Hares (Lepus europaeus occidentalis) are not widespread across Public Conservation Land (PCL) in New Zealand. However, they may still have significant impacts on the growth of palatable plant species, particularly the survival of some threatened species. Therefore, estimates of their national distribution and abundance can help direct control efforts on PCL, and also provides important baseline information against which future assessments and different management options can be compared.
Occupancy represents whether a hare was present or absent at a site through detection of faecal pellets. As can be seen from Figures 1 and 2, hare occupancy on PCL was:
Figure 1: Hare occupancy on public conservation land (PCL) over the last 7 seasons. Different ecosystem types (woody, non-woody) and conservation status (national park, non-national park) are represented by different line types and colours, respectively. Click on the legend to select different combinations and hover over an individual point to show the value and 95% credible interval.
Figure 2: Observed hare faecal pellet indices (FPIs) for the most recent measurement at each site on public conservation land (PCL). FPI is an index of relative abundance and gives a sense of distribution/occupancy across PCL. Click on an individual site to see all measurements since 2011. Switch between satellite and terrain view by clicking on the tile in the upper right corner of the map. Choose the ‘present/absent’ layer to outline in black areas that have hares present and choose ‘park level’ to switch to aggregated park averages. True locations have been randomly jittered to protect species and the integrity of the plot.
Figure 3 shows trends in the faecal pellet index (FPI) based on occupied areas as well as trends across the entire PCL. The average FPI was:
Figure 3: Hare faecal pellet index (FPI) on public conservation land (PCL) over the last 7 seasons. ‘Occupied FPI’ represents FPI trends in hare-occupied areas, whereas ‘PCL FPI’ represents trends in FPI across all PCL.
Different ecosystem types (woody, non-woody) and conservation status (national park, non-national park) are represented by different line types and colours, respectively. Click on the legend to select different combinations and hover over an individual point to show the value and 95% credible interval.
Figure 4 can be used to explore hare abundances at different parks across the country. Interpret this with caution as many of these sites have only a single sample (See Figure 2 for a spatial view of these data).
Figure 4: Average observed hare faecal pellet indices (FPIs) for the most recent measurements at plots in each park. Select a location in the box at the top (becomes red when ‘switched on’) and hover over an individual point to see the details. Several outliers are not visible but can be seen using the tools on the top right of the figure. Values are mean ± 1 standard error.
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 1 for sample sizes in different ecosystems during the eight seasons from 2011-2018.
After 2017, most measurements have been repeated surveys at plots. Table 2 shows the number of plots that have had repeated measurements, and changes in observed hare pellet occupancy between measurements. In a change from previous years, a site effect has been added to the model to allow for correlation between the repeated measurements. One consequence of this change in modelling strategy is that the plotted occupancies and abundances now incorporate the average plot effects for the respective years, which means that the plotted time trends are no longer strictly linear, even though the modelling assumtion of a linear trend still applies.
The data were modelled using a Bayesian zero-inflated negative binomial with zero inflation being informed by occupancy at a site. Both occupancy \((z_{i,j})\) and FPI \((y_{i,j})\) depended on ecosystem (woody, non-woody), park status (national park, non-national park), and time at site \(i\) and transect \(j\), with site-level random effects (\(site1, site2\)). The model was specified as follows \[ \begin{array}{rcl} y_{i,j}|z_{i} = 1 & \sim & NB(\mu_i, r) \\ x_{i,j}|z_{i} & \sim & bernoulli(p \times z_{i}) \\ z_{i} & \sim & bernoulli(\psi_{i})\\ \mu_{i} & = & \frac{r}{r + \lambda \times z_{i}}\\ log(\lambda_{i,j}) & = & \alpha_{0} + \alpha_{1}woody_{i} + \alpha_{2}time_{i} + \alpha_{3}time_{i}woody_{i} + \alpha_{4}park_{i} + site1_{i}\\ logit(\psi_{i,j}) & = & \beta_{0} + \beta_{1}woody_{i} + \beta_{2}time_{i} + \beta_{3}time_{i}woody_{i} + \beta_{4}park_{i} + site2_{i}\\ site1 & \sim & \mathcal{N}(0, \tau1) \\ site2 & \sim & \mathcal{N}(0, \tau2) \\ \end{array} \] with uninformative priors \[ \begin{array}{rcl} \alpha & \sim & \mathcal{N}(0, 1000) \\ \beta & \sim & \mathcal{N}(0, 1000) \\ r & \sim & \Gamma(0.01, 0.01)\\ p & \sim & B(1, 1)\\ \tau1 & \sim & \Gamma(0.01, 0.01)\\ \tau2 & \sim & \Gamma(0.01, 0.01)\\ \end{array} \]
Table 1: Number of plots measured annually for the different ecosystems and conservation land status that this report focusses on.
| Ecosystem | Conservation Status | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | Total plots |
|---|---|---|---|---|---|---|---|---|---|---|
| non-woody | national park | 0 | 21 | 24 | 23 | 22 | 17 | 25 | 22 | 111 |
| non-woody | non-national park | 0 | 43 | 58 | 46 | 56 | 59 | 59 | 59 | 282 |
| woody | national park | 35 | 8 | 54 | 74 | 72 | 60 | 65 | 54 | 324 |
| woody | non-national park | 33 | 22 | 150 | 125 | 115 | 120 | 123 | 141 | 639 |
| Annual total | total | 68 | 94 | 286 | 268 | 265 | 256 | 272 | 276 | 1356 |
Table 2: Counts of plots that have been re-measured since 2011, grouped by the interval between measurements and whether hare pellets were observed or not detected in each measure.
| Interval | First measure | Observed | Not detected |
|---|---|---|---|
| 2011-2015 | Observed | 0 | 0 |
| Not detected | 3 | 62 | |
| 2012-2015 | Observed | 39 | 4 |
| Not detected | 4 | 46 | |
| 2013-2018 | Observed | 54 | 6 |
| Not detected | 6 | 202 |
This measure is classified as a partial measure of high accuracy under New Zealand’s Environmental Reporting criteria.
This measure relates to indicator 1.3.2 - invasive species dominance.
This measure complies with the data quality guidelines used in the Environmental Reporting 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 2018/19 year.
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.