Species composition & diversity

Abundance and distribution of common & widespread taxa - birds

Context

The Department of Conservation’s (DOC’s) National Biodiversity Monitoring Programme has been designed to assess status and trend in common and widespread terrestrial species across all public conservation land (PCL) in New Zealand. These species are of particular importance because they have considerable influence on the structure, biomass and function of most ecosystems. Declines in these species may be difficult to detect over relatively short timeframes, particularly in the case of bird populations. However, even relatively small declines can reflect significant reductions in the number of individuals, which can have subsequent effects on ecosystem structure, function and services (Gaston, 2011). Such declines have been well documented for some of New Zealand’s rarer forest-dwelling birds, but there is also increasing evidence that significant declines have occurred for what were previously considered common and widespread species, e.g. Elliott et al. (2010) and Walker et al. (2017).

Key findings

Richness

Species richness metrics on PCL are shown in Table 1 and Figure 1. During the seven seasons from 2012/13 to 2018/19, the average species richness on PCL was:

Figure 2 can be used to explore the species richness at different parks across New Zealand. Interpret with caution as many of these sites had very few samples.

Table 1: Species richness on public conservation land broken down by ecosystem and indigenous/introduced species and ecosystem type. The values are derived from the posterior predicted site richness estimates shown in Figure 1.

Species group Ecosystem Mean SE(mean) 95% range across sites
all all 8.90 0.11 (0.56, 15.66)
all non-woody 8.35 0.22 (0.55, 15.03)
all woody 9.13 0.13 (0.57, 15.75)
indigenous all 6.33 0.09 (0.33, 11.88)
indigenous non-woody 6.07 0.17 (0.28, 11.71)
indigenous woody 6.44 0.10 (0.35, 11.91)
introduced all 2.57 0.05 (0.15, 7.25)
introduced non-woody 2.28 0.09 (0.15, 6.75)
introduced woody 2.69 0.06 (0.16, 7.41)

Figure 1: Estimated species richness at each monitoring site defined as the proportion indigenous (dominance), the total richness, the indigenous richness, or the introduced richness. Switch between satellite and terrain view by clicking on the tile in the upper right corner of the map, and explore the different metrics by using the check buttons on the top right. Click on an individual plot to see the estimates for that plot. All richness indices have been scaled between 0 and 100 for plotting purposes.1 True locations have been randomly jittered to protect species and the integrity of the plot.

Figure 2: Average estimated introduced and indigenous species richness at each park over the last five seasons. Select a location in the box at the top (turns red when ‘switched on’) and hover over an individual point to see the details. Values are mean ± 1 standard error.

Occupancy

Occupancy refers to the presence of a bird species at a site. Occupancy estimates for a range of indigenous and introduced bird species on PCL are shown in Figures 3 & 4.

Figure 3: Estimated occupancy for indigenous species across public conservation land in woody and non-woody ecosystems. Click on the legend to see the values for different ecosystem types and hover over points for the estimated mean and 95% credible interval.

Figure 4: Estimated occupancy for introduced species across public conservation land in woody and non-woody ecosystems. Click on the legend to see the values for different ecosystem types and hover over points for the estimated mean and 95% credible interval.

Definition and methodology

DOC has developed a national monitoring programme to assess status and trend of biodiversity across of all of the land it manages with a particular emphasis on terrestrial monitoring. The programme collects data on indicators and measures of ecological integrity outlined in the Department’s Biodiversity Outcomes Assessment Framework (PDF, 1.07 MB).

The terrestrial monitoring programme has been established at approximately 1400 plot locations spaced evenly across PCL. Each year, approximately 280 plots are measured with every plot being measured once over a 5-year rotation cycle. This spatially extensive monitoring programme has been designed to provide unbiased, repeatable, national-scale estimates of priority ecological integrity indicators and measures. See Table 4 for the sample sizes in different ecosystems during the seven seasons from 2012/13-2018/19.

This factsheet focusses on bird species composition (richness), occupancy and relative abundance. Communities of diurnal (daytime) birds are surveyed at each plot location using a cluster of up to 5 different bird count stations (at least 150 m apart) between 1 hour after official sunrise and 1pm hours using the 5-minute bird count (5MBC) method. Only terrestrial birds were considered for analysis (n = 51). Aquatic birds such as gulls or ducks were removed. The occasional diurnal record of morepork (ruru) was also removed as there are alternative acoustic detection and analysis methods for nocturnal (night time) species.

The data were modelled using a Bayesian hierarchical multispecies occupancy model with richness equal to the sum of species occupying a site (Dorazio and Royle, 2005). Occupancy \((z_{i,j})\) was species \(i\) specific and depended on cover (woody, non-woody). Detection \(x_{i,j,k}\) at a listening station \(k\) was also species specific. A site \(s[j]\) level random effect was included for both detection and occupancy. Index j refers to a site-season (a site in a specific season, as some sites had data from two seasons, typically 2013/14 and 2018/19) while s[j] refers to the site corresponding to site-season j.
The model was specified as follows \[ \begin{array}{rcl} x_{i,j,k}|z_{i,j} & \sim & bernoulli(p_{i,j} \times z_{i,j}) \\ z_{i,j} & \sim & bernoulli(\psi_{i,j})\\ logit(p_{i,j}) & = & \alpha_{i} + u_s[j] \\ logit(\psi_{i,j}) & = & \beta_{0,i} + \beta_{1,i}woody_{j} + v_s[j] \\ \end{array} \] with priors \[ \begin{array}{rcl} \alpha & \sim & \mathcal{N}(\mu_{\alpha}, \sigma_{\alpha}) \\ \beta & \sim & \mathcal{N}(\mu_{\beta}, \sigma_{\beta}) \\ v_j & \sim & \mathcal{N}(0, \sigma_1) \\ u_j & \sim & \mathcal{N}(0, \sigma_2) \\ \end{array} \] and hyper priors \[ \begin{array}{rcl} \mu_k & \sim & \mathcal{N}(0, 10) \\ \sigma_k & \sim & \Gamma(0.01, 0.01). \\ \end{array} \]

For the most common species on PCL the model was augmented with a negative binomial term for the total count \(y\) per species/site/season combination with a species-dependent overdispersion parameter \(r\), conditional on occupancy and detection: \[ \begin{array}{rcl} x_{i,j,k}|z_{i,j} & \sim & bernoulli(p_{i,j} \times z_{i,j}) \\ y_{i,j,k}|z_{i,j} & \sim & negbin(\lambda_{i,j} \times x_{i,j},r_i) \\ z_{i,j} & \sim & bernoulli(\psi_{i,j})\\ logit(p_{i,j}) & = & \alpha_{0,i} + \alpha_{1,i}woody_{j} + u_s[j] \\ logit(\psi_{i,j}) & = & \beta_{0,i} + \beta_{1,i}woody_{j} + v_s[j] \\ \end{array} \]

Table 4: Number of plots observed annually for the different ecosystems and conservation status that this report focusses on.

Ecosystem Conservation Status 2012 2013 2014 2015 2016 2017 2018 Total
non-woody national park 0 0 23 22 16 25 22 108
non-woody non-national park 0 2 46 56 58 59 59 280
woody national park 0 0 74 73 59 64 53 323
woody non-national park 1 2 125 115 120 123 140 626
total total 1 4 268 266 253 271 274 1337

Change of methodology relative to earlier seasons

Because the plots measured in 2018/19 are generally the same as the ones measured in 2013/14, we now have repeated measurements for those plots. We have also included the 2012/13 measurements which are repeated in 2017/18. The model already had a random site effect in order to account for between-species correlation, but we now distinguish between site-season random effects (which do not imply between-season correlation within plots) and site random effects, which do. We opted for site effects for overall (across species) detectability and species-specific occupancy, but for site-season effects for conditional abundance.

Data quality

This measure is classified as a national indicator.

Relevance

This measure relates to indicator 1.5 - Maintaining ecosystem composition, which includes:

Accuracy

This measure complies with the data quality guidelines used in New Zealand’s Environmental Reporting framework.

Outcomes Monitoring Framework

DOC’s Outcomes Monitoring Framework provides a platform on which DOC and others can assess outcomes in a clear, structured and transparent way (Lee et al., 2005). It has been developed as a logical hierarchy that is based on broad, overarching Outcomes, beneath which are nested Outcome Objectives, Indicators, Measures and Data Elements to provide ever increasing levels of detail. The framework is scalable, as the indicators and measures remain compatible and consistent whether applied locally, regionally or nationally. The recently updated framework provides a roadmap for gathering information to meet the specific objectives of DOC and other agencies (McGlone and Dalley, 2015). The provision of a national framework with agreed outcomes, indicators and measures supports collaboration with land management and regulatory agencies, allowing for more integrated environmental policy and ‘State of the Environment’ reporting. DOC has partially implemented a national monitoring and reporting system, whereby priority indicators and measures are routinely used to report on progress against the objectives and outcomes. This factsheet reports on a measure for the 2018/2019 year.

Glossary of terms

References

Dorazio, R.M., Royle, A.J., 2005. Estimating size and composition of biological communities by modeling the occurrence of species. Journal of the American Statistical Association 100, 389–398.

Elliott, G.P., Wilson, P.R., Taylor, R.H., Beggs, J.R., 2010. Declines in common, widespread native birds in a mature temperate forest. Biological Conservation 143, 2119–2126.

Gaston, K.J., 2011. Common ecology. Bioscience 61, 354–362.

Lee, W., McGlone, M., Wright, E., 2005. Biodiversity inventory and monitoring: A review of national and international systems and a proposed framework for future biodiversity monitoring by the Department of Conservation. Landcare Research Contract Report LC0405/122 (unpublished) for the Department of Conservation, Wellington.

McGlone, M., Dalley, J., 2015. A framework for Department of Conservation inventory and monitoring: Intermediate outcomes 1-5. Landcare Research Contract Report LC2427 (unpublished) for the Department of Conservation, Wellington.

Walker, S., Monks, A., Innes, J., 2017. Status and change in native forest birds on New Zealand’s mainland, 1969–1979 to 1999–2004. Dunedin: Landcare Research.

  1. A linear transformation is taken of the count data \(x\), \(f(x) = \dfrac{x - min(x)}{max(x)-min(x)} \times 100\).↩