In davan690/beech-publication-wr: Small mammal dynamics in NZ beech forests

Discussion {#discussion}

Our study focused on understanding the effects of stoat control on wild mouse populations in New Zealand beech forests. Specifically, we were interested in whether mesopredator release of mouse populations occurred in areas where stoat control was undertaken compared to areas without stoat control. Similar to previous research, we found that populations with higher seed availability (intake rate) also had higher mouse abundance in the sub-seeding months until natural germination of the seeds in mid/late summer. The intake rate ($S_{j,t}$) had the greatest impact on mice populations in all seasons. These phenomena are commonly observed in NZ beech forests (Figure \@ref(fig:figure-one-plot1); @choquenot2000; @ruscoe2005) and other NZ mixed-forest types [@innes; @sweetapple; @ruscoe2011; @ruscoe2012]. The effect of mouse density ($N_{j,t}$) and rats ($R_{j,t}$) abundance was lower than the "intake rate" ($S_{j,t}$). We observed density dependence was greatest during population declines. The effect of mouse density and rats on the rate of increase of mouse populations was much lower but similar to other published results [@choquenot2000]. These processes are commonly observed in NZ beech forests (Figure \@ref(fig:figure-one-plot1); @choquenot2000; @ruscoe2005), and to a lesser extent, other NZ mixed-forest types [@innes; @sweetapple; @ruscoe2011; @ruscoe2012].

A naïve investigation of the summarised data we collected (Figure \@ref(fig:figure-three-trends-seed): \@ref(fig:figure-three-trends-rats) compared to the predictions in Figure \@ref(fig:figure-one-plot1) might have falsely lead to the conclusion that greater numbers of rats occur when stoats are controlled but there was no raw trends in mouse abundance that indicated that rats negatively affected mice dynamics in NZ Beech forests. It was previously unclear whether stoat populations could increase at a great enough rate to exert sufficiently strong predation pressure to alter the food-driven population eruptions of mice. As with other studies we also observed high heterogeneity in individual observations. Count data in biological systems like this can be difficult to model correctly in many frequentist frameworks. Our study design and Bayesian methodology allows to observe signals of heterogeneity in different groups without over parameterising the model.

By taking the proposed processes that effect mice dynamics and applying a hierarchical model framework allows us to test and estimate effect sizes that further reduce uncertainty in the outcomes of predator control in NZ beech forests. Importantly, our model incorporates both the observational and process variability within NZ beech forests and therefore should be more realistic when describing the system. We also conclude that the underlying heterogeneity in small mammal populations was sufficiently large to make estimating true response of mice to rats difficult in biological experiments (Figures \@ref(fig:figure-three-trends-seed)-\@ref(fig:figure-three-trends-rats)). We used this BHM after encorperating the confounding effects of food availability, mouse density, and the presence of rats to simultaneously assess the overall differences in the mice dynamics between our different treatment groups (stoat control and rat removal).

Stoat control

During our study we found stoat control had minimal impact on mice populations relative to seedfall. The lack of any observed effects of stoat control on mouse abundance was that the removal of animals was potentially limited by the effectiveness of a particular stoat control program, management or experimental design. If trapping did not remove a sufficient number of individual stoats to reduce predation pressure we will not observe the theoretical responses proposed by @tompkins2013 and others.

Furthermore, the intrinsic differences in the reproductive and growth rates (life history traits) of mice compared to stoats reduces the ability for stoats to regulate mouse populations through direct predation alone [cite??]. King (2011) modelling the reproductive processes of stoats at the beginning of a masting event [@king2011].

Challenges

Population level responses such as abundance and rate of increase are often measured using indices (e.g. MNA). This can lead to difficulty in estimating population level parameters such as density. We aimed to avoid this bias as we estimated mice abundance using capture-recapture (CR) data and an integrated population model to correctly account for uncertainty in abundance estimation when fitting the population model of mice dynamics. However due to limited population numbers and data, only indices could be used to represent rat interactions. Independent research in beech forests has shown a high correlation between indices of rats in this valley and CR data. Nevertheless, increasing the quality of the rat/kiore data would most likely reduce uncertainty on the estimates of these parameter estimates. By calculating the maximum increase from the fitted population model we were able to compare the maximum population growth rate to other studies (R.max_mice=actualnumberhere; @hone2010), however, analogous models are not directly comparable because they do not include a resource component (e.g. beech seed production) or use indices (e.g. $R_(j,t)$). Field studies are also difficult to directly compare because may studies incorporate structurally different ecosystems (e.g @ruscoe2011), species indices instead of true abundance estimation using CR models or did not report effect sizes. Although this limitations exist our comparisons to general trends were all comparable to our model estimates and our estimates are all biologically viable.

High individual heterogeneity in the capture rates of stoats at both high and low mouse densities makes reductions to zero individuals virtually impossible targets. This was the case in our study where by-catch of stoats in controlled areas was observed. As an indication of removal, $4.75$ times more stoats were removed from the stoat control program (Hollyford Valley 2001-2004) than caught in by-catch in areas already being controlled prior to the experiment. Our before/after treatment tested this and verified that we did not find differences within the grid when experimental treatments were changed. We may also be missing the impact of by-catch of other pests in stoat traps. We believe that any effect this may have on mice dynamics would be limited due to the limited impacts of rat removal in our data. Biologically, the differences in home range size of rodent species (10's ha; [@bramley2014; @innes1983; @pryde2005]) relative to the home range of stoats and the scale of trap line (100's ha; [@miller2001; @murphy1995]) which suggests that population level impacts from these removals is unlikely due to the limited number of animals removed and the re-invasion biology of rodents [@bramley2014].

Rat removal

Our results suggested that it is unlikely that rats have strong impacts on the rate of increase of mice in NZ beech forests. In part, this could be due to the high variability in the number of rats and kiore between grids and sampling trips in our study (??), which is often the case in non-laboratory studies. Somewhat contrary to our results, previous laboratory experiments suggested that interactions between mice and rats were related to predation or competition effects and limited evidence of competition release has been observed in mixed podocarp-tawa forests in NZ. We found that rats had the smallest impact on mice dynamics (Figure \@ref(fig:figure-three-trends-rats)).

Instead of rats/kiore being present but at low numbers in all grids (low effect size and low uncertainty), there were only a few grids that had comparability high numbers. This result suggests that refugee areas may exist and can support larger rodents in beech forests that current averages suggest. Overall, it is likely that beech forests do not have enough resources to support larger spatially uniform populations of rats. In part this can be atrtributed to the larger size of seeds associated with other native tree species in NZ.

Resource availability

One explanation for this is that Beech forests exhibit the processes defined by resource pulse systems [@wardle1962]. Strong resource pulses cause strong effects throughout an entire ecosystem [@yang2008]. A proposed result of resource-pulse phenomenon are that even in the absence of regulation, predators can not attain high enough densities to limit mouse populations when food availability is high [@king1983]. After comparing a selection of functional responses to our data (Appendix) we found the best fitting model was a type II response and converted our estimated $Seed_{j,k}$ per $m^2$ to the intake rate $S_{j,t}$.

Management implications

Our model has subtle but important differences compared previous research when in comes to management application. The Bayesian model be have build can be fitted to future datasets. We have incorporated a reproducible workflow [@britishecologicalsociety2018] for the future development of model testing for different and new datasets (@wickham2014; See appendix).

In doing this we have incorporated leading reproducible science techniques to help address any aspects of our study may need for further support. Often studies of such large scale can address key population-level questions however these studies struggle to find replication because of the scale at which they are conducted [@oksanen2001]. Many issues that many confront a PFNZ2050 will be reduced by using simple but well fitted BHMs for predicting and allocation management resources.

Predator-free NZ

Our integrated population modelling approach and the large, high-quality CR data used to parametrise the model allowed us to predict and report the biologically relevant effect sizes. We used this to address the direct question of stoat control in NZ Beech Forests. Future studies can now test and assess the beech forest ecosystem compared to the data they collect. By using the unified modelling framework presented in this paper (Appendix; [@davidson2019), reproducible research practises and "tidy-data" [@wickham2014].

Many of the processes we have verified were previously hypothesized using indices of mice abundance [@blackwell2001; @blackwell2003], laboratory experiments [@bridgman2013], novel systems such as remote islands [@mulder2009] and small patches of mainland forest [@blackwell2001; @blackwell2003]. We have integrated these results into a framework that can now test these results in other systems that are hypothesized to be different. It will be important for future work to continue monitoring this system for anomalies and unexpected patterns such as increases in other invasive predators, particularly rats.

davan690/beech-publication-wr documentation built on March 29, 2020, 11:09 a.m.