Population dynamics of small game. Pekka Helle Natural Resources Institute Finland Luke Oulu

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1 Population dynamics of small game Pekka Helle Natural Resources Institute Finland Luke Oulu

2 Populations tend to vary in size temporally, some species show more variation than others Depends on degree of specialization, and other life-history characteristics Changes can be short-term and/or long-term Populations can be stable or nearly so, fluctuations can be erratic or cyclic Basic concepts include: - Population growth rate - Carrying capacity of environment - Density dependence - Marriage of temporal and spatial density variation

3 Short-term dynamics Long-term trends How much is normal variation; how many years make a trend?

4 Population growth model (in its simplest form) New population size = old size + births - deaths + immigrated emigrated N(t+1) = N(t)e r [1 - N(t)/K] N = population size t = time r = growth rate K = carrying capacity There are three kinds of mathematicians: Those who can count and those who cant. Anon.

5 - Population cycles have been an object of interest for a long time. - Many northern species show cyclic fluctuations. - North America and Siberia: 10-year year cycles typical year cycles common in Europe especially, but existing also elsewhere - Some populations may be cyclic but some not in the same species

6 Hudson Bay Company s records (redrawn from Butler 1953)

7 Average Capercaillie, Black grouse and Hazel grouse densities in Finland during Caper Black Hazel

8

9 During 1960s-80s: 6-7 years cycles prevailed Lindström, Jan 1994: Modelling grouse population dynamics. PhD thesis, Univ. Helsinki

10 N t = a + b 1 (t) + b 2 cos(t) + b 3 sin(t), where a constant, b 1 captures the trend, b 2 and b 3 together with the trigonometric functions allow for the part of population fluctuation

11 Annual bag of black grouse in SW Finland during What is the population ecological explanation of sin and cosine functions? Of course, none!

12 During increasing phase: - females older than average, producing more offspring - females lay more eggs - females (also/especially old) probably in better physical condition (why is that? spring food, weather, history (year of birth?), better incubators, better in guarding a brood, selecting habitats with less predators), other behavioural responses to predation? During decreasing phase: - factors opposite

13 Elements needed in Finnish grouse cycles: - delayed density dependence - dampening dynamics: random hits are needed - spatial synchrony of populations Reasons: - intrinsic factors; age structure of population - weather effects (did) - predation (dd) - parasites, diseases (dd) - etc. - probably a combination of several factors

14 What could a random hit be? Weather conditions during egg-laying period and (especially) during early brood season Predation especially during vole population low Diseases Parasites A combination of these (and unknown) factors (In addition, population age structure is playing (at least some) role in cyclic fluctuations)

15 Why did the cycles disappear (hypotheses only): - Species densities decreased below a critical threshold due to various reasons (increased predation, lowered habitat quality etc.) to start a new growth - Decreased densities: fewer observations produce more noise to the data - Simulations suggest that minor changes in parameters may alter dynamics: either shortening or lengthening cycles; they may easily disappear and come back as well (*) - If dispersal is needed to maintain spatial synchrony, it may have become weaker due to e.g. habitat fragmentation

16 18 16 Nation-wide averages - problem of spatial synchrony Caper Black Hazel Willow

17 Black grouse

18 Autocorrelation function ACF data into three periods of equal length ----> , , Within each period correlations of densities are calculated for different time lags Time lag 1: year 1 vs 2, 2 vs 3, 3 vs 4 and so on Time lag 2: year 1 vs 3, 2 vs 4, 3 vs 5 and so on Time lag 3: year 1 vs 4, 2 vs 5, 3 vs 6 and so on And so on

19

20 Grouse and voles and their population dynamics are connected via common predators (alternative prey hypothesis, e.g. Angelstam) Asko Kaikusalo

21 Population cycles of rodents in Kilpisjärvi, Finnish Lapland during Laine & Henttonen 1983

22 Vole density in Pallasjärvi (Henttonen, unpubl.) 35 Forests Mires My gla My rut My ruf Mi agr Mi oec Lem Density index

23 Grey-sided vole in northern Sweden Hörnfelt 2004: Long-term decline in numbers of cyclic voles in boreal Sweden. Oikos 107: Ims et al. 2008: Collapsing population cycles. Trends in Ecology and Evolution 23: During the past two decades, cycles of voles, forest grouse and forest insects have been fading out in Europe.

24 Grouse cycles have gone (voles also) (signs of come back?) Spatial synchrony has disappeared (not grouse only) Hypotheses: Present densities too low Dispersal weaker due to Climate change..? How to proceed: correlations maybe misleading, large-scale experiments not possible?

25 Larch budmoth Zeiraphera diniana Esper et al. 2007: 1200 years of regular outbreaks in alpine insects. Proc. Biol. Sci. 274: A lot of evidence that fading of cycles is due to recent climate warming. A study from black grouse in Central Finland supports this idea (Ludwig 2007, Ph. D., University of Jyväskylä) But

26 A study from southern Finnish voles shows the opposite (Brommer et al. 2010: Global Change Biology 16: ). Field vole open circle Bank vole filled diamond

27 SPATIAL ASPECTS

28

29 Spatial synchrony in grouse populations game management districts All pair-wise correlations calculated (105) Mean value is used to describe average regional synchronism Sliding time window technique Synchrony in 10 years periods

30 year EH ES KY KAI KS LA OU PO PH PK PS RP SA UU VS ES EH ES KY KAI KS LA OU PO PH PK PS RP SA UU VS KY KAI KS LA OU PO PH PK PS RP SA UU VS UU

31 Sliding window technique ten-year windows 4515 correlations per species

32 Cc Bg Hg

33 Caper Average regional syncrony vs mean density Black Hazel

34 Red fox synchrony, Finland & Russian Karelia

35 Example: population structure Capercaillie adult sex ratio Proportion of females about 65 % At hatching: sex ratio 50:50 Male chicks suffer from much higher mortality than females for several reasons

36 Population structure Change in sex ratio of adult capercaillie populations Percentage of females in adult population % A B C D D C B A Helle, Kurki & Lindén 1999, Wildlife Biology

37 60.6 Mean percentages of females in the adult capercaillie population by game mgmt districts during

38 How are temporal and spatial dynamics interrelated? Cycles need (necessarily) spatial syncrony spatial syncrony does not need cyclicity If cycling disappers, is it because cycles disappear or spatial syncrony disappers first? Landscape structure and its spatial characteristics may play a role

39 Located observations National forest inventory data, satellite-based GIS techniques 4 km

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