Population dynamics of small game Pekka Helle Natural Resources Institute Finland Luke Oulu
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
Short-term dynamics Long-term trends How much is normal variation; how many years make a trend?
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.
- 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 - 3-4-year cycles common in Europe especially, but existing also elsewhere - Some populations may be cyclic but some not in the same species
Hudson Bay Company s records (redrawn from Butler 1953)
Average Capercaillie, Black grouse and Hazel grouse densities in Finland during 1963-1988 18 16 14 12 10 8 6 Caper Black Hazel 4 2 0 1960 1970 1980 1990 2000 2010
During 1960s-80s: 6-7 years cycles prevailed Lindström, Jan 1994: Modelling grouse population dynamics. PhD thesis, Univ. Helsinki. 1960 70 80 90 2000
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
Annual bag of black grouse in SW Finland during 1897 1930 What is the population ecological explanation of sin and cosine functions? Of course, none!
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
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
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)
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
18 16 Nation-wide averages - problem of spatial synchrony 14 12 10 8 Caper Black Hazel Willow 6 4 2 0 1960 1970 1980 1990 2000 2010 2020
Black grouse 1964-2015
Autocorrelation function ACF 1964-2015 data into three periods of equal length ----> 1964-1980, 1981-1997, 1998-2015 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
Grouse and voles and their population dynamics are connected via common predators (alternative prey hypothesis, e.g. Angelstam) Asko Kaikusalo
Population cycles of rodents in Kilpisjärvi, Finnish Lapland during 1946-1982 Laine & Henttonen 1983
Vole density in Pallasjärvi (Henttonen, unpubl.) 35 Forests 30 25 Mires My gla My rut My ruf Mi agr Mi oec Lem Density index 20 15 10 5 0 1970 1975 1980 1985 1990 1995 2000 2005 2010
Grey-sided vole in northern Sweden Hörnfelt 2004: Long-term decline in numbers of cyclic voles in boreal Sweden. Oikos 107: 376-392. Ims et al. 2008: Collapsing population cycles. Trends in Ecology and Evolution 23: 79-86. During the past two decades, cycles of voles, forest grouse and forest insects have been fading out in Europe.
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?
Larch budmoth Zeiraphera diniana Esper et al. 2007: 1200 years of regular outbreaks in alpine insects. Proc. Biol. Sci. 274: 671-679. 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
A study from southern Finnish voles shows the opposite (Brommer et al. 2010: Global Change Biology 16: 577-586). Field vole open circle Bank vole filled diamond
SPATIAL ASPECTS
Spatial synchrony in grouse populations1964-2015 15 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 1. 1964-1973 2. 1965-1984.... 43. 2006-2015
year EH ES KY KAI KS LA OU PO PH PK PS RP SA UU VS 1964 7.00 6.83 6.26 3.70 10.71 4.37 10.50 16.36 10.12 7.25 8.22 4.00 10.08 6.46 5.01 1965 7.24 7.94 6.86 7.14 10.70 4.73 15.86 18.03 9.70 8.75 13.31 14.28 7.25 5.45 3.51 1966 7.94 11.98 8.57 12.54 11.92 5.55 14.04 23.01 10.80 8.02 14.86 16.60 8.91 8.26 8.26 1967 6.44 13.85 9.48 5.24 11.70 5.44 12.13 20.11 9.23 8.00 12.41 13.81 9.82 8.23 9.28 1968 5.90 10.36 8.30 5.00 8.71 5.30 6.90 11.16 8.13 6.50 9.06 9.29 7.02 9.93 12.46 1969 5.04 8.64 7.75 8.00 7.05 8.50 8.39 12.92 4.93 7.20 9.51 8.44 7.86 8.84 5.74 1970 3.59 8.05 6.89 9.46 7.66 8.12 8.61 9.16 4.73 7.76 7.03 7.54 7.17 6.09 3.11 1971 3.32 6.57 6.32 6.91 7.02 6.38 6.74 8.93 2.59 7.52 8.45 6.37 6.27 7.01 6.35 1972 3.54 6.21 7.22 6.80 8.65 5.62 7.85 10.67 3.66 6.52 9.22 7.61 7.26 3.99 6.00 1973 3.54 8.27 6.14 7.14 6.31 7.90 8.78 11.24 5.13 9.37 8.87 7.33 8.44 6.41 5.06 1974 3.18 5.16 4.61 5.67 6.61 6.93 9.02 8.70 4.34 6.46 8.04 6.50 7.38 3.27 5.07 1975 3.26 4.45 3.88 4.66 4.92 4.01 5.90 7.35 3.39 5.71 5.15 6.46 7.48 4.57 4.40 1976 1.34 3.90 2.89 3.47 2.62 2.64 4.76 5.26 2.13 2.86 3.54 4.47 4.53 1.86 2.45 1977 1.33 4.38 2.67 5.06 3.91 2.93 4.37 6.06 3.00 3.09 4.72 4.49 4.45 0.90 2.39 1978 2.44 5.03 4.13 4.75 5.72 5.63 5.73 9.93 3.87 4.47 4.84 4.97 5.61 2.26 2.66 2013 4.10 5.50 6.00 7.20 4.80 4.50 6.00 5.10 4.20 6.30 3.20 1.80 6.20 4.90 4.70 2014 2.70 4.10 4.30 4.50 3.80 3.50 4.30 3.10 3.70 5.00 3.40 2.00 4.00 2.40 3.70 2015 3.30 3.10 3.80 4.60 2.30 4.10 3.30 2.70 3.00 4.00 1.30 1.50 3.50 3.30 2.20 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
Sliding window technique 1964-73 43 ten-year windows 4515 correlations per species 2006-15 1964 2015
Cc Bg Hg
Caper Average regional syncrony vs mean density Black Hazel
Red fox synchrony, Finland & Russian Karelia 1990-1995 2000-2005
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
Population structure Change in sex ratio of adult capercaillie populations Percentage of females in adult population 70 65 60 % 55 50 45 64-68 69-73 74-78 79-83 84-88 A B C D D C B A Helle, Kurki & Lindén 1999, Wildlife Biology
60.6 Mean percentages of females in the adult capercaillie population by game mgmt districts during 1995 2010 39.6 52.1 55.6 44.9 47.1 54.4 42.4 40.7 40.9 42.8 38.1 46.2 35.6 40.4
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
Located observations National forest inventory data, satellite-based GIS techniques 4 km