example, the wintering areas of some Palearctic breeding populations of herons overlap

extensively with the range of the African populations of the same species. For many European

populations, particularly conspicious ones breeding in countries with adequate monitoring

schemes, breeding bird monitoring provides a rather reliable alternative source of population

size and trends estimates. However, breeding bird monitoring is incomplete in the Arctic, in

Eastern Europe, Southwest Asia and Africa. In the absence of other data to provide insight

into the status of populations in these regions, we decided to use IWC data to produce

estimates also for populations for which breeding bird monitoring could be a theoretically better

option. We have not included populations of species that are the subject of specialised non-

breeding counts such as geese and cranes (van Roomen 2010). Seaducks should also be

subject of specialised schemes but trend data is not available at flyway scale. Therefore,

available data was analysed on an experimental basis.

Allocation of count data to populations

Our analyses aim to contribute to the status assessment of the migratory waterbird flyway

populations defined in Table 1 of the AEWA Action Plan where IWC provides the best available

data or where it can be used to triangulate data from other sources, building on earlier work

by Wetlands International (Scott & Rose 1996, Delany et al. 2009), and the AEWA Technical

Committee decisions concerning population allocations reflected in Table 1 of the AEWA

Action Plan. In the IWC trend analyses of 2012 and 2014 (Wetlands International 2012, Nagy

et al. 2014), count sites were allocated to flyways using GIS spatial overlap procedures with

the population boundaries available on the Critical Site Network Tool. As manual allocation of

sites in the overlapping areas of two flyways was a rather time consuming process, this was

replaced by a country allocation to population flyway, with the exceptions of France (where

Languedoc-Roussillon and Provence-Alpes-Côte d’Azur were allocated to the West

Mediterranean, sites along the Rhine and Lake Geneva to the Central European and the rest

of the country to NW European region), Germany (where Bavaria and Baden-Würtenberg

were allocated to Central Europe and elsewhere to North-western Europe) and Russia (where

Kaliningrad and St. Petersburg were allocated to the Baltic, the southwestern part of European

Russia (Rostov, Krasnodar, Chelyabinsk, Adygey) was allocated to the Black Sea and other

divisions to the east in European Russia were allocated to the Caspian regions). Each country

or sub-region was allocated to a single population of a species except some special cases

when more than one clearly separated population occurred in the country.

Estimating population size

IWC count data can be used directly to estimate population size only if an (almost) full census

is possible. This might be the case for some conspicuous species, concentrated on a few sites

that are all well covered by observers and counted at the same time (e.g. some goose

populations). For other species, annual count totals always represent a fraction of the entire

population. Count totals can be adjusted by imputing for missing counts, allowing an

estimation of the population occurring within IWC sites. However, the coverage of the IWC

site network varies to a large extent between countries and for different species within a

country. Furthermore, the often highly congregatory behaviour of some waterbird species in

the non-breeding seasons represents additional difficulties for estimating population sizes

based on statistically robust samples as the higher variance requires higher sample size. As

a conseqence, calibration of count totals to a derived population estimate is mainly limited to

dispersed species.

National population size estimates are available for some countries, particularly those required

to report such figures to the European Union. However few of these estimates are based on

statistically robust procedures, instead relying on expert opinion to account for missing,

variable or incomplete counts.

Each population account included here presents the current population estimates based on

the 6th edition of the AEWA Conservation Status Report (Wetlands International 2015), the

range of count totals for the period of 2011-2015 and a graph showing the evolution of count

totals since the first observation available for the population in the IWC database until 2015.

Trend analyses

Site selection

To ensure consistency in site coverage over time, we have selected sites for analysis that

have at least one positive count of the species in between 1991-2002 and 2004-2015, i.e both

halves of the last 25 year trend period. This left 13,787 sites from the total of 42,719 to be

included into the trend analyses.

Figure 1. IWC sites in the African-Eurasian Flyway. Green (last counted in 2015) and yellow (last counted before 2015) sites are included in the trend analyses. Blue (counted in 2015) and black (counted before 2015) sites were excluded from the analyses due to insufficient data.

Interpreting missing count values

For the purpose of trend analyses, we consider the IWC as a full list method for waterbirds

because observers are requested by the national coordinators to record all species they have

seen even if they were not able to count them. Unreported species were considered absent,

unless a relevant multispecies group (e.g. unidentified diving ducks) was reported during the

count or for years before the count of the species group started in a country (e.g. only Anatidae

and Coots were counted in many European and Southwest Asian countries until 1989). This

assumption is probably invalid for cryptic species (such as crakes and snipes) or species that

are difficult to identify without good optics (e.g. stints).

Trend calculation

Earlier IWC trend analyses were carried out at the regional (Delany et al. 1999, Gilisen et al.

2002) or flyway-scale (Wetlands International 2012, Nagy et al. 2014), leading to trends driven

by countries with large count numbers. We removed this bias by imputing for each country

separately prior to flyway-scale analyses. We estimated missing values using the R-version

of TRIM (Bogaart et al. 2016). We first attempted models with the following settings: Model 2

(i.e. year-effect), automatic change-point removal, serial correlation and overdispersion. For

populations with insufficient data, models were attempted without the conditions of serial

correlation and/or automatic change-point removal. National trends were calculated for the

period between the first and the last year the country had positive count for the species.

Flyway population trends were calculated based on the national TRIM results, using the

imputed national totals and the covariance matrix from the first run of TRIM. To reduce the

impact of spurious imputing, years with less than 30% of observed data in the imputed totals

of the national runs were excluded and were treated as missing years for the country. Ideally,

national results should be weighted when combined for the population analyses. However, as

mentioned above, no robust national population size estimates are available yet for most

countries, leaving no basis for reliable weighting at this time.

After summing up the national totals to flyway population totals and imputing for missing

country years, years with less than 30% of observed data in the population imputed totals

were excluded and treated as missing years. This left fewer but more reliable annual

population estimates in the sample, particularly important for many populations from

Southwest Asia and Africa. Missing years were imputed through a second TRIM run that

effectively imputed the missing values using log-linear trend between years with sufficient

data.

Figure 2. Step-by-step analytical process to calculate population trends.

The TRIM index values for each population were smoothed with the MSI-tool (CBS 2017,

Soldaat et al. 2017, CBS).

Trend classification

The MSI-tool and TRIM apply a trend classification system that compares the trend to a

population change of 20% over 20 years (see Appendix C in Pannekoek and van Strien 2005).

However, both the IUCN Red List criteria and the AEWA Resolution 5.7 applies a “dynamic”

definition of annual rate of change that depends on the generation length of the species:

● The IUCN Red List criteria defines various thresholds of change over 10 years or three

generations whichever is longer (under A2, A3 and A4) or over 5 years or two

generations whichever is longer (under C1);

● The European Red List of Birds also defines declining population based on 10%

decline over 10 years or 3 generations whichever is longer;

● The AEWA Resolution 5.7 (UNEP-AEWA 2012) defines the criteria for significant long-

term decline as 25% over 25 years or 7.5 generations whichever is longer.

Although, the required rate of decline would be almost the same in case of 20% decline over

20 years (as in TRIM and MSI: ), 10% over 10 years (IUCN, BirdLife) or 25% over 25 years

(AEWA), the required rate of decline would become smaller as soon as the required 3 or 7.5

generation exceeds the 10 or 25 years (see Figure 3)

Figure 3. The change in annual rate of population change to produce 25% decline over 25 years or 7.5 generations. To illustrate the similarity of rates the value for year 1 represents 10% decline over 10 years

and year 2 represents 20% decline over 20 years.

As most of the waterbird species have a generation length longer than 3 years, application of

these criteria requires assessing the rate of decline against these dynamic thresholds. The

threshold rate of decline can be calculated from the following equations:

𝐷− = 𝑒ln ( 1−𝐶

𝑡−1) (1 for decline)

𝐷+ = 𝑒ln ( 1+𝐶

𝑡−1) (2 for increase)

Where

D: the multiplicative annual rate of change

C: the population decline/increase over 7.5 generations (i.e. 25%)

t: the length of 7.5 generations obtained from the BirdLife International DataZone

(BirdLife International 2017)

The trend classification followed Soldaat et al. (2017) with the difference that D- and D+ were

used instead of 0.95 and 1.05, i.e. as thresholds for steep decline or strong increase

respectively (Table 1).

Table 1. Trend classification (modified from Soldaat et al. 2017). CI = confidence interval, CL = confidence limit.

Category Criteria/description

Strong increase lower CL > D+ (significant increase of more than D+ per year)

Moderate increase 1.00 < lower CL < D+ (significant increase, but not significantly more than D+ per year)

Stable CI includes 1.00 AND 1 - D- ≤ lower CL AND upper CL ≤ 1 + D+ (no significant increase or decline, likely that changes are smaller than D± per year)

Uncertain lower CL < 1 - D- AND 1 + D+ < upper CL (no significant increase or decline, unlikely that changes are smaller than D± per year).

Moderate decline D- < upper CL < 1.00 (significant decline, but not significantly more than D- per year)

Steep decline upper CL < D- (significant decline of more than D- per year)

Within the uncertain category we have internally separated the subcategory ‘fluctuating’ if

the multiplicative annual rate of change remained between 0.95 and 1.05 to distinguish

fluctuation from truly uncertain trends, but we have not reported this difference because

often the visual inspection of the trend results contradicted the result of the assessment. This

is unsurprising if one considers that a sustained increase by 5% would result in a population

size over 25 years that is more than 3 times larger than at the start, or the same rate of

decline over the same period would result in a population size under one third of the original

population size.

As the MSI-tool often produced uncertain trends, especially in the short-term, we have also

reported the results of the TRIM trend analysis if that was different from the MSI results to

assist the interpretation of the population trend, especially in case of populations in data-

poor areas. We have opted to do so because an assessment based on the available

imperfect data is still more useful for management purposes than no assessment at all.

Obviously, the results of the trend analyses based on less certain data are given less weight

in the final assessment of the status of the population than data from more certain sources.

However, the fact remains that for the majority of waterbird populations in Africa and SW

Asia no trend data is available other than from the International Waterbird Census.

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